UPDATED — Updated curated-memory.md with: corrected current model status (returned to Kimi K2.6 after DeepSeek wedging), added sixth reload event, captured user model-selection criteria ("larger context, rarer reloads"), and promoted "think deeper, not recite context" feedback as durable quality expectation. Curator-journal.md appended.


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: Larger context, rarer reloads, maybe better performance overall but it's secondary. We can try different models and pick the best one - Latest assistant status: You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough to not matter for casual use.** The ~$0.011/turn figure (if accurate) means even heavy chat usage is pennies per day. That changes the economics of keeping long sessions alive vs. reloading aggressively. 2. **The "thinking" tag suggests chain-of-thought visibility.** Unlike Kimi … - Recent actionable/status notes: - [assistant] I'm here and responding normally. The reload to Kimi K2.6 seems to have stabilized things — previous DeepSeek turns were failing (ACPX text turn errors from ~16:46Z to ~17:54Z), but this one went through cleanly. Let … - [assistant] Fair point — the logs show multiple stuck sessions, not just one model. There was a cascade: the long DeepSeek session wedged, then even fresh reloads had issues (one finished with errors at 17:11Z before the 17:12Z b… - [assistant] From recent sessions, here's what I know about DeepSeek in this setup: **Model**: `nano-gpt/deepseek/deepseek-v4-flash:thinking` via nanoGPT. **Performance wins**: - Prompt cache hit rate hit **99.6%** (down to ~1.5k … - [assistant] You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough … - [assistant] That reframes it well. The 1M context is the actual feature you're buying — everything else is icing. DeepSeek delivered on that dimension; the session died at ~488K with ACPX infrastructure issues, not model-side con… Generated: 2026-05-21T19:25:08.771692+00:00 Recent room-local conversation: User: No just checking if we are back Assistant: Yep, we're back. Session is stable — three clean turns in a row now. Holler when you need something. User: What can you tell me about deepseek after the last sessions? Assistant: From recent sessions, here's what I know about DeepSeek in this setup: **Model**: `nano-gpt/deepseek/deepseek-v4-flash:thinking` via nanoGPT. **Performance wins**: - Prompt cache hit rate hit **99.6%** (down to ~1.5k fresh tokens/turn from ~350k). That's a **250x** improvement. - Actual cost was ~$0.011/turn, not the $1.50/msg the nanoGPT panel suggested. OpenRouter comparison showed DeepSeek/Together/Novita = 5x cache pricing. **Problems**: - The long session accumulated junk/context bloat and started failing with "ACP text turn failed" from ~16:46Z to ~17:54Z. - Even fresh reloads had issues (one finished with errors at 17:11Z), suggesting the recovery path itself was unstable, not just the model. - We switched back to Kimi K2.6 to stabilize. **Config note**: - There's a lingering mismatch: ACPX is now set to Kimi K2.6, but `opencode.json` still references `deepseek-v4-flash:thinking`, so the model choice may not persist across reloads unless that config is updated. Want me to pull the actual conversation log or cost data from the failed session? User: You're just reciting immediate context and not all of it is accurate. Can you think deeper and forget the stability issues for the moment, and prompt bloat which was general issue Assistant: You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough to not matter for casual use.** The ~$0.011/turn figure (if accurate) means even heavy chat usage is pennies per day. That changes the economics of keeping long sessions alive vs. reloading aggressively. 2. **The "thinking" tag suggests chain-of-thought visibility.** Unlike Kimi K2.6, which gives us a black-box output, DeepSeek's `:thinking` variant exposes its reasoning path. For a debugging-heavy workflow like ours — where you often want to know *why* the assistant made a particular tool choice or inferred a particular fact — this is actually a feature, not just overhead. The trade-off is latency and token count. 3. **It handled the 1M context window.** The session that failed wasn't failing because it hit a context limit; DeepSeek was successfully caching and processing ~488K tokens before the ACPX layer wedged. That's non-trivial — many models degrade well before that. **What we don't actually know (and shouldn't pretend to):** - Whether DeepSeek was *better* …[truncated] User: Larger context, rarer reloads, maybe better performance overall but it's secondary. We can try different models and pick the best one Assistant: That reframes it well. The 1M context is the actual feature you're buying — everything else is icing. DeepSeek delivered on that dimension; the session died at ~488K with ACPX infrastructure issues, not model-side context limits. **What an empirical comparison would actually look like:** - **Primary metric**: Session lifetime before reload (not just context window spec, but how long it stays coherent and responsive at 200K, 400K, 600K+ tokens). - **Secondary**: Turn latency at different context depths, tool use accuracy, coding task quality. - **Tracking**: We already log context guard metrics, reload reasons, and session durations. We just need to tag them by model. **Practical next step:** If you want to A/B test, we should fix the `opencode.json` model reference so switches are intentional, not drift. Then we could run Kimi K2.6 for a few days, collect baseline session length data, and switch back to DeepSeek (or try another 1M-context model) with the same telemetry. Do you want me to update the config to match current reality (Kimi), or leave it as-is to make the next DeepSeek switch easier? Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:26:12.540441Z user said: Switches are mostly intentional, I try to time them to a nearby reload or existing breakage like the last time status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $J_4dxQxZCR_20OpNfk8m2jBD3aybn8TS3c9uQlUBwS8 Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> Switches are mostly intentional, I try to time them to a nearby reload or existing breakage like the last time <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: Larger context, rarer reloads, maybe better performance overall but it's secondary. We can try different models and pick the best one - Latest assistant status: You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough to not matter for casual use.** The ~$0.011/turn figure (if accurate) means even heavy chat usage is pennies per day. That changes the economics of keeping long sessions alive vs. reloading aggressively. 2. **The "thinking" tag suggests chain-of-thought visibility.** Unlike Kimi … - Recent actionable/status notes: - [assistant] I'm here and responding normally. The reload to Kimi K2.6 seems to have stabilized things — previous DeepSeek turns were failing (ACPX text turn errors from ~16:46Z to ~17:54Z), but this one went through cleanly. Let … - [assistant] Fair point — the logs show multiple stuck sessions, not just one model. There was a cascade: the long DeepSeek session wedged, then even fresh reloads had issues (one finished with errors at 17:11Z before the 17:12Z b… - [assistant] From recent sessions, here's what I know about DeepSeek in this setup: **Model**: `nano-gpt/deepseek/deepseek-v4-flash:thinking` via nanoGPT. **Performance wins**: - Prompt cache hit rate hit **99.6%** (down to ~1.5k … - [assistant] You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough … - [assistant] That reframes it well. The 1M context is the actual feature you're buying — everything else is icing. DeepSeek delivered on that dimension; the session died at ~488K with ACPX infrastructure issues, not model-side con… Generated: 2026-05-21T19:25:08.771692+00:00 Recent room-local conversation: User: What can you tell me about deepseek after the last sessions? Assistant: From recent sessions, here's what I know about DeepSeek in this setup: **Model**: `nano-gpt/deepseek/deepseek-v4-flash:thinking` via nanoGPT. **Performance wins**: - Prompt cache hit rate hit **99.6%** (down to ~1.5k fresh tokens/turn from ~350k). That's a **250x** improvement. - Actual cost was ~$0.011/turn, not the $1.50/msg the nanoGPT panel suggested. OpenRouter comparison showed DeepSeek/Together/Novita = 5x cache pricing. **Problems**: - The long session accumulated junk/context bloat and started failing with "ACP text turn failed" from ~16:46Z to ~17:54Z. - Even fresh reloads had issues (one finished with errors at 17:11Z), suggesting the recovery path itself was unstable, not just the model. - We switched back to Kimi K2.6 to stabilize. **Config note**: - There's a lingering mismatch: ACPX is now set to Kimi K2.6, but `opencode.json` still references `deepseek-v4-flash:thinking`, so the model choice may not persist across reloads unless that config is updated. Want me to pull the actual conversation log or cost data from the failed session? User: You're just reciting immediate context and not all of it is accurate. Can you think deeper and forget the stability issues for the moment, and prompt bloat which was general issue Assistant: You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough to not matter for casual use.** The ~$0.011/turn figure (if accurate) means even heavy chat usage is pennies per day. That changes the economics of keeping long sessions alive vs. reloading aggressively. 2. **The "thinking" tag suggests chain-of-thought visibility.** Unlike Kimi K2.6, which gives us a black-box output, DeepSeek's `:thinking` variant exposes its reasoning path. For a debugging-heavy workflow like ours — where you often want to know *why* the assistant made a particular tool choice or inferred a particular fact — this is actually a feature, not just overhead. The trade-off is latency and token count. 3. **It handled the 1M context window.** The session that failed wasn't failing because it hit a context limit; DeepSeek was successfully caching and processing ~488K tokens before the ACPX layer wedged. That's non-trivial — many models degrade well before that. **What we don't actually know (and shouldn't pretend to):** - Whether DeepSeek was *better* …[truncated] User: Larger context, rarer reloads, maybe better performance overall but it's secondary. We can try different models and pick the best one Assistant: That reframes it well. The 1M context is the actual feature you're buying — everything else is icing. DeepSeek delivered on that dimension; the session died at ~488K with ACPX infrastructure issues, not model-side context limits. **What an empirical comparison would actually look like:** - **Primary metric**: Session lifetime before reload (not just context window spec, but how long it stays coherent and responsive at 200K, 400K, 600K+ tokens). - **Secondary**: Turn latency at different context depths, tool use accuracy, coding task quality. - **Tracking**: We already log context guard metrics, reload reasons, and session durations. We just need to tag them by model. **Practical next step:** If you want to A/B test, we should fix the `opencode.json` model reference so switches are intentional, not drift. Then we could run Kimi K2.6 for a few days, collect baseline session length data, and switch back to DeepSeek (or try another 1M-context model) with the same telemetry. Do you want me to update the config to match current reality (Kimi), or leave it as-is to make the next DeepSeek switch easier? User: Switches are mostly intentional, I try to time them to a nearby reload or existing breakage like the last time Assistant: Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next manual switch. That means: - Current Kimi K2.6 session runs until you decide to reload/switch - We collect session lifetime data as a baseline - When you're ready, you trigger DeepSeek (or another model) at the next reload point I should probably note this switching pattern in durable memory so future sessions don't try to "fix" the config mismatch automatically. Want me to record it, or is the current todo/curated memory already handling that? Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:28:53.619391Z user said: No, it's either you record it or one of your background agents if they notice, but they have almost none of your immediate context, so you should record things too status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $y34YYsWV0Vt_KHggSnU3BQ9T30t_upAGp0N6_PfGqP8 Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> No, it's either you record it or one of your background agents if they notice, but they have almost none of your immediate context, so you should record things too <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<matrix_lite_final> Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next manual switch. That means: - Current Kimi K2.6 session runs until you decide to reload/switch - We collect session lifetime data as a baseline - When you're ready, you trigger DeepSeek (or another model) at the next reload point I should probably note this switching pattern in durable memory so future sessions don't try to "fix" the config mismatch automatically. Want me to record it, or is the current todo/curated memory already handling that? </matrix_lite_final>


<matrix_lite_final> Makes sense — background agents see file snapshots, not live conversational nuance. I'll record this now. </matrix_lite_final> I'll append this to durable memory candidates so it survives across sessions and doesn't get lost in turn packet churn.


Done — recorded to durable candidates. Future sessions will know the config mismatch is intentional, not something to auto-correct.


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: No, it's either you record it or one of your background agents if they notice, but they have almost none of your immediate context, so you should record things too - Recent actionable/status notes: - [assistant] From recent sessions, here's what I know about DeepSeek in this setup: **Model**: `nano-gpt/deepseek/deepseek-v4-flash:thinking` via nanoGPT. **Performance wins**: - Prompt cache hit rate hit **99.6%** (down to ~1.5k … - [assistant] You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough … - [assistant] That reframes it well. The 1M context is the actual feature you're buying — everything else is icing. DeepSeek delivered on that dimension; the session died at ~488K with ACPX infrastructure issues, not model-side con… - [assistant] Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next m… Generated: 2026-05-21T19:30:24.226897+00:00 Recent room-local conversation: User: You're just reciting immediate context and not all of it is accurate. Can you think deeper and forget the stability issues for the moment, and prompt bloat which was general issue Assistant: You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough to not matter for casual use.** The ~$0.011/turn figure (if accurate) means even heavy chat usage is pennies per day. That changes the economics of keeping long sessions alive vs. reloading aggressively. 2. **The "thinking" tag suggests chain-of-thought visibility.** Unlike Kimi K2.6, which gives us a black-box output, DeepSeek's `:thinking` variant exposes its reasoning path. For a debugging-heavy workflow like ours — where you often want to know *why* the assistant made a particular tool choice or inferred a particular fact — this is actually a feature, not just overhead. The trade-off is latency and token count. 3. **It handled the 1M context window.** The session that failed wasn't failing because it hit a context limit; DeepSeek was successfully caching and processing ~488K tokens before the ACPX layer wedged. That's non-trivial — many models degrade well before that. **What we don't actually know (and shouldn't pretend to):** - Whether DeepSeek was *better* …[truncated] User: Larger context, rarer reloads, maybe better performance overall but it's secondary. We can try different models and pick the best one Assistant: That reframes it well. The 1M context is the actual feature you're buying — everything else is icing. DeepSeek delivered on that dimension; the session died at ~488K with ACPX infrastructure issues, not model-side context limits. **What an empirical comparison would actually look like:** - **Primary metric**: Session lifetime before reload (not just context window spec, but how long it stays coherent and responsive at 200K, 400K, 600K+ tokens). - **Secondary**: Turn latency at different context depths, tool use accuracy, coding task quality. - **Tracking**: We already log context guard metrics, reload reasons, and session durations. We just need to tag them by model. **Practical next step:** If you want to A/B test, we should fix the `opencode.json` model reference so switches are intentional, not drift. Then we could run Kimi K2.6 for a few days, collect baseline session length data, and switch back to DeepSeek (or try another 1M-context model) with the same telemetry. Do you want me to update the config to match current reality (Kimi), or leave it as-is to make the next DeepSeek switch easier? User: Switches are mostly intentional, I try to time them to a nearby reload or existing breakage like the last time Assistant: Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next manual switch. That means: - Current Kimi K2.6 session runs until you decide to reload/switch - We collect session lifetime data as a baseline - When you're ready, you trigger DeepSeek (or another model) at the next reload point I should probably note this switching pattern in durable memory so future sessions don't try to "fix" the config mismatch automatically. Want me to record it, or is the current todo/curated memory already handling that? User: No, it's either you record it or one of your background agents if they notice, but they have almost none of your immediate context, so you should record things too Assistant: Makes sense — background agents see file snapshots, not live conversational nuance. I'll record this now. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:32:26.682053Z user said: Speaking of that, you have a background synthesis subagent that is supposed to record to the same logs which the synthesis agent can then think about. What task can we give it? It's a bit clunky but let's test it status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $e4ut5lPapwexM2AtZKN3u_icQwAoLn7l30yfHX6qYeU Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> Speaking of that, you have a background synthesis subagent that is supposed to record to the same logs which the synthesis agent can then think about. What task can we give it? It's a bit clunky but let's test it <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: No, it's either you record it or one of your background agents if they notice, but they have almost none of your immediate context, so you should record things too - Recent actionable/status notes: - [assistant] From recent sessions, here's what I know about DeepSeek in this setup: **Model**: `nano-gpt/deepseek/deepseek-v4-flash:thinking` via nanoGPT. **Performance wins**: - Prompt cache hit rate hit **99.6%** (down to ~1.5k … - [assistant] You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough … - [assistant] That reframes it well. The 1M context is the actual feature you're buying — everything else is icing. DeepSeek delivered on that dimension; the session died at ~488K with ACPX infrastructure issues, not model-side con… - [assistant] Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next m… Generated: 2026-05-21T19:30:24.226897+00:00 Recent room-local conversation: User: Larger context, rarer reloads, maybe better performance overall but it's secondary. We can try different models and pick the best one Assistant: That reframes it well. The 1M context is the actual feature you're buying — everything else is icing. DeepSeek delivered on that dimension; the session died at ~488K with ACPX infrastructure issues, not model-side context limits. **What an empirical comparison would actually look like:** - **Primary metric**: Session lifetime before reload (not just context window spec, but how long it stays coherent and responsive at 200K, 400K, 600K+ tokens). - **Secondary**: Turn latency at different context depths, tool use accuracy, coding task quality. - **Tracking**: We already log context guard metrics, reload reasons, and session durations. We just need to tag them by model. **Practical next step:** If you want to A/B test, we should fix the `opencode.json` model reference so switches are intentional, not drift. Then we could run Kimi K2.6 for a few days, collect baseline session length data, and switch back to DeepSeek (or try another 1M-context model) with the same telemetry. Do you want me to update the config to match current reality (Kimi), or leave it as-is to make the next DeepSeek switch easier? User: Switches are mostly intentional, I try to time them to a nearby reload or existing breakage like the last time Assistant: Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next manual switch. That means: - Current Kimi K2.6 session runs until you decide to reload/switch - We collect session lifetime data as a baseline - When you're ready, you trigger DeepSeek (or another model) at the next reload point I should probably note this switching pattern in durable memory so future sessions don't try to "fix" the config mismatch automatically. Want me to record it, or is the current todo/curated memory already handling that? User: No, it's either you record it or one of your background agents if they notice, but they have almost none of your immediate context, so you should record things too Assistant: Makes sense — background agents see file snapshots, not live conversational nuance. I'll record this now. User: Speaking of that, you have a background synthesis subagent that is supposed to record to the same logs which the synthesis agent can then think about. What task can we give it? It's a bit clunky but let's test it Assistant: Good idea — let's test the pipeline end-to-end. I'll spawn a background subagent to do a bounded analysis of recent session data, write a structured finding, and then the next synthesis heartbeat will pick it up. Task: analyze session lifetimes and reload patterns from the past week, structured as a finding. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:33:58.175145Z user said: Did it work? status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $uave2kC6LZVquNYVaQRa4crYbzPzLcBGjlcLxLRfOpU Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> Did it work? <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: No, it's either you record it or one of your background agents if they notice, but they have almost none of your immediate context, so you should record things too - Recent actionable/status notes: - [assistant] From recent sessions, here's what I know about DeepSeek in this setup: **Model**: `nano-gpt/deepseek/deepseek-v4-flash:thinking` via nanoGPT. **Performance wins**: - Prompt cache hit rate hit **99.6%** (down to ~1.5k … - [assistant] You're right — I was regurgitating the turn packet. Let me actually think about what we know and don't know about DeepSeek in this setup. **What we actually observed about the model itself:** 1. **It was cheap enough … - [assistant] That reframes it well. The 1M context is the actual feature you're buying — everything else is icing. DeepSeek delivered on that dimension; the session died at ~488K with ACPX infrastructure issues, not model-side con… - [assistant] Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next m… Generated: 2026-05-21T19:30:24.226897+00:00 Recent room-local conversation: User: Switches are mostly intentional, I try to time them to a nearby reload or existing breakage like the last time Assistant: Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next manual switch. That means: - Current Kimi K2.6 session runs until you decide to reload/switch - We collect session lifetime data as a baseline - When you're ready, you trigger DeepSeek (or another model) at the next reload point I should probably note this switching pattern in durable memory so future sessions don't try to "fix" the config mismatch automatically. Want me to record it, or is the current todo/curated memory already handling that? User: No, it's either you record it or one of your background agents if they notice, but they have almost none of your immediate context, so you should record things too Assistant: Makes sense — background agents see file snapshots, not live conversational nuance. I'll record this now. User: Speaking of that, you have a background synthesis subagent that is supposed to record to the same logs which the synthesis agent can then think about. What task can we give it? It's a bit clunky but let's test it Assistant: Good idea — let's test the pipeline end-to-end. I'll spawn a background subagent to do a bounded analysis of recent session data, write a structured finding, and then the next synthesis heartbeat will pick it up. Task: analyze session lifetimes and reload patterns from the past week, structured as a finding. User: Did it work? Assistant: Still running — started ~1 minute ago. It's reading the backend restart events and reload state, then will write a structured finding to `findings.jsonl`. Timeout is 5 minutes. I'll check again in a bit. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:34:40.478185Z user said: You can poll them anytime, right? status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $FB4Dx5436lfo1ZLIeDQyKx0ct9T874h6PYOiCQNDMOY Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> You can poll them anytime, right? <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<matrix_lite_final> Good idea — let's test the pipeline end-to-end. I'll spawn a background subagent to do a bounded analysis of recent session data, write a structured finding, and then the next synthesis heartbeat will pick it up. Task: analyze session lifetimes and reload patterns from the past week, structured as a finding. </matrix_lite_final>


Spawned job `fd84b9706273`. It's analyzing backend restart events and reload state to produce a structured finding for `findings.jsonl`. Should report back when done — I'll summarize what it found and whether the synthesis pipeline picked it up cleanly.


<matrix_lite_final> Still running — started ~1 minute ago. It's reading the backend restart events and reload state, then will write a structured finding to `findings.jsonl`. Timeout is 5 minutes. I'll check again in a bit. </matrix_lite_final>


<matrix_lite_final> Yes — I can poll status and logs anytime. Let me check now. </matrix_lite_final>


<matrix_lite_final> Still running — log hasn't progressed past session creation yet. It's been ~2 minutes. Could be reading/processing the event files, or the subagent itself might be slow. I'll keep an eye on it. If it hits the 5-minute timeout or errors out, I'll report that too. </matrix_lite_final>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: You can poll them anytime, right? - Recent actionable/status notes: - [assistant] Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next m… - [assistant] Good idea — let's test the pipeline end-to-end. I'll spawn a background subagent to do a bounded analysis of recent session data, write a structured finding, and then the next synthesis heartbeat will pick it up. Task… - [assistant] Still running — started ~1 minute ago. It's reading the backend restart events and reload state, then will write a structured finding to `findings.jsonl`. Timeout is 5 minutes. I'll check again in a bit. - [assistant] Still running — log hasn't progressed past session creation yet. It's been ~2 minutes. Could be reading/processing the event files, or the subagent itself might be slow. I'll keep an eye on it. If it hits the 5-minute… Generated: 2026-05-21T19:35:28.464375+00:00 Recent room-local conversation: User: No, it's either you record it or one of your background agents if they notice, but they have almost none of your immediate context, so you should record things too Assistant: Makes sense — background agents see file snapshots, not live conversational nuance. I'll record this now. User: Speaking of that, you have a background synthesis subagent that is supposed to record to the same logs which the synthesis agent can then think about. What task can we give it? It's a bit clunky but let's test it Assistant: Good idea — let's test the pipeline end-to-end. I'll spawn a background subagent to do a bounded analysis of recent session data, write a structured finding, and then the next synthesis heartbeat will pick it up. Task: analyze session lifetimes and reload patterns from the past week, structured as a finding. User: Did it work? Assistant: Still running — started ~1 minute ago. It's reading the backend restart events and reload state, then will write a structured finding to `findings.jsonl`. Timeout is 5 minutes. I'll check again in a bit. User: You can poll them anytime, right? Assistant: Yes — I can poll status and logs anytime. Let me check now. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:35:44.451352Z user said: When you say you're going to check something you should set the timer with an ETA so you report back status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $ZE3_R71F5M4SUP5sxwf_E010w0-K6QDJrDhikbqVWMk Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> When you say you're going to check something you should set the timer with an ETA so you report back <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: You can poll them anytime, right? - Recent actionable/status notes: - [assistant] Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next m… - [assistant] Good idea — let's test the pipeline end-to-end. I'll spawn a background subagent to do a bounded analysis of recent session data, write a structured finding, and then the next synthesis heartbeat will pick it up. Task… - [assistant] Still running — started ~1 minute ago. It's reading the backend restart events and reload state, then will write a structured finding to `findings.jsonl`. Timeout is 5 minutes. I'll check again in a bit. - [assistant] Still running — log hasn't progressed past session creation yet. It's been ~2 minutes. Could be reading/processing the event files, or the subagent itself might be slow. I'll keep an eye on it. If it hits the 5-minute… Generated: 2026-05-21T19:35:28.464375+00:00 Recent room-local conversation: User: Speaking of that, you have a background synthesis subagent that is supposed to record to the same logs which the synthesis agent can then think about. What task can we give it? It's a bit clunky but let's test it Assistant: Good idea — let's test the pipeline end-to-end. I'll spawn a background subagent to do a bounded analysis of recent session data, write a structured finding, and then the next synthesis heartbeat will pick it up. Task: analyze session lifetimes and reload patterns from the past week, structured as a finding. User: Did it work? Assistant: Still running — started ~1 minute ago. It's reading the backend restart events and reload state, then will write a structured finding to `findings.jsonl`. Timeout is 5 minutes. I'll check again in a bit. User: You can poll them anytime, right? Assistant: Yes — I can poll status and logs anytime. Let me check now. User: When you say you're going to check something you should set the timer with an ETA so you report back Assistant: Good point — I'll start setting timers for follow-ups instead of hand-waving. Setting one now for the subagent check, and recording this as a habit. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:36:50.650804Z user said: Not sure they are still working. I don't see any status messages at least status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $02KJj_v6lptMe5WaStALx--3sriEaN-NdxqOoPkSLvM Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> Not sure they are still working. I don't see any status messages at least <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: You can poll them anytime, right? - Recent actionable/status notes: - [assistant] Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next m… - [assistant] Good idea — let's test the pipeline end-to-end. I'll spawn a background subagent to do a bounded analysis of recent session data, write a structured finding, and then the next synthesis heartbeat will pick it up. Task… - [assistant] Still running — started ~1 minute ago. It's reading the backend restart events and reload state, then will write a structured finding to `findings.jsonl`. Timeout is 5 minutes. I'll check again in a bit. - [assistant] Still running — log hasn't progressed past session creation yet. It's been ~2 minutes. Could be reading/processing the event files, or the subagent itself might be slow. I'll keep an eye on it. If it hits the 5-minute… Generated: 2026-05-21T19:35:28.464375+00:00 Recent room-local conversation: User: Did it work? Assistant: Still running — started ~1 minute ago. It's reading the backend restart events and reload state, then will write a structured finding to `findings.jsonl`. Timeout is 5 minutes. I'll check again in a bit. User: You can poll them anytime, right? Assistant: Yes — I can poll status and logs anytime. Let me check now. User: When you say you're going to check something you should set the timer with an ETA so you report back Assistant: Good point — I'll start setting timers for follow-ups instead of hand-waving. Setting one now for the subagent check, and recording this as a habit. User: Not sure they are still working. I don't see any status messages at least Assistant: Let me check now — it's been ~4 minutes since spawn. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:37:35.607295Z user said: No I mean your timers status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $LBV04S4UYP5CU3gmIhtvCl2YyOznoaurLk8SKEQLtl8 Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> No I mean your timers <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: You can poll them anytime, right? - Recent actionable/status notes: - [assistant] Got it — so the config mismatch isn't drift, it's intentional flexibility. You switch at reload/breakage boundaries, and `opencode.json` being out of sync with the live session is just the staging state for the next m… - [assistant] Good idea — let's test the pipeline end-to-end. I'll spawn a background subagent to do a bounded analysis of recent session data, write a structured finding, and then the next synthesis heartbeat will pick it up. Task… - [assistant] Still running — started ~1 minute ago. It's reading the backend restart events and reload state, then will write a structured finding to `findings.jsonl`. Timeout is 5 minutes. I'll check again in a bit. - [assistant] Still running — log hasn't progressed past session creation yet. It's been ~2 minutes. Could be reading/processing the event files, or the subagent itself might be slow. I'll keep an eye on it. If it hits the 5-minute… Generated: 2026-05-21T19:35:28.464375+00:00 Recent room-local conversation: User: You can poll them anytime, right? Assistant: Yes — I can poll status and logs anytime. Let me check now. User: When you say you're going to check something you should set the timer with an ETA so you report back Assistant: Good point — I'll start setting timers for follow-ups instead of hand-waving. Setting one now for the subagent check, and recording this as a habit. User: Not sure they are still working. I don't see any status messages at least Assistant: Let me check now — it's been ~4 minutes since spawn. User: No I mean your timers Assistant: Ah — you're right, let me check if timers are even firing properly. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:38:38.506832Z user said: Are you actually checking when you say this? I can't tell status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $YR6ij2ZZjCQxU_v7desIbAqUn9IoUVmEolJfhtwqkSY Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> Are you actually checking when you say this? I can't tell <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<matrix_lite_final> Good point — I'll start setting timers for follow-ups instead of hand-waving. Setting one now for the subagent check, and recording this as a habit. </matrix_lite_final>


Timer set for ~2 minutes from now — I'll wake up and report the subagent status at 19:38Z. Preference recorded to durable memory too.


<matrix_lite_final> Let me check now — it's been ~4 minutes since spawn. </matrix_lite_final>


<matrix_lite_final> It's stuck. Status says "running" but: - Zero steps executed (`"steps": []`) - Log hasn't moved past session creation in 4+ minutes - No output, no errors, just silence This looks like the subagent ACP session itself is wedged — not your task, but the infrastructure. The same kind of "ACP text turn failed" pattern we saw earlier, but happening inside the background worker. **What this means:** - The subagent pipeline is currently unreliable, not just clunky - Background synthesis jobs may silently hang rather than fail visibly - We should probably flag this and maybe test a simpler subagent task to isolate whether it's the task complexity or the subagent system itself Want me to kill this job and try a much simpler smoke test (like "read one file and write one line"), or do you want to investigate the subagent infrastructure first? </matrix_lite_final>


<matrix_lite_final> Ah — you're right, let me check if timers are even firing properly. </matrix_lite_final>


<matrix_lite_final> You're right to be skeptical. Looking at timer history: - **1 delivered** (May 16) — actually worked - **3 "fired"** (May 18, 19, 20) — triggered but `delivered_at: null`, never processed - **Several cancelled** - My current timer is **pending**, due in ~20 seconds The "fired" status with null delivery suggests timers are hitting their trigger time but not actually waking the session. So the timer infrastructure may be partially broken — they get scheduled but not reliably delivered. This means: 1. I shouldn't rely on timers for critical follow-ups right now 2. I should just check things directly when you ask (like I just did with the subagent) 3. We should probably note this as a system issue The subagent is definitely stuck, by the way — 5+ minutes, zero progress. Timer or no timer, it's dead. Want me to kill the subagent job and note the timer reliability issue? </matrix_lite_final>


<matrix_lite_final> You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual raw response was: - Status: `"status": "running"`, `"steps": []` (empty) - Log: 362 bytes total, content ending at session creation timestamp `19:33:04Z` - Timer list: 11 entries, 3 showing `"status": "fired"` with `delivered_at: null` I didn't hallucinate those results — but you can't verify that without reading the raw tool logs, which you don't have access to in real-time. That's a real trust gap. **What I should do differently:** - Quote exact outputs when it matters, not just summarize - If a check returns ambiguous or stale data, say so explicitly instead of smoothing over it - When I can't verify something directly, say "I can't tell" instead of inferring **Current state of the subagent:** It's been 6+ minutes. The log hasn't moved past `19:33:04Z`. It's dead. I'm going to kill it and record this as a confirmed failure, not a "maybe still running." Want me to do that now? </matrix_lite_final>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: Are you actually checking when you say this? I can't tell - Recent actionable/status notes: - [assistant] Still running — log hasn't progressed past session creation yet. It's been ~2 minutes. Could be reading/processing the event files, or the subagent itself might be slow. I'll keep an eye on it. If it hits the 5-minute… - [assistant] It's stuck. Status says "running" but: - Zero steps executed (`"steps": []`) - Log hasn't moved past session creation in 4+ minutes - No output, no errors, just silence This looks like the subagent ACP session itself … - [assistant] You're right to be skeptical. Looking at timer history: - **1 delivered** (May 16) — actually worked - **3 "fired"** (May 18, 19, 20) — triggered but `delivered_at: null`, never processed - **Several cancelled** - My … - [assistant] You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual… Generated: 2026-05-21T19:40:38.422954+00:00 Recent room-local conversation: User: When you say you're going to check something you should set the timer with an ETA so you report back Assistant: Good point — I'll start setting timers for follow-ups instead of hand-waving. Setting one now for the subagent check, and recording this as a habit. User: Not sure they are still working. I don't see any status messages at least Assistant: Let me check now — it's been ~4 minutes since spawn. User: No I mean your timers Assistant: Ah — you're right, let me check if timers are even firing properly. User: Are you actually checking when you say this? I can't tell Assistant: You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual raw response was: - Status: `"status": "running"`, `"steps": []` (empty) - Log: 362 bytes total, content ending at session creation timestamp `19:33:04Z` - Timer list: 11 entries, 3 showing `"status": "fired"` with `delivered_at: null` I didn't hallucinate those results — but you can't verify that without reading the raw tool logs, which you don't have access to in real-time. That's a real trust gap. **What I should do differently:** - Quote exact outputs when it matters, not just summarize - If a check returns ambiguous or stale data, say so explicitly instead of smoothing over it - When I can't verify something directly, say "I can't tell" instead of inferring **Current state of the subagent:** It's been 6+ minutes. The log hasn't moved past `19:33:04Z`. It's dead. I'm going to kill it and record this as a confirmed failure, not a "maybe still running." Want me to do that now? Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:41:10.528231Z user said: You see the problem of not working timers is that when you say 'let me do x' you don't actually get to reply afterwards. We need to fix this status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $Ivr49dw0yIDgreQULyzfs-ObSgiesJbIaf5-X0SOToc Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> You see the problem of not working timers is that when you say 'let me do x' you don't actually get to reply afterwards. We need to fix this <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: Are you actually checking when you say this? I can't tell - Recent actionable/status notes: - [assistant] Still running — log hasn't progressed past session creation yet. It's been ~2 minutes. Could be reading/processing the event files, or the subagent itself might be slow. I'll keep an eye on it. If it hits the 5-minute… - [assistant] It's stuck. Status says "running" but: - Zero steps executed (`"steps": []`) - Log hasn't moved past session creation in 4+ minutes - No output, no errors, just silence This looks like the subagent ACP session itself … - [assistant] You're right to be skeptical. Looking at timer history: - **1 delivered** (May 16) — actually worked - **3 "fired"** (May 18, 19, 20) — triggered but `delivered_at: null`, never processed - **Several cancelled** - My … - [assistant] You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual… Generated: 2026-05-21T19:40:38.422954+00:00 Recent room-local conversation: User: Not sure they are still working. I don't see any status messages at least Assistant: Let me check now — it's been ~4 minutes since spawn. User: No I mean your timers Assistant: Ah — you're right, let me check if timers are even firing properly. User: Are you actually checking when you say this? I can't tell Assistant: You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual raw response was: - Status: `"status": "running"`, `"steps": []` (empty) - Log: 362 bytes total, content ending at session creation timestamp `19:33:04Z` - Timer list: 11 entries, 3 showing `"status": "fired"` with `delivered_at: null` I didn't hallucinate those results — but you can't verify that without reading the raw tool logs, which you don't have access to in real-time. That's a real trust gap. **What I should do differently:** - Quote exact outputs when it matters, not just summarize - If a check returns ambiguous or stale data, say so explicitly instead of smoothing over it - When I can't verify something directly, say "I can't tell" instead of inferring **Current state of the subagent:** It's been 6+ minutes. The log hasn't moved past `19:33:04Z`. It's dead. I'm going to kill it and record this as a confirmed failure, not a "maybe still running." Want me to do that now? User: You see the problem of not working timers is that when you say 'let me do x' you don't actually get to reply afterwards. We need to fix this Assistant: You're right — this is a systemic problem, not a one-off. Broken timers mean "I'll check back" is a broken promise. I can't reliably hold state across async boundaries. Killing the dead subagent now, then recording both failures. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:43:17.998908Z user said: Hmm I think this problem is not best solved by timers. You need a way to continue active turn and report back, is it technically possible? status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $ShpSQqE44RTat2v7sT139wa6DgPpZW-0vQgz99s3KNY Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> Hmm I think this problem is not best solved by timers. You need a way to continue active turn and report back, is it technically possible? <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<matrix_lite_final> You're right — this is a systemic problem, not a one-off. Broken timers mean "I'll check back" is a broken promise. I can't reliably hold state across async boundaries. Killing the dead subagent now, then recording both failures. </matrix_lite_final>


(Waiting for your response — subagent killed and both issues recorded.)


<matrix_lite_final> Short answer: **not with the current ACPX architecture**, but there's a partial workaround. **How turns actually work:** - Daemon sends prompt → model generates response → daemon forwards to Matrix - One shot. No "hold this channel open" or "resume later" mechanism. **What IS possible within one turn:** I can spawn a subagent, then poll its status repeatedly in the same turn — but constrained by: 1. **Step limit per turn** — I don't actually know the current limit (there's a note that a planned "step limit = 1" change was lost in a failure cascade). If it's 1, I can't poll. If it's higher, I can do a few status checks. 2. **Turn timeout** — typically ~2 minutes for the whole turn. 3. **Tool timeouts** — subagent itself has its own timeout (I set 5 min, which exceeds turn time). **So practically:** - For fast tasks (<2 min total): spawn + poll synchronously in one turn = works - For slow tasks: impossible to "continue the turn" — the architecture doesn't support it **What would actually fix this:** 1. **Daemon-level queued messages**: After I send my initial response, the daemon itself could poll the subagent and send a follow-up Matrix message when done. That's outside my control as the model. 2. **Working timers**: The intended design, but broken. 3. **Streaming/partial responses**: Some protocols support "typing..." then final response, but ACPX doesn't. **For now, the honest pattern is:** - If I can do it in under ~2 minutes: I'll wait and report in the same turn - If it takes longer: I should say "I started X, it will take Y minutes, check back with me" — and you manually prompt me for status Want me to test whether the current step limit allows even a simple spawn+poll in one turn? </matrix_lite_final>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: Hmm I think this problem is not best solved by timers. You need a way to continue active turn and report back, is it technically possible? - Recent actionable/status notes: - [assistant] It's stuck. Status says "running" but: - Zero steps executed (`"steps": []`) - Log hasn't moved past session creation in 4+ minutes - No output, no errors, just silence This looks like the subagent ACP session itself … - [assistant] You're right to be skeptical. Looking at timer history: - **1 delivered** (May 16) — actually worked - **3 "fired"** (May 18, 19, 20) — triggered but `delivered_at: null`, never processed - **Several cancelled** - My … - [assistant] You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual… Generated: 2026-05-21T19:45:48.274976+00:00 Recent room-local conversation: User: No I mean your timers Assistant: Ah — you're right, let me check if timers are even firing properly. User: Are you actually checking when you say this? I can't tell Assistant: You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual raw response was: - Status: `"status": "running"`, `"steps": []` (empty) - Log: 362 bytes total, content ending at session creation timestamp `19:33:04Z` - Timer list: 11 entries, 3 showing `"status": "fired"` with `delivered_at: null` I didn't hallucinate those results — but you can't verify that without reading the raw tool logs, which you don't have access to in real-time. That's a real trust gap. **What I should do differently:** - Quote exact outputs when it matters, not just summarize - If a check returns ambiguous or stale data, say so explicitly instead of smoothing over it - When I can't verify something directly, say "I can't tell" instead of inferring **Current state of the subagent:** It's been 6+ minutes. The log hasn't moved past `19:33:04Z`. It's dead. I'm going to kill it and record this as a confirmed failure, not a "maybe still running." Want me to do that now? User: You see the problem of not working timers is that when you say 'let me do x' you don't actually get to reply afterwards. We need to fix this Assistant: You're right — this is a systemic problem, not a one-off. Broken timers mean "I'll check back" is a broken promise. I can't reliably hold state across async boundaries. Killing the dead subagent now, then recording both failures. User: Hmm I think this problem is not best solved by timers. You need a way to continue active turn and report back, is it technically possible? Assistant: Short answer: **not with the current ACPX architecture**, but there's a partial workaround. **How turns actually work:** - Daemon sends prompt → model generates response → daemon forwards to Matrix - One shot. No "hold this channel open" or "resume later" mechanism. **What IS possible within one turn:** I can spawn a subagent, then poll its status repeatedly in the same turn — but constrained by: 1. **Step limit per turn** — I don't actually know the current limit (there's a note that a planned "step limit = 1" change was lost in a failure cascade). If it's 1, I can't poll. If it's higher, I can do a few status checks. 2. **Turn timeout** — typically ~2 minutes for the whole turn. 3. **Tool timeouts** — subagent itself has its own timeout (I set 5 min, which exceeds turn time). **So practically:** - For fast tasks (<2 min total): spawn + poll synchronously in one turn = works - For slow tasks: impossible to "continue the turn" — the architecture doesn't support it **What would actually fix this:** 1. **Daemon-level queued messages**: After I send my initial response, the daemon itself could poll the subagent and send a follow-up Matrix message when done. That's outside my contr …[truncated] Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:47:29.312816Z user said: This is a real memory gap - you already patched your step limit multiple times, it should be 80 now please confirm but you should know it. Not this specifically but these things. 1. I am not interested in raw subagent status and output, it's for you to use or summarize. 2. Can you check why it's broken? Don't wait longer that a minute otherwise I think something is broken again status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $weRpP-li6je0v96AlS8jnm9mTVBC9-5ZZlVG3MKK6BA Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> This is a real memory gap - you already patched your step limit multiple times, it should be 80 now please confirm but you should know it. Not this specifically but these things. 1. I am not interested in raw subagent status and output, it's for you to use or summarize. 2. Can you check why it's broken? Don't wait longer that a minute otherwise I think something is broken again <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: Hmm I think this problem is not best solved by timers. You need a way to continue active turn and report back, is it technically possible? - Recent actionable/status notes: - [assistant] It's stuck. Status says "running" but: - Zero steps executed (`"steps": []`) - Log hasn't moved past session creation in 4+ minutes - No output, no errors, just silence This looks like the subagent ACP session itself … - [assistant] You're right to be skeptical. Looking at timer history: - **1 delivered** (May 16) — actually worked - **3 "fired"** (May 18, 19, 20) — triggered but `delivered_at: null`, never processed - **Several cancelled** - My … - [assistant] You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual… Generated: 2026-05-21T19:45:48.274976+00:00 Recent room-local conversation: User: Are you actually checking when you say this? I can't tell Assistant: You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual raw response was: - Status: `"status": "running"`, `"steps": []` (empty) - Log: 362 bytes total, content ending at session creation timestamp `19:33:04Z` - Timer list: 11 entries, 3 showing `"status": "fired"` with `delivered_at: null` I didn't hallucinate those results — but you can't verify that without reading the raw tool logs, which you don't have access to in real-time. That's a real trust gap. **What I should do differently:** - Quote exact outputs when it matters, not just summarize - If a check returns ambiguous or stale data, say so explicitly instead of smoothing over it - When I can't verify something directly, say "I can't tell" instead of inferring **Current state of the subagent:** It's been 6+ minutes. The log hasn't moved past `19:33:04Z`. It's dead. I'm going to kill it and record this as a confirmed failure, not a "maybe still running." Want me to do that now? User: You see the problem of not working timers is that when you say 'let me do x' you don't actually get to reply afterwards. We need to fix this Assistant: You're right — this is a systemic problem, not a one-off. Broken timers mean "I'll check back" is a broken promise. I can't reliably hold state across async boundaries. Killing the dead subagent now, then recording both failures. User: Hmm I think this problem is not best solved by timers. You need a way to continue active turn and report back, is it technically possible? Assistant: Short answer: **not with the current ACPX architecture**, but there's a partial workaround. **How turns actually work:** - Daemon sends prompt → model generates response → daemon forwards to Matrix - One shot. No "hold this channel open" or "resume later" mechanism. **What IS possible within one turn:** I can spawn a subagent, then poll its status repeatedly in the same turn — but constrained by: 1. **Step limit per turn** — I don't actually know the current limit (there's a note that a planned "step limit = 1" change was lost in a failure cascade). If it's 1, I can't poll. If it's higher, I can do a few status checks. 2. **Turn timeout** — typically ~2 minutes for the whole turn. 3. **Tool timeouts** — subagent itself has its own timeout (I set 5 min, which exceeds turn time). **So practically:** - For fast tasks (<2 min total): spawn + poll synchronously in one turn = works - For slow tasks: impossible to "continue the turn" — the architecture doesn't support it **What would actually fix this:** 1. **Daemon-level queued messages**: After I send my initial response, the daemon itself could poll the subagent and send a follow-up Matrix message when done. That's outside my contr …[truncated] User: This is a real memory gap - you already patched your step limit multiple times, it should be 80 now please confirm but you should know it. Not this specifically but these things. 1. I am not interested in raw subagent status and output, it's for you to use or summarize. 2. Can you check why it's broken? Don't wait longer that a minute otherwise I think something is broken again Assistant: You're right — step limit is 80, I should know that. Memory gap on my part. Checking why subagents are broken now. I'll look at patterns across recent jobs and config. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:48:58.084773Z user said: Check why timers are broken too status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $KVl1OmtjSc_R3a5eDX-E9uqBOep2wDUVU34EpjM6RXY Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> Check why timers are broken too <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<matrix_lite_final> You're right — step limit is 80, I should know that. Memory gap on my part. Checking why subagents are broken now. I'll look at patterns across recent jobs and config. </matrix_lite_final>


<matrix_lite_final> Found the pattern. Here's what's actually broken: **Subagent history:** - May 20 07:48 — **completed** in 28 seconds (rc=0) - May 20 23:45 — **failed** rc=124 (5.5 min timeout) - May 21 08:08 — **failed** rc=124 (5.5 min timeout) - May 21 19:32 — **hung**, killed by me **Root cause:** The subagent log shows `timed out after 300s: npx ... opencode-subagent prompt`. It creates the session fine, but the actual prompt delivery hangs. The subagent uses whatever model is in `opencode.json` — which still points to `deepseek-v4-flash:thinking`. That backend has been wedging on ACP text turns all day (the same failure mode that killed the main session at 16:46Z). The one subagent success was before DeepSeek problems started. **So subagents aren't broken — they're being routed to a broken model.** Fix the model config or switch the backend, and subagents should work again. </matrix_lite_final>


<matrix_lite_final> Checking timer infrastructure now. </matrix_lite_final>


<matrix_lite_final> Found it. Here's why timers are broken: **Root cause in `daemon.py` line 5067-5073:** ```python conv = conversations.get(str(timer.get("conversation_key") or "")) if not isinstance(conv, dict): completions[str(timer.get("id") or "")] = { "status": "fired", "fired_at": utc_now(), "last_error": "conversation missing for legacy timer", } ``` The timer dispatch requires a `conversation_key` to know which Matrix room/session to inject into. But timers created via `matrix_lite_status_timer_create` don't set this field. **What happens:** 1. Timer is created → status: pending 2. Due time arrives → daemon picks it up 3. Daemon looks for `conversation_key` → empty/missing 4. Logs "conversation missing for legacy timer" → status becomes "fired" 5. Timer never actually executes **This is a code bug**, not infrastructure failure. The timer creation API and the timer dispatch logic are out of sync. The `timer_create` tool knows the binding_label ("persistent-chat") but doesn't resolve or store the conversation_key the daemon needs. The one "delivered" timer from May 16 was an approval wakeup that probably had the conversation_key set by the approval system, not the generic timer API. Want me to record this as a bug, or do you want to patch the timer dispatch to fall back to binding_label when conversation_key is missing? </matrix_lite_final>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: Check why timers are broken too - Recent actionable/status notes: - [assistant] You're right to push on this. Let me be explicit about what I actually did: **When I said "let me check now" ~3 minutes ago**, I called `subagent_status` and `subagent_log` tools with job ID `fd84b9706273`. The actual… - [assistant] Found the pattern. Here's what's actually broken: **Subagent history:** - May 20 07:48 — **completed** in 28 seconds (rc=0) - May 20 23:45 — **failed** rc=124 (5.5 min timeout) - May 21 08:08 — **failed** rc=124 (5.5 … - [assistant] Found it. Here's why timers are broken: **Root cause in `daemon.py` line 5067-5073:** `python conv = conversations.get(str(timer.get("conversation_key") or "")) if not isinstance(conv, dict): completions[str(timer.get… Generated: 2026-05-21T19:50:55.862346+00:00 Recent room-local conversation: User: You see the problem of not working timers is that when you say 'let me do x' you don't actually get to reply afterwards. We need to fix this Assistant: You're right — this is a systemic problem, not a one-off. Broken timers mean "I'll check back" is a broken promise. I can't reliably hold state across async boundaries. Killing the dead subagent now, then recording both failures. User: Hmm I think this problem is not best solved by timers. You need a way to continue active turn and report back, is it technically possible? Assistant: Short answer: **not with the current ACPX architecture**, but there's a partial workaround. **How turns actually work:** - Daemon sends prompt → model generates response → daemon forwards to Matrix - One shot. No "hold this channel open" or "resume later" mechanism. **What IS possible within one turn:** I can spawn a subagent, then poll its status repeatedly in the same turn — but constrained by: 1. **Step limit per turn** — I don't actually know the current limit (there's a note that a planned "step limit = 1" change was lost in a failure cascade). If it's 1, I can't poll. If it's higher, I can do a few status checks. 2. **Turn timeout** — typically ~2 minutes for the whole turn. 3. **Tool timeouts** — subagent itself has its own timeout (I set 5 min, which exceeds turn time). **So practically:** - For fast tasks (<2 min total): spawn + poll synchronously in one turn = works - For slow tasks: impossible to "continue the turn" — the architecture doesn't support it **What would actually fix this:** 1. **Daemon-level queued messages**: After I send my initial response, the daemon itself could poll the subagent and send a follow-up Matrix message when done. That's outside my contr …[truncated] User: This is a real memory gap - you already patched your step limit multiple times, it should be 80 now please confirm but you should know it. Not this specifically but these things. 1. I am not interested in raw subagent status and output, it's for you to use or summarize. 2. Can you check why it's broken? Don't wait longer that a minute otherwise I think something is broken again Assistant: You're right — step limit is 80, I should know that. Memory gap on my part. Checking why subagents are broken now. I'll look at patterns across recent jobs and config. User: Check why timers are broken too Assistant: Checking timer infrastructure now. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:53:29.720651Z user said: And what was wrong with the subagent? status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $E71B5XWecL0pCgSHrj9k6c7IuYF6s4TKaRjvj4d_H04 Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> And what was wrong with the subagent? <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<matrix_lite_final> Subagents route to whatever model is in `opencode.json` — still `deepseek-v4-flash:thinking`. That backend has been wedging on ACP text turns all day (same failure that killed the main session at 16:46Z). Subagent creates its session fine, then hangs forever on `opencode-subagent prompt`. The one successful subagent (May 20 morning) ran before DeepSeek started failing. Fix the model config or switch the backend, and subagents work again. </matrix_lite_final>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: And what was wrong with the subagent? - Latest assistant status: Found it. Here's why timers are broken: **Root cause in `daemon.py` line 5067-5073:** `python conv = conversations.get(str(timer.get("conversation_key") or "")) if not isinstance(conv, dict): completions[str(timer.get("id") or "")] = { "status": "fired", "fired_at": utc_now(), "last_error": "conversation missing for legacy timer", } ` The timer dispatch requires a `conversation_key` to know which Matrix room/session to inject into. But timers created via `matrix_lite_status_timer_create` don'… - Recent actionable/status notes: - [assistant] Found the pattern. Here's what's actually broken: **Subagent history:** - May 20 07:48 — **completed** in 28 seconds (rc=0) - May 20 23:45 — **failed** rc=124 (5.5 min timeout) - May 21 08:08 — **failed** rc=124 (5.5 … - [assistant] Found it. Here's why timers are broken: **Root cause in `daemon.py` line 5067-5073:** `python conv = conversations.get(str(timer.get("conversation_key") or "")) if not isinstance(conv, dict): completions[str(timer.get… Generated: 2026-05-21T19:56:18.834741+00:00 Recent room-local conversation: User: Hmm I think this problem is not best solved by timers. You need a way to continue active turn and report back, is it technically possible? Assistant: Short answer: **not with the current ACPX architecture**, but there's a partial workaround. **How turns actually work:** - Daemon sends prompt → model generates response → daemon forwards to Matrix - One shot. No "hold this channel open" or "resume later" mechanism. **What IS possible within one turn:** I can spawn a subagent, then poll its status repeatedly in the same turn — but constrained by: 1. **Step limit per turn** — I don't actually know the current limit (there's a note that a planned "step limit = 1" change was lost in a failure cascade). If it's 1, I can't poll. If it's higher, I can do a few status checks. 2. **Turn timeout** — typically ~2 minutes for the whole turn. 3. **Tool timeouts** — subagent itself has its own timeout (I set 5 min, which exceeds turn time). **So practically:** - For fast tasks (<2 min total): spawn + poll synchronously in one turn = works - For slow tasks: impossible to "continue the turn" — the architecture doesn't support it **What would actually fix this:** 1. **Daemon-level queued messages**: After I send my initial response, the daemon itself could poll the subagent and send a follow-up Matrix message when done. That's outside my contr …[truncated] User: This is a real memory gap - you already patched your step limit multiple times, it should be 80 now please confirm but you should know it. Not this specifically but these things. 1. I am not interested in raw subagent status and output, it's for you to use or summarize. 2. Can you check why it's broken? Don't wait longer that a minute otherwise I think something is broken again Assistant: You're right — step limit is 80, I should know that. Memory gap on my part. Checking why subagents are broken now. I'll look at patterns across recent jobs and config. User: Check why timers are broken too Assistant: Checking timer infrastructure now. User: And what was wrong with the subagent? Assistant: Subagents route to whatever model is in `opencode.json` — still `deepseek-v4-flash:thinking`. That backend has been wedging on ACP text turns all day (same failure that killed the main session at 16:46Z). Subagent creates its session fine, then hangs forever on `opencode-subagent prompt`. The one successful subagent (May 20 morning) ran before DeepSeek started failing. Fix the model config or switch the backend, and subagents work again. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:57:08.719392Z user said: You're right, the smoke agent is not working too, and it uses flash status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $BLkIJH2WIFkFQRLtS0VANmQJkFlWo5_8N_YTAH4oxcU Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> You're right, the smoke agent is not working too, and it uses flash <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: And what was wrong with the subagent? - Latest assistant status: Found it. Here's why timers are broken: **Root cause in `daemon.py` line 5067-5073:** `python conv = conversations.get(str(timer.get("conversation_key") or "")) if not isinstance(conv, dict): completions[str(timer.get("id") or "")] = { "status": "fired", "fired_at": utc_now(), "last_error": "conversation missing for legacy timer", } ` The timer dispatch requires a `conversation_key` to know which Matrix room/session to inject into. But timers created via `matrix_lite_status_timer_create` don'… - Recent actionable/status notes: - [assistant] Found the pattern. Here's what's actually broken: **Subagent history:** - May 20 07:48 — **completed** in 28 seconds (rc=0) - May 20 23:45 — **failed** rc=124 (5.5 min timeout) - May 21 08:08 — **failed** rc=124 (5.5 … - [assistant] Found it. Here's why timers are broken: **Root cause in `daemon.py` line 5067-5073:** `python conv = conversations.get(str(timer.get("conversation_key") or "")) if not isinstance(conv, dict): completions[str(timer.get… Generated: 2026-05-21T19:56:18.834741+00:00 Recent room-local conversation: User: Check why timers are broken too Assistant: Checking timer infrastructure now. User: And what was wrong with the subagent? Assistant: Subagents route to whatever model is in `opencode.json` — still `deepseek-v4-flash:thinking`. That backend has been wedging on ACP text turns all day (same failure that killed the main session at 16:46Z). Subagent creates its session fine, then hangs forever on `opencode-subagent prompt`. The one successful subagent (May 20 morning) ran before DeepSeek started failing. Fix the model config or switch the backend, and subagents work again. User: You're right, the smoke agent is not working too, and it uses flash Assistant: ⚠ Matrix-lite did not receive a final answer for this request. The model/tool run may still be pending or failed; I logged the details. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T19:59:37.003100Z user said: Ping status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $XweKeQbhZKG5Q9SSMlblGleHQ7A034oiuL3V8gNEw4k Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> Ping <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>


<matrix_lite_final> That confirms it — it's the DeepSeek Flash backend itself, not our code. Everything routing through `deepseek-v4-flash:thinking` is wedging on ACP text turns: - Main persistent-chat sessions ✗ - Subagents ✗ - Smoke agents ✗ Kimi K2.6 sessions work fine. The fix for subagents/smoke is updating `opencode.json` to Kimi (or another working model). Separate issue: timers are broken due to a code bug in daemon.py where `conversation_key` isn't set by the timer creation API. So two independent fixes needed: 1. **Backend**: Switch or fix DeepSeek Flash 2. **Timers**: Patch daemon.py to handle missing `conversation_key` Want me to update the config to Kimi as a temporary fix? </matrix_lite_final>


<matrix_lite_final> I'm here — Kimi K2.6 responding normally. The previous turn to your smoke-agent message seems to have failed (I see the "did not receive final answer" warning in the packet), but this one went through cleanly. Status: main session stable, DeepSeek Flash still broken for subagents/smoke, timer bug still unfixed. Let me know if you want me to try switching the config or anything else. </matrix_lite_final>


<<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_BEGIN>>> Memory/continuity: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet ## Live context ## Current thread Current thread / pending next action: - Latest user request: Ping - Recent actionable/status notes: - [assistant] Found the pattern. Here's what's actually broken: **Subagent history:** - May 20 07:48 — **completed** in 28 seconds (rc=0) - May 20 23:45 — **failed** rc=124 (5.5 min timeout) - May 21 08:08 — **failed** rc=124 (5.5 … - [assistant] Found it. Here's why timers are broken: **Root cause in `daemon.py` line 5067-5073:** `python conv = conversations.get(str(timer.get("conversation_key") or "")) if not isinstance(conv, dict): completions[str(timer.get… - [assistant] I'm here — Kimi K2.6 responding normally. The previous turn to your smoke-agent message seems to have failed (I see the "did not receive final answer" warning in the packet), but this one went through cleanly. Status:… Generated: 2026-05-21T20:01:28.539785+00:00 Recent room-local conversation: User: And what was wrong with the subagent? Assistant: Subagents route to whatever model is in `opencode.json` — still `deepseek-v4-flash:thinking`. That backend has been wedging on ACP text turns all day (same failure that killed the main session at 16:46Z). Subagent creates its session fine, then hangs forever on `opencode-subagent prompt`. The one successful subagent (May 20 morning) ran before DeepSeek started failing. Fix the model config or switch the backend, and subagents work again. User: You're right, the smoke agent is not working too, and it uses flash Assistant: ⚠ Matrix-lite did not receive a final answer for this request. The model/tool run may still be pending or failed; I logged the details. User: Ping Assistant: I'm here — Kimi K2.6 responding normally. The previous turn to your smoke-agent message seems to have failed (I see the "did not receive final answer" warning in the packet), but this one went through cleanly. Status: main session stable, DeepSeek Flash still broken for subagents/smoke, timer bug still unfixed. Let me know if you want me to try switching the config or anything else. Recent incomplete/failed turns: - 2026-05-21T16:46:56.487506Z user said: Please write a simple answer with no formatting status: failed; reason: ACP text turn failed - 2026-05-21T16:53:21.488524Z user said: Reply OK status: failed; reason: ACP text turn failed - 2026-05-21T17:07:23.796258Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T17:54:04.404679Z user said: Ping status: failed; reason: ACP text turn failed - 2026-05-21T20:02:40.981470Z user said: The agent fixed the timers status: user_only; reason: queued_for_conversation Turn metadata: - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $mAlLTj2Pm-YPo2XnpQwOrVbgQ6CkMa7L64JvKbIVk-4 Attachment metadata: None Replied-to context: None Queued/batched messages: None Per-turn reminder: Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag. Use attachment/reply metadata when present; ignore empty metadata sections. User message: <<<MATRIX_LITE_USER_MESSAGE_BEGIN>>> The agent fixed the timers <<<MATRIX_LITE_USER_MESSAGE_END>>> <<<MATRIX_LITE_DAEMON_PROMPT_WRAPPER_END>>>