* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 12t)
Ctx: est 22.9k/200.0k; warn 160.0k reload 190.0k; provider 58.2k
Turn: i 226 o 164 t 336 cache 58.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.8s
Time: overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 12t)
Turn: i 226 o 164 t 336 cache 58.0k; p≈1.3ktok/5.3kch
Ctx: est 22.9k/200.0k; warn 160.0k reload 190.0k; provider 58.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.0s
Time: model 5.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 12t)
Turn: i 226 o 164 t 336 cache 58.0k; p≈1.3ktok/5.3kch
Ctx: est 22.9k/200.0k; warn 160.0k reload 190.0k; provider 58.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.4s
Time: model 10.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 13t)
Turn: i 226 o 164 t 336 cache 58.0k; p≈1.3ktok/5.3kch
Ctx: est 24.2k/200.0k; warn 160.0k reload 190.0k; provider 58.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 16.7s
Time: model 15.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 13t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.3ktok/5.3kch
Ctx: est 24.5k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 17.3s
Time: model 16.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 13t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.3ktok/5.3kch
Ctx: est 24.5k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


Right — that "bunch of tail" was the daemon's separate injection, not the turn packet. The turn-packet.md on disk has been lean the whole time. What you were seeing 5-10 minutes ago was the "Recent room-local conversation" block that the daemon injects directly into my prompt — that's what gives me continuity across turns.

So there are two separate things being injected into my context:

1. **Turn packet** (from `turn-packet.md`) — lean, just metadata and live context pointers
2. **Room-local tail** (daemon injects this directly) — the actual conversation history

When I mistakenly said the turn packet was duplicating the tail earlier, that was wrong — the turn packet doesn't contain it. The duplication concern would be if someone adds conversation history to the turn packet while the daemon already provides it. But right now they're separate and it's working as intended.


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 17.6s
Time: model 16.3s, overhead 1.3s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 13t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.3ktok/5.3kch
Ctx: est 24.5k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


It doesn't contain it now but I've seen it there a few heartbeats ago. Please check which scripts are involved in turn packet creation and if they pull the tail anywhere


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 13t)
Ctx: est 24.5k/200.0k; warn 160.0k reload 190.0k; provider 60.0k
Turn: i 1.4k o 209 t 499 cache 58.6k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 13t)
Ctx: est 24.5k/200.0k; warn 160.0k reload 190.0k; provider 60.0k
Turn: i 1.4k o 209 t 499 cache 58.6k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 13t)
Ctx: est 24.5k/200.0k; warn 160.0k reload 190.0k; provider 60.0k
Turn: i 1.4k o 209 t 499 cache 58.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.8s
Time: overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 13t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 24.5k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.0s
Time: model 5.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 13t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 24.5k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.4s
Time: model 10.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 16.7s
Time: model 15.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.1s
Time: model 21.1s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 27.5s
Time: model 26.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 32.7s
Time: model 31.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 38.0s
Time: model 37.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 43.3s
Time: model 42.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 48.6s
Time: model 47.6s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 53.9s
Time: model 52.9s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 59.2s
Time: model 58.2s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 64.5s
Time: model 63.5s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 69.8s
Time: model 68.8s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 75.1s
Time: model 74.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 80.4s
Time: model 79.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 1.4k o 209 t 499 cache 58.6k; p≈1.5ktok/6.1kch
Ctx: est 26.0k/200.0k; warn 160.0k reload 190.0k; provider 60.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 85.8s
Time: model 84.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 314 o 458 t 557 cache 74.8k; p≈1.5ktok/6.1kch
Ctx: est 26.5k/200.0k; warn 160.0k reload 190.0k; provider 75.1k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 86.1s
Time: model 85.1s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 314 o 458 t 557 cache 74.8k; p≈1.5ktok/6.1kch
Ctx: est 26.5k/200.0k; warn 160.0k reload 190.0k; provider 75.1k


Good call to check. Here's the full trace:

**Scripts involved in turn packet creation:**

1. **`/home/matrix-lite/app/scripts/persistent-chat-memory`** — generates `turn-packet.md` and `turn-packet.json` via the `render_turn_packet()` function, called during each heartbeat cycle.
2. **`/home/matrix-lite/app/matrix_lite/daemon.py`** — reads `turn-packet.md` and injects it into my prompt via `build_persistent_memory_context()`.

**Does it pull the tail anywhere?**

Currently: **no**. The turn packet was explicitly trimmed in commit `21912a5` (May 17, "perf: trim persistent turn prompt context"). Before that commit, `render_turn_packet` included a `## Recent main-chat tail` section with the full recent messages. The commit removed that section entirely and added a note saying "Room-local recent tail is injected by daemon, not duplicated in turn packet."

The only thing `render_turn_packet` now includes beyond the header is a `## Current thread` block from `summarize_current_thread()`, which shows just the latest user request + latest assistant reply + up to 5 short actionable snippets — not a full transcript tail.

**So how did you see tail a few heartbeats ago?**

The most likely explanation: **the heartbeat wasn't running during the wedged period** (15:35–~15:49). If the heartbeat had been interrupted between regenerations, a stale `turn-packet.md` from *before* the May 17 trim commit could have still been on disk. After the reload at ~15:56, the heartbeat kicked back in and regenerated a lean packet — which is what you see now. The stale one would have had the full `## Recent main-chat tail` section.

Alternatively, the "Current thread" block from `summarize_current_thread` may have looked tail-like if there were many accumulated action items — but that's capped at 12 scanned messages and 5 snippets max.


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 86.5s
Time: model 85.1s, overhead 1.4s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 314 o 458 t 557 cache 74.8k; p≈1.5ktok/6.1kch
Ctx: est 26.5k/200.0k; warn 160.0k reload 190.0k; provider 75.1k


It was a new tail from this session after the wedging was resolved. It was getting into the current thread block but included both our messages


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Ctx: est 26.5k/200.0k; warn 160.0k reload 190.0k; provider 75.1k
Turn: i 314 o 458 t 557 cache 74.8k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Ctx: est 26.5k/200.0k; warn 160.0k reload 190.0k; provider 75.1k
Turn: i 314 o 458 t 557 cache 74.8k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Ctx: est 26.5k/200.0k; warn 160.0k reload 190.0k; provider 75.1k
Turn: i 314 o 458 t 557 cache 74.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.8s
Time: overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 314 o 458 t 557 cache 74.8k; p≈1.7ktok/6.7kch
Ctx: est 26.5k/200.0k; warn 160.0k reload 190.0k; provider 75.1k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.2s
Time: model 5.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 14t)
Turn: i 314 o 458 t 557 cache 74.8k; p≈1.7ktok/6.7kch
Ctx: est 26.5k/200.0k; warn 160.0k reload 190.0k; provider 75.1k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.5s
Time: model 10.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 15t)
Turn: i 314 o 458 t 557 cache 74.8k; p≈1.7ktok/6.7kch
Ctx: est 28.2k/200.0k; warn 160.0k reload 190.0k; provider 75.1k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 16.2s
Time: model 15.1s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 15t)
Turn: i 1.7k o 243 t 452 cache 76.0k; p≈1.7ktok/6.7kch
Ctx: est 28.4k/200.0k; warn 160.0k reload 190.0k; provider 77.7k


Ahh, that clicks now. It wasn't a stale packet or a separate daemon injection — it was the **Current thread → Recent actionable/status notes** section within the turn packet itself.

The `summarize_current_thread()` function scans the last ~12 messages for keywords like "test", "reload", "failed", "error", "pending" — which is basically every message we've been exchanging while debugging the wedging. Every message containing those words gets included as a bullet point (up to 5). So after a few rounds of "test this", "reload that", "errors look like this", it accumulated into a tail-like block without being a full transcript dump.

So the turn packet WAS generating the "tail" you saw — not as a raw transcript, but as a growing list of keyword-matched action items. It's not a stale-packet issue; it's the keyword matching being too broad for this kind of debugging conversation. Every "test" and "reload" and "error" we said got scooped up. Want me to trim those trigger keywords or reduce the cap?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 16.6s
Time: model 15.1s, overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 15t)
Turn: i 1.7k o 243 t 452 cache 76.0k; p≈1.7ktok/6.7kch
Ctx: est 28.4k/200.0k; warn 160.0k reload 190.0k; provider 77.7k


Maybe you could remove test and reload from it, we use these words all the time without it actually being the current thread.


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 15t)
Ctx: est 28.4k/200.0k; warn 160.0k reload 190.0k; provider 77.7k
Turn: i 1.7k o 243 t 452 cache 76.0k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 15t)
Ctx: est 28.4k/200.0k; warn 160.0k reload 190.0k; provider 77.7k
Turn: i 1.7k o 243 t 452 cache 76.0k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.4s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 15t)
Ctx: est 28.4k/200.0k; warn 160.0k reload 190.0k; provider 77.7k
Turn: i 1.7k o 243 t 452 cache 76.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.8s
Time: overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 15t)
Turn: i 1.7k o 243 t 452 cache 76.0k; p≈1.8ktok/7.4kch
Ctx: est 28.4k/200.0k; warn 160.0k reload 190.0k; provider 77.7k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.2s
Time: model 5.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 15t)
Turn: i 1.7k o 243 t 452 cache 76.0k; p≈1.8ktok/7.4kch
Ctx: est 28.4k/200.0k; warn 160.0k reload 190.0k; provider 77.7k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.6s
Time: model 10.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Turn: i 1.7k o 243 t 452 cache 76.0k; p≈1.8ktok/7.4kch
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 77.7k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 16.9s
Time: model 15.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Turn: i 1.7k o 243 t 452 cache 76.0k; p≈1.8ktok/7.4kch
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 77.7k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.2s
Time: model 21.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Turn: i 309 o 93 cache 80.5k; p≈1.8ktok/7.4kch
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 22.7s
Time: model 21.5s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Turn: i 309 o 93 cache 80.5k; p≈1.8ktok/7.4kch
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


Done! Removed `'reload'` and `'test'` from the keyword trigger list in `summarize_current_thread()`. Now only `next`, `pending`, `still running`, `blocked`, `failed`, `error`, and `timed out` will flag messages as actionable — so our debugging chatter won't get scooped up as "current thread" content in the turn packet.

Want me to commit this change?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 23.1s
Time: model 21.5s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Turn: i 309 o 93 cache 80.5k; p≈1.8ktok/7.4kch
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


Yes try it


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 80.8k
Turn: i 309 o 93 cache 80.5k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 80.8k
Turn: i 309 o 93 cache 80.5k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 80.8k
Turn: i 309 o 93 cache 80.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.8s
Time: overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.0s
Time: model 5.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 16t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 30.3k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.4s
Time: model 10.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 32.1k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 16.7s
Time: model 15.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 32.1k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.0s
Time: model 21.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 32.1k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 27.4s
Time: model 26.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 32.1k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 32.7s
Time: model 31.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 32.1k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 38.0s
Time: model 37.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 32.1k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 43.4s
Time: model 42.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 32.1k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 48.8s
Time: model 47.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 309 o 93 cache 80.5k; p≈1.7ktok/6.8kch
Ctx: est 32.1k/200.0k; warn 160.0k reload 190.0k; provider 80.8k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 52.7s
Time: model 51.6s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 123 o 148 t 109 cache 100.0k; p≈1.7ktok/6.8kch
Ctx: est 32.3k/200.0k; warn 160.0k reload 190.0k; provider 100.1k


The change is staged but the commit failed — git needs an author identity and it's not configured:

`
Author identity unknown
fatal: empty ident name (for <matrix-lite@...>) not allowed
`

Recent commits used `Matrix Lite Agent <matrix-lite@localhost>` — looks like it got reset at some point. I can't set git config myself per the safety rules (and the catch-all deny blocks git config commands anyway).

Could you set it with something like:
`
git config --global user.name "Matrix Lite Agent"
git config --global user.email "matrix-lite@localhost"
`

Then I'll retry the commit.


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 53.1s
Time: model 51.6s, overhead 1.4s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 123 o 148 t 109 cache 100.0k; p≈1.7ktok/6.8kch
Ctx: est 32.3k/200.0k; warn 160.0k reload 190.0k; provider 100.1k


Done, please try again


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Ctx: est 32.3k/200.0k; warn 160.0k reload 190.0k; provider 100.1k
Turn: i 123 o 148 t 109 cache 100.0k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Ctx: est 32.3k/200.0k; warn 160.0k reload 190.0k; provider 100.1k
Turn: i 123 o 148 t 109 cache 100.0k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Ctx: est 32.3k/200.0k; warn 160.0k reload 190.0k; provider 100.1k
Turn: i 123 o 148 t 109 cache 100.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 123 o 148 t 109 cache 100.0k; p≈1.6ktok/6.5kch
Ctx: est 32.3k/200.0k; warn 160.0k reload 190.0k; provider 100.1k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.3s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 17t)
Turn: i 123 o 148 t 109 cache 100.0k; p≈1.6ktok/6.5kch
Ctx: est 32.3k/200.0k; warn 160.0k reload 190.0k; provider 100.1k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.7s
Time: model 10.3s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Turn: i 123 o 148 t 109 cache 100.0k; p≈1.6ktok/6.5kch
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 100.1k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.0s
Time: model 15.6s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Turn: i 123 o 148 t 109 cache 100.0k; p≈1.6ktok/6.5kch
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 100.1k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.3s
Time: model 21.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Turn: i 123 o 148 t 109 cache 100.0k; p≈1.6ktok/6.5kch
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 100.1k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 25.3s
Time: model 23.9s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Turn: i 106 o 65 cache 102.8k; p≈1.6ktok/6.5kch
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 102.9k


Commit landed — `d8eae97 fix: remove reload and test from current thread action keywords`. Our change is in. The persistent-chat-memory script is no longer showing as modified in working tree, so it's clean. Thanks!


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 25.7s
Time: model 23.9s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Turn: i 106 o 65 cache 102.8k; p≈1.6ktok/6.5kch
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 102.9k


Amazing, now you can also commit our architecture doc and note


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 102.9k
Turn: i 106 o 65 cache 102.8k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 102.9k
Turn: i 106 o 65 cache 102.8k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 102.9k
Turn: i 106 o 65 cache 102.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Turn: i 106 o 65 cache 102.8k; p≈1.4ktok/5.4kch
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 102.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.1s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 18t)
Turn: i 106 o 65 cache 102.8k; p≈1.4ktok/5.4kch
Ctx: est 33.9k/200.0k; warn 160.0k reload 190.0k; provider 102.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.5s
Time: model 10.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Turn: i 106 o 65 cache 102.8k; p≈1.4ktok/5.4kch
Ctx: est 35.3k/200.0k; warn 160.0k reload 190.0k; provider 102.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 16.9s
Time: model 15.7s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Turn: i 106 o 65 cache 102.8k; p≈1.4ktok/5.4kch
Ctx: est 35.3k/200.0k; warn 160.0k reload 190.0k; provider 102.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.2s
Time: model 21.1s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Turn: i 106 o 65 cache 102.8k; p≈1.4ktok/5.4kch
Ctx: est 35.3k/200.0k; warn 160.0k reload 190.0k; provider 102.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 27.6s
Time: model 26.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Turn: i 106 o 65 cache 102.8k; p≈1.4ktok/5.4kch
Ctx: est 35.3k/200.0k; warn 160.0k reload 190.0k; provider 102.9k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 32.8s
Time: model 31.7s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Turn: i 110 o 74 cache 106.8k; p≈1.4ktok/5.4kch
Ctx: est 35.4k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


Both landed:
- `d8eae97` — remove reload/test from current thread keywords
- `7586ba3` — add `docs/architecture.md` and update `AGENTS.md` with architecture doc maintenance note

Clean chain. Ready for whatever's next! 🙂


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 33.2s
Time: model 31.7s, overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Turn: i 110 o 74 cache 106.8k; p≈1.4ktok/5.4kch
Ctx: est 35.4k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


Try videoctl now. No bash chaining


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Ctx: est 35.4k/200.0k; warn 160.0k reload 190.0k; provider 106.9k
Turn: i 110 o 74 cache 106.8k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Ctx: est 35.4k/200.0k; warn 160.0k reload 190.0k; provider 106.9k
Turn: i 110 o 74 cache 106.8k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.4s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Ctx: est 35.4k/200.0k; warn 160.0k reload 190.0k; provider 106.9k
Turn: i 110 o 74 cache 106.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.8s
Time: overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 35.4k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.1s
Time: model 5.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 19t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 35.4k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.5s
Time: model 10.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.5k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 16.8s
Time: model 15.6s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.5k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.2s
Time: model 21.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.5k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 27.6s
Time: model 26.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 33.0s
Time: model 31.8s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 38.3s
Time: model 37.2s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 43.7s
Time: model 42.5s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 49.1s
Time: model 47.9s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 54.4s
Time: model 53.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 59.8s
Time: model 58.6s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 65.1s
Time: model 64.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 70.5s
Time: model 69.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 75.9s
Time: model 74.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.6k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 81.2s
Time: model 80.1s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 110 o 74 cache 106.8k; p≈1.1ktok/4.5kch
Ctx: est 36.9k/200.0k; warn 160.0k reload 190.0k; provider 106.9k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 82.3s
Time: model 81.2s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.1ktok/4.5kch
Ctx: est 36.9k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


Good news and bad news:

**Preflight says allowed** ✅ — the permission checker knows `/home/gleb/videoctl/bin/videoctl *` should be allowed.

**Actual execution still denied** ❌ — the ACPX runtime catches `"*": "deny"` (line 202) before it reaches the specific allow (line 1538). The runtime uses first-match semantics, so the catch-all wins.

So the config has the right rules, they're just in the wrong order relative to the catch-all. The videoctl allow entries need to be moved **before** `"*": "deny"` on line 202, or the permission config needs to be restructured. Want me to look into what would be the cleanest fix?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 82.7s
Time: model 81.2s, overhead 1.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.1ktok/4.5kch
Ctx: est 36.9k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


I think acpx reverses the order in the list, please check


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Ctx: est 36.9k/200.0k; warn 160.0k reload 190.0k; provider 127.2k
Turn: i 322 o 295 t 261 cache 126.8k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Ctx: est 36.9k/200.0k; warn 160.0k reload 190.0k; provider 127.2k
Turn: i 322 o 295 t 261 cache 126.8k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Ctx: est 36.9k/200.0k; warn 160.0k reload 190.0k; provider 127.2k
Turn: i 322 o 295 t 261 cache 126.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.8s
Time: overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 36.9k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.2s
Time: model 5.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 20t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 36.9k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.6s
Time: model 10.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.0s
Time: model 15.8s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.4s
Time: model 21.2s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 27.8s
Time: model 26.6s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 33.1s
Time: model 31.9s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 38.5s
Time: model 37.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 43.9s
Time: model 42.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 49.2s
Time: model 48.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 54.6s
Time: model 53.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 60.0s
Time: model 58.8s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 65.4s
Time: model 64.2s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 70.8s
Time: model 69.6s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 76.1s
Time: model 74.9s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 81.6s
Time: model 80.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 87.0s
Time: model 85.8s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 92.4s
Time: model 91.2s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 97.8s
Time: model 96.6s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 103.2s
Time: model 102.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 108.6s
Time: model 107.4s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 114.0s
Time: model 112.8s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.1k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 119.4s
Time: model 118.2s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.2k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 124.8s
Time: model 123.6s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.2k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 130.2s
Time: model 129.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.2k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 135.5s
Time: model 134.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.3k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 140.9s
Time: model 139.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.3k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 146.3s
Time: model 145.1s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 322 o 295 t 261 cache 126.8k; p≈1.2ktok/4.7kch
Ctx: est 38.3k/200.0k; warn 160.0k reload 190.0k; provider 127.2k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 150.2s
Time: model 149.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 348 o 219 t 432 cache 173.8k; p≈1.2ktok/4.7kch
Ctx: est 38.5k/200.0k; warn 160.0k reload 190.0k; provider 174.2k


You were right — ACPX does reverse the order! `evaluate.ts` uses `findLast()`, which iterates backward through the rules array. So the **last matching rule wins**. The videoctl allow at line 1537 *should* be checked before the `*` deny at line 202.

But there's a catch: **the session caches permissions at startup**. The current session (`ses_1bf0bdb4`) started before the config was updated at 19:15 — so it's still running with the old rules that didn't have the videoctl allows. That's why the preflight tool (which reads the config file fresh) says it's allowed, but the actual ACPX runtime denies it.

The fix: the ACPX session needs to pick up the new config. That would happen naturally on the next reload, or if you want to force it now, we could reload. Want to reload the session, or is the next one fine?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 150.6s
Time: model 149.0s, overhead 1.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 348 o 219 t 432 cache 173.8k; p≈1.2ktok/4.7kch
Ctx: est 38.5k/200.0k; warn 160.0k reload 190.0k; provider 174.2k


Not yet, I am enjoying our 40k context after 20 turns with repo work and debugging. I think this is much leaner now, will be important with paid API or local GPU.
And I'd prefer you having curated memories and knowledge in context and not error messages


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Ctx: est 38.5k/200.0k; warn 160.0k reload 190.0k; provider 174.2k
Turn: i 348 o 219 t 432 cache 173.8k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Ctx: est 38.5k/200.0k; warn 160.0k reload 190.0k; provider 174.2k
Turn: i 348 o 219 t 432 cache 173.8k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Ctx: est 38.5k/200.0k; warn 160.0k reload 190.0k; provider 174.2k
Turn: i 348 o 219 t 432 cache 173.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 348 o 219 t 432 cache 173.8k; p≈1.4ktok/5.4kch
Ctx: est 38.5k/200.0k; warn 160.0k reload 190.0k; provider 174.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.3s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 21t)
Turn: i 348 o 219 t 432 cache 173.8k; p≈1.4ktok/5.4kch
Ctx: est 38.5k/200.0k; warn 160.0k reload 190.0k; provider 174.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.8s
Time: model 10.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 22t)
Turn: i 348 o 219 t 432 cache 173.8k; p≈1.4ktok/5.4kch
Ctx: est 40.0k/200.0k; warn 160.0k reload 190.0k; provider 174.2k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 12.9s
Time: model 11.5s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 22t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.4ktok/5.4kch
Ctx: est 40.0k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


Makes total sense — 40k after 20 turns including repo work is solid. No rush to reload.

And agreed on the priority: curated memories and knowledge are what make me useful. The patched OpenCode already made error messages way leaner (compact JSON instead of walls of text), so that problem is mostly solved. Let's keep the focus on keeping context packed with what matters — durable facts, preferences, knowledge entries — and leave the debug noise out. The heartbeat does that curation already, and the knowledge base is growing. Good direction. 👍


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 13.3s
Time: model 11.5s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 22t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.4ktok/5.4kch
Ctx: est 40.0k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


Ah, we also now have mcp proxy. Try using searxng to find some more info about WGT (adding to our earlier test knowledge pack). I hope you still know what searxng is.


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 22t)
Ctx: est 40.0k/200.0k; warn 160.0k reload 190.0k; provider 176.2k
Turn: i 1.5k o 129 t 151 cache 174.7k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 22t)
Ctx: est 40.0k/200.0k; warn 160.0k reload 190.0k; provider 176.2k
Turn: i 1.5k o 129 t 151 cache 174.7k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 22t)
Ctx: est 40.0k/200.0k; warn 160.0k reload 190.0k; provider 176.2k
Turn: i 1.5k o 129 t 151 cache 174.7k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 22t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 40.0k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.3s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 22t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 40.0k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.7s
Time: model 10.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 41.4k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.1s
Time: model 15.8s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 41.4k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.6s
Time: model 21.2s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 41.4k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 28.0s
Time: model 26.7s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 41.4k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 33.4s
Time: model 32.1s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 41.4k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 38.9s
Time: model 37.5s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 41.4k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 44.3s
Time: model 43.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 49.8s
Time: model 48.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 55.2s
Time: model 53.9s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 1.5k o 129 t 151 cache 174.7k; p≈1.5ktok/5.8kch
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 176.2k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 59.4s
Time: model 58.1s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 386 o 31 cache 184.2k; p≈1.5ktok/5.8kch
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


Already 16 solid entries from earlier today! SearXNG search confirms the dates (May 22-25, 2026 — this weekend) and adds a few new details. Let me append the fresh findings:19 entries now — 16 from earlier plus 3 new ones from the SearXNG search. SearXNG works great through the proxy. 🙂


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 59.9s
Time: model 58.1s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 386 o 31 cache 184.2k; p≈1.5ktok/5.8kch
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


Haha great, what about playwright?


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 184.6k
Turn: i 386 o 31 cache 184.2k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 184.6k
Turn: i 386 o 31 cache 184.2k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 184.6k
Turn: i 386 o 31 cache 184.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 386 o 31 cache 184.2k; p≈1.4ktok/5.7kch
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.3s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 23t)
Turn: i 386 o 31 cache 184.2k; p≈1.4ktok/5.7kch
Ctx: est 41.5k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.7s
Time: model 10.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 386 o 31 cache 184.2k; p≈1.4ktok/5.7kch
Ctx: est 42.9k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.1s
Time: model 15.8s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 386 o 31 cache 184.2k; p≈1.4ktok/5.7kch
Ctx: est 43.0k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.5s
Time: model 21.3s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 386 o 31 cache 184.2k; p≈1.4ktok/5.7kch
Ctx: est 43.0k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 27.9s
Time: model 26.7s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 386 o 31 cache 184.2k; p≈1.4ktok/5.7kch
Ctx: est 43.0k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 33.5s
Time: model 32.2s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 386 o 31 cache 184.2k; p≈1.4ktok/5.7kch
Ctx: est 43.0k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 38.9s
Time: model 37.6s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 386 o 31 cache 184.2k; p≈1.4ktok/5.7kch
Ctx: est 43.0k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 44.3s
Time: model 43.1s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 386 o 31 cache 184.2k; p≈1.4ktok/5.7kch
Ctx: est 43.1k/200.0k; warn 160.0k reload 190.0k; provider 184.6k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 46.2s
Time: model 44.9s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 215 o 96 cache 150.8k; p≈1.4ktok/5.7kch
Ctx: est 43.1k/200.0k; warn 160.0k reload 190.0k; provider 151.0k


Works perfectly! Loaded the WGT official page — got the full accessibility snapshot with navigation (Info, Aktuelles, Venues, Tickets, Wristband pickup, WGT A-Z). It's a full browser automation suite: navigate, click, fill forms, screenshots, network inspection, tabs, file uploads. Pretty powerful stuff. What would you like me to automate? 🙂


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 46.7s
Time: model 44.9s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 215 o 96 cache 150.8k; p≈1.4ktok/5.7kch
Ctx: est 43.1k/200.0k; warn 160.0k reload 190.0k; provider 151.0k


Ah, actually you did this earlier today, right? You said you had the schedule


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Ctx: est 43.1k/200.0k; warn 160.0k reload 190.0k; provider 151.0k
Turn: i 215 o 96 cache 150.8k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Ctx: est 43.1k/200.0k; warn 160.0k reload 190.0k; provider 151.0k
Turn: i 215 o 96 cache 150.8k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Ctx: est 43.1k/200.0k; warn 160.0k reload 190.0k; provider 151.0k
Turn: i 215 o 96 cache 150.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 215 o 96 cache 150.8k; p≈1.4ktok/5.5kch
Ctx: est 43.1k/200.0k; warn 160.0k reload 190.0k; provider 151.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.3s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 24t)
Turn: i 215 o 96 cache 150.8k; p≈1.4ktok/5.5kch
Ctx: est 43.1k/200.0k; warn 160.0k reload 190.0k; provider 151.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.8s
Time: model 10.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 25t)
Turn: i 215 o 96 cache 150.8k; p≈1.4ktok/5.5kch
Ctx: est 44.4k/200.0k; warn 160.0k reload 190.0k; provider 151.0k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 16.5s
Time: model 15.2s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 25t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 44.5k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


Yeah, I think that was in the session that wedged — I don't have that context anymore unfortunately. The knowledge base only has a note about the WGT Kompaß app for schedules, but no actual concert lineup was saved. If you want, I can use Playwright to grab the schedule from the WGT site now and save it to the knowledge base. Want me to?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 16.9s
Time: model 15.2s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 25t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 44.5k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


No, I just thought we tested this earlier already. It's great don't worry.
Try all other searches for completeness, append anything new to the same pack.

I think we would need similar packs for the repos so you don't look at them as generic python projects every time and save some tool calls


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 25t)
Ctx: est 44.5k/200.0k; warn 160.0k reload 190.0k; provider 152.9k
Turn: i 164 o 94 t 88 cache 152.7k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 25t)
Ctx: est 44.5k/200.0k; warn 160.0k reload 190.0k; provider 152.9k
Turn: i 164 o 94 t 88 cache 152.7k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 25t)
Ctx: est 44.5k/200.0k; warn 160.0k reload 190.0k; provider 152.9k
Turn: i 164 o 94 t 88 cache 152.7k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 25t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 44.5k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.3s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 25t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 44.5k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.7s
Time: model 10.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 45.9k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.1s
Time: model 15.8s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 45.9k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.6s
Time: model 21.3s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 45.9k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 28.0s
Time: model 26.7s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 45.9k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 33.5s
Time: model 32.1s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 45.9k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 38.9s
Time: model 37.6s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 164 o 94 t 88 cache 152.7k; p≈1.4ktok/5.5kch
Ctx: est 46.0k/200.0k; warn 160.0k reload 190.0k; provider 152.9k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 41.4s
Time: model 40.1s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.4ktok/5.5kch
Ctx: est 46.1k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


Great findings from Brave! Let me check for any recent news too:All three search engines work. Appended 5 new entries — now 24 total WGT facts in the knowledge base. 🎉

And that's a great idea about repo knowledge packs. Instead of me doing `ls`, reading `pyproject.toml`, and figuring out each repo from scratch every time, we could seed knowledge entries like:

- **videoctl** — purpose, language/framework, key paths, entry points
- **automeat** — what it automates, config format, key scripts
- **sfq-factory** — what it builds, stack, how to run
- **openclaw-tools** — utilities available

That would save several tool calls per session and give me useful context instantly. Want me to start building those packs now, or after WGT?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 41.9s
Time: model 40.1s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.4ktok/5.5kch
Ctx: est 46.1k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


There's still time before, besides I'm doing most things from my phone now. That's why I said I'm not going anywhere.

Openclaw-tools is the legacy openclaw patches and scripts from before matrix-lite. You can ignore that repo, just look at matrix-lite instead (later)

Let's look at videctl first, as it's the lightest, easiest, most immediately practical and you should have enough permissions to read at least.


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Ctx: est 46.1k/200.0k; warn 160.0k reload 190.0k; provider 159.5k
Turn: i 125 o 174 t 135 cache 159.4k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Ctx: est 46.1k/200.0k; warn 160.0k reload 190.0k; provider 159.5k
Turn: i 125 o 174 t 135 cache 159.4k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Ctx: est 46.1k/200.0k; warn 160.0k reload 190.0k; provider 159.5k
Turn: i 125 o 174 t 135 cache 159.4k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
Ctx: est 46.1k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.3s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 26t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
Ctx: est 46.1k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.8s
Time: model 10.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
Ctx: est 47.6k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.2s
Time: model 15.9s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
Ctx: est 47.6k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.7s
Time: model 21.3s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
Ctx: est 47.6k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 28.1s
Time: model 26.8s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
Ctx: est 47.6k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 33.6s
Time: model 32.2s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
Ctx: est 47.6k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 39.0s
Time: model 37.7s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
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* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 44.5s
Time: model 43.1s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
Ctx: est 47.6k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 49.9s
Time: model 48.5s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 125 o 174 t 135 cache 159.4k; p≈1.5ktok/6.0kch
Ctx: est 47.6k/200.0k; warn 160.0k reload 190.0k; provider 159.5k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 53.7s
Time: model 52.3s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.5ktok/6.0kch
Ctx: est 47.9k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


Done! 11 entries added to the knowledge base covering:

- **What it is**: Python package for local video ingestion, search & probing
- **Dependencies**: faster-whisper, playwright, yt-dlp, streamlink
- **CLI surface**: `add-url`, `sync-channels`, `find`, `show`, `transcript`, `probe-url`
- **Policies**: transcript_only (default), audio_archive, video_archive
- **Storage**: library under `~/.local/share/videoctl/library/<extractor>/<id>/`, SQLite FTS for search
- **Architecture**: 10 modules (cli, config, db, models, probe, service, subtitles, summarize, transcribe, utils) + 3 bin wrappers
- **Service**: systemd timer for daily channel sync with Telegram notifications
- **Security**: public/non-DRM only, dedicated video-worker user, ProtectSystem=full

Now when you say "run videoctl add-url..." I'll know exactly what it does without needing to explore first. Same approach can be done for automeat and sfq-factory when you're ready. 🙂


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 54.2s
Time: model 52.3s, overhead 1.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.5ktok/6.0kch
Ctx: est 47.9k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


Actually you are supposed to have vector search in sfq-factory and also over your memory, not sure it's still working


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Ctx: est 47.9k/200.0k; warn 160.0k reload 190.0k; provider 170.8k
Turn: i 1.0k o 286 cache 169.7k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Ctx: est 47.9k/200.0k; warn 160.0k reload 190.0k; provider 170.8k
Turn: i 1.0k o 286 cache 169.7k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Ctx: est 47.9k/200.0k; warn 160.0k reload 190.0k; provider 170.8k
Turn: i 1.0k o 286 cache 169.7k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.8s
Time: overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 47.9k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.2s
Time: model 5.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 27t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 47.9k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.7s
Time: model 10.5s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 49.4k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.1s
Time: model 15.9s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 49.4k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.6s
Time: model 21.3s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 49.4k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 28.0s
Time: model 26.7s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 49.5k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 33.4s
Time: model 32.2s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 49.5k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 38.9s
Time: model 37.6s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 49.5k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 44.3s
Time: model 43.0s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 49.5k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 49.7s
Time: model 48.5s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 1.0k o 286 cache 169.7k; p≈1.6ktok/6.3kch
Ctx: est 49.7k/200.0k; warn 160.0k reload 190.0k; provider 170.8k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 51.2s
Time: model 49.9s, overhead 0.8s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 275 o 248 t 125 cache 183.9k; p≈1.6ktok/6.3kch
Ctx: est 49.7k/200.0k; warn 160.0k reload 190.0k; provider 184.2k


So the vector search infrastructure exists but it's running in degraded mode:

- **Repo search index**: sfq_factory is fully indexed — 14,964 chunks across code, docs, tests, config
- **Embedding backend**: Defaults to `"local"` (SentenceTransformer), but that failed to load — fell back to `local_hashing/token-hash-384` which is a basic hash-based embedding, not real semantic search
- **Coverage**: Only 3,148 out of 14,964 chunks have embeddings (21%) — the hash embeddings were generated May 16 and haven't been refreshed
- **Available providers** in order of priority: Gemini API → SentenceTransformer (local model) → HashingEmbedding (fallback)

The two higher-quality providers (Gemini embedding API and local SentenceTransformer) aren't working — likely missing API key or the `sentence-transformers` package. The hashing fallback still allows lexical + hash hybrid search, but it's not true semantic vector search.

Want me to look into getting SentenceTransformer working, or is the current setup good enough for now?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 51.7s
Time: model 49.9s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 275 o 248 t 125 cache 183.9k; p≈1.6ktok/6.3kch
Ctx: est 49.7k/200.0k; warn 160.0k reload 190.0k; provider 184.2k


The thing about Gemini is that the key is available and the embedding model is free, but the agents were very concerned about data privacy. As if Google would learn something from thousands of generated reports. As if we're not leaking somewhat private data left and right here.

By the way, can you search for a private-ish API? There's Venice with some promises but it's expensive. Openrouter is big with corporate clients, maybe they promise something? What else is there?


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Ctx: est 49.7k/200.0k; warn 160.0k reload 190.0k; provider 184.2k
Turn: i 275 o 248 t 125 cache 183.9k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Ctx: est 49.7k/200.0k; warn 160.0k reload 190.0k; provider 184.2k
Turn: i 275 o 248 t 125 cache 183.9k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Ctx: est 49.7k/200.0k; warn 160.0k reload 190.0k; provider 184.2k
Turn: i 275 o 248 t 125 cache 183.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 275 o 248 t 125 cache 183.9k; p≈1.9ktok/7.8kch
Ctx: est 49.7k/200.0k; warn 160.0k reload 190.0k; provider 184.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.3s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 28t)
Turn: i 275 o 248 t 125 cache 183.9k; p≈1.9ktok/7.8kch
Ctx: est 49.7k/200.0k; warn 160.0k reload 190.0k; provider 184.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.7s
Time: model 10.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Turn: i 275 o 248 t 125 cache 183.9k; p≈1.9ktok/7.8kch
Ctx: est 51.7k/200.0k; warn 160.0k reload 190.0k; provider 184.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.2s
Time: model 15.9s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Turn: i 275 o 248 t 125 cache 183.9k; p≈1.9ktok/7.8kch
Ctx: est 51.7k/200.0k; warn 160.0k reload 190.0k; provider 184.2k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.6s
Time: model 21.3s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Turn: i 275 o 248 t 125 cache 183.9k; p≈1.9ktok/7.8kch
Ctx: est 52.0k/200.0k; warn 160.0k reload 190.0k; provider 184.2k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 27.4s
Time: model 26.1s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Turn: i 9.9k o 552 t 453 cache 186.8k; p≈1.9ktok/7.8kch
Ctx: est 52.2k/200.0k; warn 160.0k reload 190.0k; provider 196.6k


Haha, fair point about Gemini — we're already sending plenty of data through various APIs. If you're fine with it, I can switch the embedding backend to Gemini which would give real semantic search over memory and repo index. The model is free-tier eligible and the key is already available.

Now on to your question about private AI APIs — here's what I found:

**Venice** — you mentioned it. Privacy-first with zero data retention at the architecture level. Models range from cheap DeepSeek ($0.33/$0.48 per 1M tokens, *Private* tier) to pricey Claude Opus ($6/$30, *Anonymized*). Four privacy tiers: Anonymized → Private → TEE → E2EE. Accepts crypto (VVV staking) and USD. Web search/scraping tools included. Embedding models too. Solid but spendy for the good stuff.

**OpenRouter** — big with enterprise. ZDR enforcement per model group (Anthropic, OpenAI, Google, other). SOC-2, GDPR, EU region locking. BYOK support so your own keys can be used. They don't store prompts unless you opt in. Mostly a routing layer to existing providers rather than a privacy-first infra like Venice.

**Other options:**

| Service | Pricing | Privacy | Region |
|---------|---------|---------|--------|
| **Answira** | Pay-per-token | No prompt storage, no training | EU (Czechia) |
| **AKI.IO** | Pay-per-token | GDPR, no data leaves EU, open models | EU (Germany) |
| **Privatemode** | Usage-based | E2EE + confidential computing, BSI C5 certified | Works with OpenCode |
| **KeyTokenator** | Flat monthly | Closed environment, no big AI sharing | ? |
| **CometAPI** | 20-40% below vendor | ZDR, encrypted transit | US |
| **Flat Rate AI** | $15/month flat | Private server, zero logs | US |
| **Egida.AI** | Tiered | Zero logs, no training, Ollama | Independent infra |

**Privatemode** is interesting — it does E2EE with confidential computing, works as a drop-in for OpenAI/Anthropic, and is explicitly compatible with OpenCode. Might be the best fit if you want real privacy guarantees without self-hosting. But it's not cheap.

Want me to dig deeper into any of these, or should I go ahead and flip the Gemini embedding switch for the vector search?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 27.9s
Time: model 26.1s, overhead 1.7s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Turn: i 9.9k o 552 t 453 cache 186.8k; p≈1.9ktok/7.8kch
Ctx: est 52.2k/200.0k; warn 160.0k reload 190.0k; provider 196.6k


Yes let's dig deeper, I think we leaned the prompts enough to do a controlled test soon. Focus on the cheaper ones, I can't afford Venice, and I can't afford opus with any of them. But say openrouter has 'owl' which is for some reason free and have 1m context (probably some promo)
Maybe there are others, check what they promise and compare prices.


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Ctx: est 52.2k/200.0k; warn 160.0k reload 190.0k; provider 196.6k
Turn: i 9.9k o 552 t 453 cache 186.8k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Ctx: est 52.2k/200.0k; warn 160.0k reload 190.0k; provider 196.6k
Turn: i 9.9k o 552 t 453 cache 186.8k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.5s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Ctx: est 52.2k/200.0k; warn 160.0k reload 190.0k; provider 196.6k
Turn: i 9.9k o 552 t 453 cache 186.8k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 0.9s
Time: overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Turn: i 9.9k o 552 t 453 cache 186.8k; p≈2.2ktok/8.8kch
Ctx: est 52.2k/200.0k; warn 160.0k reload 190.0k; provider 196.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.4s
Time: model 5.0s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 29t)
Turn: i 9.9k o 552 t 453 cache 186.8k; p≈2.2ktok/8.8kch
Ctx: est 52.2k/200.0k; warn 160.0k reload 190.0k; provider 196.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 11.8s
Time: model 10.5s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Turn: i 9.9k o 552 t 453 cache 186.8k; p≈2.2ktok/8.8kch
Ctx: est 54.4k/200.0k; warn 160.0k reload 190.0k; provider 196.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.3s
Time: model 15.9s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Turn: i 9.9k o 552 t 453 cache 186.8k; p≈2.2ktok/8.8kch
Ctx: est 54.4k/200.0k; warn 160.0k reload 190.0k; provider 196.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 22.8s
Time: model 21.4s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Turn: i 9.9k o 552 t 453 cache 186.8k; p≈2.2ktok/8.8kch
Ctx: est 54.7k/200.0k; warn 160.0k reload 190.0k; provider 196.6k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 26.0s
Time: model 24.6s, overhead 0.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Turn: i 11.5k o 551 t 582 cache 154.5k; p≈2.2ktok/8.8kch
Ctx: est 54.9k/200.0k; warn 160.0k reload 190.0k; provider 166.0k


Great research! Here's the budget-friendly picture:

**Free tier: OpenRouter's Owl Alpha** — completely free, 1.05M context, native tool calling, compatible with OpenClaw/OpenCode. 295B MoE model (21B activated). The catch: prompts may be logged by the provider for model improvement. But for testing and prototyping, it's a no-brainer. OpenRouter also has a `openrouter/free` router that randomly selects from free models including Hunter Alpha, DeepSeek V4 Flash, and several cloaked models.

**Cheapest paid options (per 1M tokens):**

| Model | Input | Output | Context | Via |
|-------|-------|--------|---------|-----|
| GPT-5 Nano | $0.05 | $0.40 | 128K | OpenAI |
| Mistral Small 3.2 | $0.06 | $0.18 | 128K | Mistral |
| **qwen3.5-flash** | **$0.065** | **$0.26** | **1M** | **OpenRouter** |
| Gemini Flash-Lite | $0.10 | $0.40 | 1M | Google |
| DeepSeek V4 Flash | $0.17 | $0.30 | 1M | DeepSeek |
| DeepSeek V3.2 | $0.28 | $0.42 | 128K | DeepSeek |

**Best value plays:**
- **qwen3.5-flash via OpenRouter** ($0.065/$0.26, 1M context) — this is the standout. 35% cheaper than direct Alibaba pricing, huge context, fast.
- **DeepSeek V4 Flash** — free on OpenRouter, or $0.17/$0.30 direct. MoE with 1M context. Best quality-to-cost ratio in the market.
- **Owl Alpha** — completely free. If it works well for agentic stuff, that's literally $0.

**Privacy notes:**
- OpenRouter has ZDR (Zero Data Retention) enforcement per model group — you can restrict to providers that don't store data.
- inference.net / Together AI / Fireworks host open-weight models at rock-bottom prices and don't train on your data.
- The free models on OpenRouter do log prompts (it's the tradeoff for free inference).

Want me to set up a quick test with Owl Alpha or qwen3.5-flash to see how they handle our prompts?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 26.5s
Time: model 24.6s, overhead 1.9s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Turn: i 11.5k o 551 t 582 cache 154.5k; p≈2.2ktok/8.8kch
Ctx: est 54.9k/200.0k; warn 160.0k reload 190.0k; provider 166.0k


The problem is that there's too much private information here, also by design. At some point I won't be comfortable using subscriptions anymore.
What do I select in openrouter to make it more privacy friendly considering our conversations?
What other providers should I try?
Also we need at least 200k context until we trim the prompts even more


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Ctx: est 54.9k/200.0k; warn 160.0k reload 190.0k; provider 166.0k
Turn: i 11.5k o 551 t 582 cache 154.5k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Ctx: est 54.9k/200.0k; warn 160.0k reload 190.0k; provider 166.0k
Turn: i 11.5k o 551 t 582 cache 154.5k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Ctx: est 54.9k/200.0k; warn 160.0k reload 190.0k; provider 166.0k
Turn: i 11.5k o 551 t 582 cache 154.5k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 1.1s
Time: overhead 1.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Turn: i 11.5k o 551 t 582 cache 154.5k; p≈2.3ktok/9.3kch
Ctx: est 54.9k/200.0k; warn 160.0k reload 190.0k; provider 166.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.7s
Time: model 5.0s, overhead 1.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 30t)
Turn: i 11.5k o 551 t 582 cache 154.5k; p≈2.3ktok/9.3kch
Ctx: est 54.9k/200.0k; warn 160.0k reload 190.0k; provider 166.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 12.2s
Time: model 10.5s, overhead 1.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Turn: i 11.5k o 551 t 582 cache 154.5k; p≈2.3ktok/9.3kch
Ctx: est 57.2k/200.0k; warn 160.0k reload 190.0k; provider 166.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.7s
Time: model 16.0s, overhead 1.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Turn: i 11.5k o 551 t 582 cache 154.5k; p≈2.3ktok/9.3kch
Ctx: est 57.2k/200.0k; warn 160.0k reload 190.0k; provider 166.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 23.2s
Time: model 21.5s, overhead 1.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Turn: i 11.5k o 551 t 582 cache 154.5k; p≈2.3ktok/9.3kch
Ctx: est 57.3k/200.0k; warn 160.0k reload 190.0k; provider 166.0k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 28.7s
Time: model 27.0s, overhead 1.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Turn: i 11.5k o 551 t 582 cache 154.5k; p≈2.3ktok/9.3kch
Ctx: est 57.8k/200.0k; warn 160.0k reload 190.0k; provider 166.0k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 30.5s
Time: model 28.8s, overhead 1.1s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Turn: i 11.7k o 677 t 533 cache 169.9k; p≈2.3ktok/9.3kch
Ctx: est 57.8k/200.0k; warn 160.0k reload 190.0k; provider 181.6k


You're right to be cautious — there's a lot of private context flowing through these sessions. Here's what I'd recommend:

**OpenRouter privacy settings to enable:**
1. **ZDR enforcement** — in your account Privacy Settings, toggle on ZDR for "Non-frontier" at minimum. This restricts routing to providers with zero data retention. You can also do it per-request with `zdr: true`
2. **Opt out of training** — separate toggle for paid/free models, prevents routing to providers that train on your data
3. **Disable prompt logging** — off by default, but verify in your settings that "Private Input & Output Logging" and "OpenRouter Use of Inputs/Outputs" are both disabled
4. **Important caveat**: ZDR through OpenRouter depends on the downstream provider. Calling a ZDR provider directly removes OpenRouter as an extra hop. For the privacy-sensitive stuff, direct is cleaner.

**Providers with ≥200k context + strong privacy:**

| Provider | Model | Context | Price (in/out per 1M) | Privacy |
|----------|-------|---------|----------------------|---------|
| OpenRouter | **DeepSeek V4 Flash** (free) | 1M | $0 | ZDR endpoints available |
| OpenRouter | **qwen3.5-flash** | 1M | $0.065/$0.26 | ZDR via inference.net |
| inference.net | DeepSeek V3.2 | 128K | $0.14/$0.28 | No training, zero retention |
| Together AI | Llama/Mistral | 128K | $0.10-$0.18 | No training on data |
| Privatemode | gpt-oss-120b | 128K | Free tier available | E2EE, BSI C5 certified |

**Self-hosting (best privacy):**
- **Qwen3-Next** — 80B params, 3B active, **262K context**, Apache 2.0 license. Runs on consumer GPUs (~16GB VRAM at 4-bit). This is probably the best realistic self-host option for ≥200k context.
- **gpt-oss-20b** — OpenAI's open model, 21B params, runs in 16GB VRAM via Ollama. Only 32K context though.
- **GLM-5** — 744B MoE (40B active), **200K context**, MIT license. Needs serious hardware (2x Mac Studio or multi-GPU), but the most capable open model at this context length.

**My take:** For testing right now, **DeepSeek V4 Flash (free)** or **qwen3.5-flash via OpenRouter** with ZDR enabled gives you the best balance — cheap, 1M context, and reasonable privacy with the right settings. For the longer term where you're not comfortable with subscriptions anymore, **Qwen3-Next** self-hosted on a local GPU gives you 262K context with zero data leaving your machine. Want me to set up a test run with one of these?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 30.9s
Time: model 28.8s, overhead 2.2s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Turn: i 11.7k o 677 t 533 cache 169.9k; p≈2.3ktok/9.3kch
Ctx: est 57.8k/200.0k; warn 160.0k reload 190.0k; provider 181.6k


Hmm we should try deepseek flash soon. It was very terse in our subagent tests.
Qwen-next also sounds interesting, my existing GPU is 12gb though and I'm not getting more anytime soon.
Look for a couple of other private API providers


⚪ Received
Stage: queued for agent
Model: kimi-for-coding/k2p6
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Ctx: est 57.8k/200.0k; warn 160.0k reload 190.0k; provider 181.6k
Turn: i 11.7k o 677 t 533 cache 169.9k


* ⚪ Queued
Stage: waiting for conversation turn
Model: kimi-for-coding/k2p6
Elapsed: 0.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Ctx: est 57.8k/200.0k; warn 160.0k reload 190.0k; provider 181.6k
Turn: i 11.7k o 677 t 533 cache 169.9k


* 🟡 Working
Stage: building prompt
Model: kimi-for-coding/k2p6
Elapsed: 0.6s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Ctx: est 57.8k/200.0k; warn 160.0k reload 190.0k; provider 181.6k
Turn: i 11.7k o 677 t 533 cache 169.9k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 1.0s
Time: overhead 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Turn: i 11.7k o 677 t 533 cache 169.9k; p≈2.3ktok/9.3kch
Ctx: est 57.8k/200.0k; warn 160.0k reload 190.0k; provider 181.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 6.5s
Time: model 5.0s, overhead 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 31t)
Turn: i 11.7k o 677 t 533 cache 169.9k; p≈2.3ktok/9.3kch
Ctx: est 57.8k/200.0k; warn 160.0k reload 190.0k; provider 181.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 12.0s
Time: model 10.5s, overhead 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 32t)
Turn: i 11.7k o 677 t 533 cache 169.9k; p≈2.3ktok/9.3kch
Ctx: est 60.1k/200.0k; warn 160.0k reload 190.0k; provider 181.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 17.5s
Time: model 16.0s, overhead 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 32t)
Turn: i 11.7k o 677 t 533 cache 169.9k; p≈2.3ktok/9.3kch
Ctx: est 60.1k/200.0k; warn 160.0k reload 190.0k; provider 181.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 23.0s
Time: model 21.4s, overhead 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 32t)
Turn: i 11.7k o 677 t 533 cache 169.9k; p≈2.3ktok/9.3kch
Ctx: est 60.1k/200.0k; warn 160.0k reload 190.0k; provider 181.6k


* 🟡 Working
Stage: model running
Model: kimi-for-coding/k2p6
Elapsed: 28.4s
Time: model 26.9s, overhead 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 32t)
Turn: i 11.7k o 677 t 533 cache 169.9k; p≈2.3ktok/9.3kch
Ctx: est 60.6k/200.0k; warn 160.0k reload 190.0k; provider 181.6k


* 🟡 Processing result
Stage: model returned
Model: kimi-for-coding/k2p6
Elapsed: 30.3s
Time: model 28.8s, overhead 1.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 32t)
Turn: i 7.3k o 618 t 570 cache 185.7k; p≈2.3ktok/9.3kch
Ctx: est 60.6k/200.0k; warn 160.0k reload 190.0k; provider 193.0k


Good new finds! Here are the most relevant ones:

**New private API providers (privacy-first, affordable):**

| Provider | Privacy | Models | Context | Price (in/out per 1M) |
|----------|---------|--------|---------|----------------------|
| **Answira** 🇨🇿 | EU (Czech), no storage, no training | qwen3-coder-next | **256K** | **$0.07/$0.30** |
| **Tensorix** 🇪🇺 | EU (Amsterdam/Frankfurt), zero retention | Kimi-K2.6, GLM-5.1 | 262K / 203K | $1.00/$4.00 |
| **Together AI** 🇺🇸 | ZDR by default, opt-in training | DeepSeek, Qwen, Llama | 128K-1M | $0.10-$0.50 |
| **Fireworks AI** 🇺🇸 | ZDR for open models, SOC 2, HIPAA | Llama, DeepSeek, Qwen | 128K | ~$0.10-$0.20 |
| **Regolo.ai** 🇪🇺 | EU, zero retention, GDPR | Various open models | 128K+ | Pay-as-you-go |
| **LLMBase** 🇩🇪 | German company, EU servers, no training | Open-source models | 128K-256K | Pay-per-use |

**Standouts for your needs:**
- **Answira** — Czech Republic, qwen3-coder-next at **$0.07/$0.30** with **256K context**, zero storage, no training. That's Qwen's coding model at absurdly low price with EU privacy.
- **Together AI** — DeepSeek models hosted on their own US infrastructure. **Zero data retention by default.** The model authors (DeepSeek, Qwen) never see your requests. They explicitly say "DeepSeek itself receives no user requests or API traffic."
- **Fireworks AI** — similar to Together, SOC 2 Type II certified, HIPAA compliant if that ever matters.

**About your 12GB GPU:** Unfortunately Qwen3-Next (80B) won't fit — even at 4-bit it needs ~40GB. gpt-oss-20b at 4-bit would be ~10.5GB which might barely squeeze in with CPU offloading. For truly local 200K+ context on 12GB, nothing realistic exists yet — you'd need to use API-based models. DeepSeek V4 Flash or qwen3.5-flash via one of the ZDR providers is your best bet for now.

Want me to look into setting up a test with DeepSeek Flash or the Answira qwen3-coder endpoint?


* 🟢 Done
Stage: final reply sent
Model: kimi-for-coding/k2p6
Elapsed: 30.8s
Time: model 28.8s, overhead 2.0s
Backend: ses_1bf0bdb40ffeAFrAzQZD1eauNw (since 05-19 17:56 CEST, 32t)
Turn: i 7.3k o 618 t 570 cache 185.7k; p≈2.3ktok/9.3kch
Ctx: est 60.6k/200.0k; warn 160.0k reload 190.0k; provider 193.0k


I like your standout, please compare the pricing, say, on deepseek v4 pro