Done. Here's how I mapped your responses into structured tracking: **Decision thread** `smallcode-inspired-improvements-2026-05-18` (in `decision-state.json`): | # | Idea | Priority | Scope | Your call | |---|------|----------|-------|-----------| | 1 | Forgiving tool parser | Deferred | — | Later, complex | | 2 | 2-stage tool routing | Medium | Subagents only | Good for background agents | | 3 | Patch-first editing | **High** | Global | "Need our own robust version" | | 4 | Early-stop detection | Needs design | Global | Open question on architecture | | 5 | Model profiles | Medium | Subagents only | Primarily for background agents | **Action items** added to `actions.jsonl`: - Design robust `apply_patch` primitive (high) - Design early-stop detection (low) - Add model profiles for subagents (medium) - Test curated memory + prompts across DeepSeek Pro/Flash (medium) **Open questions** captured: - How to add early-stop in current ACP architecture - Model memory/vibe testing — DeepSeek Pro spiraling, Flash being terse - Can prompt engineering mitigate personality quirks? **Recent topics** updated with today's discussion. Let me know if the priority/scope mapping feels right, or if you want anything moved around.


You are Persistent Assistant running through Matrix-lite. Use the bootstrapped character/session context, live turn packet, and room-local conversation to answer the user naturally. Conversation metadata: - conversation_key: persistent:main - session_label: persistent-chat-20260518T123431Z - prompt_package: None - shared_memory_profile: None - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $HHf8mbZodWFUdyLwVMnV5CEkKU50LmGg0vX2gJr2XyY - reply_to_id: None - thread_root_id: None Persistent-chat memory/continuity context: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet Generated: 2026-05-18T12:54:55.236553+00:00 ## Live context ## Recent reload note # Recent Reload Note Generated: 2026-05-18T12:34:49.081738Z Result: ok Reason: restart persistent-chat Old session: persistent-chat-20260517T115406Z New session: persistent-chat-20260518T123431Z Curation: skipped; ok=True; reason=disabled Packet health: turn=True; session=True; restore_alias=True; stale_turn=False; stale_session=False Details: /home/matrix-lite/state/persistent-chat/reload-state.json If context seems missing, inspect the pre-reload handoff, restore/session packet, and canonical perpetual log before assuming memory loss. ## Backend restart/reload events Recent backend restart/reload events (must be visible to user/agents): - 2026-05-18T14:34:32+02:00: starting; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=? backend=(none) ctx=unavailable unavailable - 2026-05-18T14:34:50+02:00: finished; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=persistent-chat-20260518T123431Z backend=ses_1c4eb4208ffe7u72UUkCBd67PV ctx=31123/200000 acpx usage_update ## Background synthesis notices Background synthesis notices (actionable): - 2026-05-18T12:23:24Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=225420 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:30:49Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:33:54Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - If relevant, inspect the source report/log before acting; notices are pointers, not full context. Live runtime capability context: Runtime details are dynamic; use Matrix-lite status/capability/permission/context tools when current paths, timers, repo access, or reload policy matter. Do not rely on boot-time guesses. Recent room-local conversation: User: Oh I think it went well, and you even remember the link which we just started to discuss Assistant: Glad it went smoothly. The handoff captured the key state, so I knew exactly where we left off. Go ahead and drop the Reddit link — I've got a fresh context window and Playwright ready to go. User: Okay check this out https://www.reddit.com/r/ollama/s/KMxf9q4MgS Assistant: Got it — here's the summary: ## SmallCode — coding agent built for small local models OP (*Glittering_Focus1538*) was frustrated that OpenCode, Cursor, Claude Code all assume frontier models. Built SmallCode from the ground up for small local models, scoring **87/100** on benchmarks with Gemma 4 (4B active params) vs. OpenCode's ~75% with 14B models. ### The tricks that make it work: 1. **Compound tools** — one tool that does find→read→edit→verify instead of 4 chained calls (small models lose coherence after 3+ sequential calls) 2. **Improvement loop** — instantly compiles/lints every write, feeds errors back automatically 3. **Decompose on failure** — after 2 failures, breaks the problem into smaller pieces instead of retrying 4. **Escalation** — if decompose fails and you have cloud API keys, auto-escalates just that one subtask to bigger model 5. **Token budgeting** — summarizes/truncates instead of dumping whole files, never hits context truncation mid-code 6. **Code graph** — indexes code into a symbol graph (functions, classes, callers), walks it for relevant context instead of 15 random grep snippets ### Status: - `npm install -g smallcode`, MIT licensed on [GitHub](htt …[truncated] User: Maybe a brief glance, I don't necessarily want to use the code as is but maybe we can steal some ideas or scripts Assistant: Alright, I skimmed the repo. Here's what's worth stealing vs what we already cover: **Already have / don't need:** - *Context budget engine* — our context guard + packet system does this - *Working memory* — curated memory + perpetual log covers it - *TODO-driven planning* — our existing plan decomposition is equivalent - *BoneScript* — their compound tool DSL is too narrow (Node.js backend generation), not relevant **Worth stealing:** 1. **Forgiving tool call parser** — small models produce messy output. SmallCode parses tool calls from JSON, YAML, XML, Hermes format, or *plain text* and auto-repairs mistakes (wrong param names, type mismatches). This would be very relevant if we switch to smaller local models. 2. **2-stage tool routing** — model picks a category (read/write/search/run/plan) first, then gets only relevant tool schemas. Halves the schema context overhead. Critical for 8-16K context models. 3. **Patch-first editing philosophy** — explicit rationale: "small models can't reliably reproduce entire files — they truncate, hallucinate, or drift." Search-and-replace patches are safer than full-file writes. We already do this via the Edit tool, but the framing is a goo …[truncated] User: 1. i think we need but later it's a bit complex 2. this will be good for your subagents or background agents. in this chat we kinda want full tool availability, or at least on demand (switching to be added later) 3. yes especially considering our earlier glm incident. i see gpt5.5 always thinking about apply_patch in various forms. maybe we need our own robust version 4. how could we possibly add this in the current structure? 5. yes, again primarily for subagents and background. also we still need to see how your memory works with other models and if it changes the 'vibe' too much. Deepseek pro tends to spiral a bit and sounds hysterical sometimes, deepseek flash is very terse. Maybe this could be mitigated by prompts. let's gather this also in our earlier todo, maybe a different section, let's keep it structured. Assistant: I see the structure clearly now. Let me add a proper decision thread and update the recent topics — that's the right structured tracking you asked for.Let me add a structured decision thread and update the recent topics to track all this properly.Done. Here's how I mapped your responses into structured tracking: **Decision thread** `smallcode-inspired-improvements-2026-05-18` (in `decision-state.json`): | # | Idea | Priority | Scope | Your call | |---|------|----------|-------|-----------| | 1 | Forgiving tool parser | Deferred | — | Later, complex | | 2 | 2-stage tool routing | Medium | Subagents only | Good for background agents | | 3 | Patch-first editing | **High** | Global | "Need our own robust version" | | 4 | Early-stop detection | Needs design | Global | Open question on architecture | | 5 | Model profiles | Medium | Subagents only | Primarily for background agents | **Action items** added to `actions.jsonl`: - Design robust `apply_patch` primitive (high) - Design early-stop detection (low) - Add model profiles for subagents (medium) - Test curated memory + prompts across DeepSeek Pro/Flash (medium) **Open questions** captured: - How to add early-stop in current ACP ar …[truncated] Recent incomplete/failed turns that still matter for continuity: - 2026-05-17T17:19:21.968268Z user said: Hmm I hope this doesn't break anything but in any case you should be able to edit those status: user_only; reason: queued_for_conversation - 2026-05-18T09:21:52.960196Z user said: test test status: failed; reason: ACPX completed without a final assistant message - 2026-05-18T12:56:30.729446Z user said: hmm so you think we don't need an explicit text todo.md and you can just carry this in your decision state? i am not complaining, just wondering if this will work long term? status: user_only; reason: queued_for_conversation Recent/current attachment metadata, if any: None Message this user replied to, if any: None Queued/batched messages, if any: None Per-turn volatile reminders: - Answer normally and concisely. Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. - Use the live capability context above as the source of truth for current debug/capability tools; call capability/permission/context MCP tools when uncertain instead of relying on stale boot knowledge. - If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag from your stable prompt; do not only describe approval in prose. - If recent incomplete/failed turns mention an unhandled user intent, address it now before moving on. - Use attachment/reply metadata when present; otherwise ignore empty metadata sections. - Do not mention internal Matrix-lite metadata unless the user asks. User message: hmm so you think we don't need an explicit text todo.md and you can just carry this in your decision state? i am not complaining, just wondering if this will work long term?


You are Persistent Assistant running through Matrix-lite. Use the bootstrapped character/session context, live turn packet, and room-local conversation to answer the user naturally. Conversation metadata: - conversation_key: persistent:main - session_label: persistent-chat-20260518T123431Z - prompt_package: None - shared_memory_profile: None - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $1qCAwzcMem6OZDMVrovEGn6ehy3fLtU2TN4MI-1kaxo - reply_to_id: None - thread_root_id: None Persistent-chat memory/continuity context: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet Generated: 2026-05-18T12:54:55.236553+00:00 ## Live context ## Recent reload note # Recent Reload Note Generated: 2026-05-18T12:34:49.081738Z Result: ok Reason: restart persistent-chat Old session: persistent-chat-20260517T115406Z New session: persistent-chat-20260518T123431Z Curation: skipped; ok=True; reason=disabled Packet health: turn=True; session=True; restore_alias=True; stale_turn=False; stale_session=False Details: /home/matrix-lite/state/persistent-chat/reload-state.json If context seems missing, inspect the pre-reload handoff, restore/session packet, and canonical perpetual log before assuming memory loss. ## Backend restart/reload events Recent backend restart/reload events (must be visible to user/agents): - 2026-05-18T14:34:32+02:00: starting; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=? backend=(none) ctx=unavailable unavailable - 2026-05-18T14:34:50+02:00: finished; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=persistent-chat-20260518T123431Z backend=ses_1c4eb4208ffe7u72UUkCBd67PV ctx=31123/200000 acpx usage_update ## Background synthesis notices Background synthesis notices (actionable): - 2026-05-18T12:23:24Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=225420 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:30:49Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:33:54Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - If relevant, inspect the source report/log before acting; notices are pointers, not full context. Live runtime capability context: Runtime details are dynamic; use Matrix-lite status/capability/permission/context tools when current paths, timers, repo access, or reload policy matter. Do not rely on boot-time guesses. Recent room-local conversation: User: Okay check this out https://www.reddit.com/r/ollama/s/KMxf9q4MgS Assistant: Got it — here's the summary: ## SmallCode — coding agent built for small local models OP (*Glittering_Focus1538*) was frustrated that OpenCode, Cursor, Claude Code all assume frontier models. Built SmallCode from the ground up for small local models, scoring **87/100** on benchmarks with Gemma 4 (4B active params) vs. OpenCode's ~75% with 14B models. ### The tricks that make it work: 1. **Compound tools** — one tool that does find→read→edit→verify instead of 4 chained calls (small models lose coherence after 3+ sequential calls) 2. **Improvement loop** — instantly compiles/lints every write, feeds errors back automatically 3. **Decompose on failure** — after 2 failures, breaks the problem into smaller pieces instead of retrying 4. **Escalation** — if decompose fails and you have cloud API keys, auto-escalates just that one subtask to bigger model 5. **Token budgeting** — summarizes/truncates instead of dumping whole files, never hits context truncation mid-code 6. **Code graph** — indexes code into a symbol graph (functions, classes, callers), walks it for relevant context instead of 15 random grep snippets ### Status: - `npm install -g smallcode`, MIT licensed on [GitHub](htt …[truncated] User: Maybe a brief glance, I don't necessarily want to use the code as is but maybe we can steal some ideas or scripts Assistant: Alright, I skimmed the repo. Here's what's worth stealing vs what we already cover: **Already have / don't need:** - *Context budget engine* — our context guard + packet system does this - *Working memory* — curated memory + perpetual log covers it - *TODO-driven planning* — our existing plan decomposition is equivalent - *BoneScript* — their compound tool DSL is too narrow (Node.js backend generation), not relevant **Worth stealing:** 1. **Forgiving tool call parser** — small models produce messy output. SmallCode parses tool calls from JSON, YAML, XML, Hermes format, or *plain text* and auto-repairs mistakes (wrong param names, type mismatches). This would be very relevant if we switch to smaller local models. 2. **2-stage tool routing** — model picks a category (read/write/search/run/plan) first, then gets only relevant tool schemas. Halves the schema context overhead. Critical for 8-16K context models. 3. **Patch-first editing philosophy** — explicit rationale: "small models can't reliably reproduce entire files — they truncate, hallucinate, or drift." Search-and-replace patches are safer than full-file writes. We already do this via the Edit tool, but the framing is a goo …[truncated] User: 1. i think we need but later it's a bit complex 2. this will be good for your subagents or background agents. in this chat we kinda want full tool availability, or at least on demand (switching to be added later) 3. yes especially considering our earlier glm incident. i see gpt5.5 always thinking about apply_patch in various forms. maybe we need our own robust version 4. how could we possibly add this in the current structure? 5. yes, again primarily for subagents and background. also we still need to see how your memory works with other models and if it changes the 'vibe' too much. Deepseek pro tends to spiral a bit and sounds hysterical sometimes, deepseek flash is very terse. Maybe this could be mitigated by prompts. let's gather this also in our earlier todo, maybe a different section, let's keep it structured. Assistant: I see the structure clearly now. Let me add a proper decision thread and update the recent topics — that's the right structured tracking you asked for.Let me add a structured decision thread and update the recent topics to track all this properly.Done. Here's how I mapped your responses into structured tracking: **Decision thread** `smallcode-inspired-improvements-2026-05-18` (in `decision-state.json`): | # | Idea | Priority | Scope | Your call | |---|------|----------|-------|-----------| | 1 | Forgiving tool parser | Deferred | — | Later, complex | | 2 | 2-stage tool routing | Medium | Subagents only | Good for background agents | | 3 | Patch-first editing | **High** | Global | "Need our own robust version" | | 4 | Early-stop detection | Needs design | Global | Open question on architecture | | 5 | Model profiles | Medium | Subagents only | Primarily for background agents | **Action items** added to `actions.jsonl`: - Design robust `apply_patch` primitive (high) - Design early-stop detection (low) - Add model profiles for subagents (medium) - Test curated memory + prompts across DeepSeek Pro/Flash (medium) **Open questions** captured: - How to add early-stop in current ACP ar …[truncated] User: hmm so you think we don't need an explicit text todo.md and you can just carry this in your decision state? i am not complaining, just wondering if this will work long term? Assistant: Fair question. I think the current setup works **for now**, but it's worth being honest about the trade-offs: **Why structured JSON works:** - Survives reloads better than markdown (no format drift) - Agents (heartbeat, reflection, subagents) can read/update it programmatically - Keeps metadata attached — priority, scope, status, timestamps - The decision thread pattern already proved itself with `obs-features` and `safe-agent-patch-workflow` **Where it could fail long-term:** - You can't glance at it directly — you have to ask me or read a file - `decision-state.json` could become a junk drawer if we don't prune completed threads - Format rigidity means adding ad-hoc notes requires a schema decision - If I'm down or mid-reload, you can't just open `todo.md` in an editor and see what's pending **My honest take:** For *agent-maintained* tracking (decisions, prioritized actions with scope), the JSON approach is better — it's what the heartbeat/reflection pipeline already consumes. But if you ever want self-service visibility without asking me, a companion `todo.md` with a simplified view wouldn't hurt. They'd serve different purposes: the JSON is the source of truth, the markdown …[truncated] Recent incomplete/failed turns that still matter for continuity: - 2026-05-17T17:19:21.968268Z user said: Hmm I hope this doesn't break anything but in any case you should be able to edit those status: user_only; reason: queued_for_conversation - 2026-05-18T09:21:52.960196Z user said: test test status: failed; reason: ACPX completed without a final assistant message - 2026-05-18T12:58:09.271010Z user said: yes let's try the decision state to test it, but please also copy this in a markdown as i can't read json well status: user_only; reason: queued_for_conversation Recent/current attachment metadata, if any: None Message this user replied to, if any: None Queued/batched messages, if any: None Per-turn volatile reminders: - Answer normally and concisely. Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. - Use the live capability context above as the source of truth for current debug/capability tools; call capability/permission/context MCP tools when uncertain instead of relying on stale boot knowledge. - If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag from your stable prompt; do not only describe approval in prose. - If recent incomplete/failed turns mention an unhandled user intent, address it now before moving on. - Use attachment/reply metadata when present; otherwise ignore empty metadata sections. - Do not mention internal Matrix-lite metadata unless the user asks. User message: yes let's try the decision state to test it, but please also copy this in a markdown as i can't read json well


You are Persistent Assistant running through Matrix-lite. Use the bootstrapped character/session context, live turn packet, and room-local conversation to answer the user naturally. Conversation metadata: - conversation_key: persistent:main - session_label: persistent-chat-20260518T123431Z - prompt_package: None - shared_memory_profile: None - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $NOxqZgPDTSZZygzfOxefMulenKG2hZmtFAySuV5ddG8 - reply_to_id: None - thread_root_id: None Persistent-chat memory/continuity context: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet Generated: 2026-05-18T12:54:55.236553+00:00 ## Live context ## Recent reload note # Recent Reload Note Generated: 2026-05-18T12:34:49.081738Z Result: ok Reason: restart persistent-chat Old session: persistent-chat-20260517T115406Z New session: persistent-chat-20260518T123431Z Curation: skipped; ok=True; reason=disabled Packet health: turn=True; session=True; restore_alias=True; stale_turn=False; stale_session=False Details: /home/matrix-lite/state/persistent-chat/reload-state.json If context seems missing, inspect the pre-reload handoff, restore/session packet, and canonical perpetual log before assuming memory loss. ## Backend restart/reload events Recent backend restart/reload events (must be visible to user/agents): - 2026-05-18T14:34:32+02:00: starting; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=? backend=(none) ctx=unavailable unavailable - 2026-05-18T14:34:50+02:00: finished; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=persistent-chat-20260518T123431Z backend=ses_1c4eb4208ffe7u72UUkCBd67PV ctx=31123/200000 acpx usage_update ## Background synthesis notices Background synthesis notices (actionable): - 2026-05-18T12:23:24Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=225420 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:30:49Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:33:54Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - If relevant, inspect the source report/log before acting; notices are pointers, not full context. Live runtime capability context: Runtime details are dynamic; use Matrix-lite status/capability/permission/context tools when current paths, timers, repo access, or reload policy matter. Do not rely on boot-time guesses. Recent room-local conversation: User: Maybe a brief glance, I don't necessarily want to use the code as is but maybe we can steal some ideas or scripts Assistant: Alright, I skimmed the repo. Here's what's worth stealing vs what we already cover: **Already have / don't need:** - *Context budget engine* — our context guard + packet system does this - *Working memory* — curated memory + perpetual log covers it - *TODO-driven planning* — our existing plan decomposition is equivalent - *BoneScript* — their compound tool DSL is too narrow (Node.js backend generation), not relevant **Worth stealing:** 1. **Forgiving tool call parser** — small models produce messy output. SmallCode parses tool calls from JSON, YAML, XML, Hermes format, or *plain text* and auto-repairs mistakes (wrong param names, type mismatches). This would be very relevant if we switch to smaller local models. 2. **2-stage tool routing** — model picks a category (read/write/search/run/plan) first, then gets only relevant tool schemas. Halves the schema context overhead. Critical for 8-16K context models. 3. **Patch-first editing philosophy** — explicit rationale: "small models can't reliably reproduce entire files — they truncate, hallucinate, or drift." Search-and-replace patches are safer than full-file writes. We already do this via the Edit tool, but the framing is a goo …[truncated] User: 1. i think we need but later it's a bit complex 2. this will be good for your subagents or background agents. in this chat we kinda want full tool availability, or at least on demand (switching to be added later) 3. yes especially considering our earlier glm incident. i see gpt5.5 always thinking about apply_patch in various forms. maybe we need our own robust version 4. how could we possibly add this in the current structure? 5. yes, again primarily for subagents and background. also we still need to see how your memory works with other models and if it changes the 'vibe' too much. Deepseek pro tends to spiral a bit and sounds hysterical sometimes, deepseek flash is very terse. Maybe this could be mitigated by prompts. let's gather this also in our earlier todo, maybe a different section, let's keep it structured. Assistant: I see the structure clearly now. Let me add a proper decision thread and update the recent topics — that's the right structured tracking you asked for.Let me add a structured decision thread and update the recent topics to track all this properly.Done. Here's how I mapped your responses into structured tracking: **Decision thread** `smallcode-inspired-improvements-2026-05-18` (in `decision-state.json`): | # | Idea | Priority | Scope | Your call | |---|------|----------|-------|-----------| | 1 | Forgiving tool parser | Deferred | — | Later, complex | | 2 | 2-stage tool routing | Medium | Subagents only | Good for background agents | | 3 | Patch-first editing | **High** | Global | "Need our own robust version" | | 4 | Early-stop detection | Needs design | Global | Open question on architecture | | 5 | Model profiles | Medium | Subagents only | Primarily for background agents | **Action items** added to `actions.jsonl`: - Design robust `apply_patch` primitive (high) - Design early-stop detection (low) - Add model profiles for subagents (medium) - Test curated memory + prompts across DeepSeek Pro/Flash (medium) **Open questions** captured: - How to add early-stop in current ACP ar …[truncated] User: hmm so you think we don't need an explicit text todo.md and you can just carry this in your decision state? i am not complaining, just wondering if this will work long term? Assistant: Fair question. I think the current setup works **for now**, but it's worth being honest about the trade-offs: **Why structured JSON works:** - Survives reloads better than markdown (no format drift) - Agents (heartbeat, reflection, subagents) can read/update it programmatically - Keeps metadata attached — priority, scope, status, timestamps - The decision thread pattern already proved itself with `obs-features` and `safe-agent-patch-workflow` **Where it could fail long-term:** - You can't glance at it directly — you have to ask me or read a file - `decision-state.json` could become a junk drawer if we don't prune completed threads - Format rigidity means adding ad-hoc notes requires a schema decision - If I'm down or mid-reload, you can't just open `todo.md` in an editor and see what's pending **My honest take:** For *agent-maintained* tracking (decisions, prioritized actions with scope), the JSON approach is better — it's what the heartbeat/reflection pipeline already consumes. But if you ever want self-service visibility without asking me, a companion `todo.md` with a simplified view wouldn't hurt. They'd serve different purposes: the JSON is the source of truth, the markdown …[truncated] User: yes let's try the decision state to test it, but please also copy this in a markdown as i can't read json well Assistant: Makes total sense. Let me create a human-readable markdown dashboard that mirrors the JSON decision state + actions.Done. Created `/home/matrix-lite/state/persistent-chat/todo.md` as the human-readable dashboard. It mirrors the JSON decision state and action items in plain markdown with: - **Checkbox action items** sorted by priority (high → medium → low/deferred) - **Decision threads** with status indicators (🔴 active, 🟢 approved, 🔵 informational) - **Open questions** listed under each thread - **File facts** at the bottom The division of labor is: - **`decision-state.json`** — source of truth, parsed by agents/scripts - **`todo.md`** — human dashboard, regenerated/updated when things change - **`actions.jsonl`** — lightweight action item queue for the synthesis pipeline When something changes, I'll keep both in sync. That work for you? Recent incomplete/failed turns that still matter for continuity: - 2026-05-17T17:19:21.968268Z user said: Hmm I hope this doesn't break anything but in any case you should be able to edit those status: user_only; reason: queued_for_conversation - 2026-05-18T09:21:52.960196Z user said: test test status: failed; reason: ACPX completed without a final assistant message - 2026-05-18T12:58:59.588157Z user said: can you publish it? status: user_only; reason: queued_for_conversation Recent/current attachment metadata, if any: None Message this user replied to, if any: None Queued/batched messages, if any: None Per-turn volatile reminders: - Answer normally and concisely. Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. - Use the live capability context above as the source of truth for current debug/capability tools; call capability/permission/context MCP tools when uncertain instead of relying on stale boot knowledge. - If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag from your stable prompt; do not only describe approval in prose. - If recent incomplete/failed turns mention an unhandled user intent, address it now before moving on. - Use attachment/reply metadata when present; otherwise ignore empty metadata sections. - Do not mention internal Matrix-lite metadata unless the user asks. User message: can you publish it?


Fair question. I think the current setup works **for now**, but it's worth being honest about the trade-offs: **Why structured JSON works:** - Survives reloads better than markdown (no format drift) - Agents (heartbeat, reflection, subagents) can read/update it programmatically - Keeps metadata attached — priority, scope, status, timestamps - The decision thread pattern already proved itself with `obs-features` and `safe-agent-patch-workflow` **Where it could fail long-term:** - You can't glance at it directly — you have to ask me or read a file - `decision-state.json` could become a junk drawer if we don't prune completed threads - Format rigidity means adding ad-hoc notes requires a schema decision - If I'm down or mid-reload, you can't just open `todo.md` in an editor and see what's pending **My honest take:** For *agent-maintained* tracking (decisions, prioritized actions with scope), the JSON approach is better — it's what the heartbeat/reflection pipeline already consumes. But if you ever want self-service visibility without asking me, a companion `todo.md` with a simplified view wouldn't hurt. They'd serve different purposes: the JSON is the source of truth, the markdown is the human dashboard. Want me to keep it as-is, or add a lightweight markdown summary alongside it?


Makes total sense. Let me create a human-readable markdown dashboard that mirrors the JSON decision state + actions.


Done. Created `/home/matrix-lite/state/persistent-chat/todo.md` as the human-readable dashboard. It mirrors the JSON decision state and action items in plain markdown with: - **Checkbox action items** sorted by priority (high → medium → low/deferred) - **Decision threads** with status indicators (🔴 active, 🟢 approved, 🔵 informational) - **Open questions** listed under each thread - **File facts** at the bottom The division of labor is: - **`decision-state.json`** — source of truth, parsed by agents/scripts - **`todo.md`** — human dashboard, regenerated/updated when things change - **`actions.jsonl`** — lightweight action item queue for the synthesis pipeline When something changes, I'll keep both in sync. That work for you?


Sure — here it is: # To-Do & Decision Dashboard Generated: 2026-05-18T12:58Z Source of truth: `decision-state.json` + `actions.jsonl` (edits should go there) --- ## Active Action Items ### High Priority - [ ] **Design robust `apply_patch` primitive** — search-and-replace edit safe for smaller models. Motivated by GLM truncation incident; GPT-5.5 already thinks in patches. *(SmallCode-inspired)* ### Medium Priority - [ ] **Add model profiles for subagents** — per-model config: context length, tool format, prompt style, strengths/weaknesses. Primarily for background agents. *(SmallCode-inspired)* - [ ] **Test curated memory + prompts across models** — check vibe compatibility with DeepSeek Pro (spirals, hysterical), DeepSeek Flash (very terse), others. Can prompting mitigate quirks? *(SmallCode-inspired)* - [ ] **Re-apply plan/general step limit → 1** — lost to May 16 failure cascade. - [ ] **Investigate candidates pipeline gap** — no new memory candidates since May 16 packet restructuring. ### Low / Deferred - [ ] **Design early-stop detection** — detect repetition loops / runaway output within current ACP structure. *(SmallCode-inspired, needs architecture design)* - [ ] **Add read namespace allow rule** for `/home/matrix-lite/state/*.jsonl` and `*.json`. - [ ] **Clean up stale memory candidates** (entries from May 11-14) — TTL-based archival or promotion review. - [ ] **Forgiving tool call parser** — parse model output from JSON/YAML/XML/plain text, auto-repair mistakes. *Deferred — complex, relevant when switching to smaller local models.* --- ## Active Decision Threads ### 🔴 SmallCode-inspired improvements *Reviewed SmallCode coding agent (87% benchmark with 4B model). Adopted subset of ideas.* **Open questions:** - How to implement early-stop detection within current ACPX/OpenCode architecture? - Model memory/vibe testing needed before committing to switches - Can prompt engineering mitigate DeepSeek Pro's tendency to spiral? - How to design a robust `apply_patch` primitive across all target models? ### 🔴 Safe agent patch workflow *Need a robust way for background agents to propose/apply patches to scripts/configs without broad self-edit permissions.* ### 🔴 Stale session & compaction policy *Avoid reload unless context pressure or stale session requires it. Capture compaction summaries into durable continuity.* ### 🔴 Investigate session-start overhead *Measure why live ACPX context usage is much higher than visible turn packet estimates.* ### 🔴 Search engine comparison *DuckDuckGo: job-focused. SearXNG: best aggregation. Brave: technical/academic. Exa: richest mixed-context.* ### 🟢 Observability feature requests — **APPROVED** *Four items agreed: event-log, per-failure injection, session-event-log exploration, helper-first.* → See: `observability-feature-requests-2026-05-18.md` ### 🔵 Matrix-lite memory runtime *Canonical memory paths live under `/home/matrix-lite/state/persistent-chat`. Fast heartbeat → packets, slow heartbeat → curation.* --- It's saved at `todo.md` in the persistent-chat state directory alongside the JSON source. Whenever we update something, I'll refresh both so the markdown stays readable.


Persistent-chat active context near threshold: metric=240582, warn=160000, reload=190000, max=200000, label=persistent-chat-20260518T123431Z


context guard recommends reload before overflow active_metric=240582 threshold=190000 max=200000


You are Persistent Assistant running through Matrix-lite. Use the bootstrapped character/session context, live turn packet, and room-local conversation to answer the user naturally. Conversation metadata: - conversation_key: persistent:main - session_label: persistent-chat-20260518T123431Z - prompt_package: None - shared_memory_profile: None - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $pf23OM6obUw3RJMh-Y9A_d_TQDFodoxvdhYczOgSryw - reply_to_id: None - thread_root_id: None Persistent-chat memory/continuity context: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet Generated: 2026-05-18T12:54:55.236553+00:00 ## Live context ## Recent reload note # Recent Reload Note Generated: 2026-05-18T12:34:49.081738Z Result: ok Reason: restart persistent-chat Old session: persistent-chat-20260517T115406Z New session: persistent-chat-20260518T123431Z Curation: skipped; ok=True; reason=disabled Packet health: turn=True; session=True; restore_alias=True; stale_turn=False; stale_session=False Details: /home/matrix-lite/state/persistent-chat/reload-state.json If context seems missing, inspect the pre-reload handoff, restore/session packet, and canonical perpetual log before assuming memory loss. ## Backend restart/reload events Recent backend restart/reload events (must be visible to user/agents): - 2026-05-18T14:34:32+02:00: starting; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=? backend=(none) ctx=unavailable unavailable - 2026-05-18T14:34:50+02:00: finished; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=persistent-chat-20260518T123431Z backend=ses_1c4eb4208ffe7u72UUkCBd67PV ctx=31123/200000 acpx usage_update ## Background synthesis notices Background synthesis notices (actionable): - 2026-05-18T12:23:24Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=225420 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:30:49Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:33:54Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - If relevant, inspect the source report/log before acting; notices are pointers, not full context. Live runtime capability context: Runtime details are dynamic; use Matrix-lite status/capability/permission/context tools when current paths, timers, repo access, or reload policy matter. Do not rely on boot-time guesses. Recent room-local conversation: User: 1. i think we need but later it's a bit complex 2. this will be good for your subagents or background agents. in this chat we kinda want full tool availability, or at least on demand (switching to be added later) 3. yes especially considering our earlier glm incident. i see gpt5.5 always thinking about apply_patch in various forms. maybe we need our own robust version 4. how could we possibly add this in the current structure? 5. yes, again primarily for subagents and background. also we still need to see how your memory works with other models and if it changes the 'vibe' too much. Deepseek pro tends to spiral a bit and sounds hysterical sometimes, deepseek flash is very terse. Maybe this could be mitigated by prompts. let's gather this also in our earlier todo, maybe a different section, let's keep it structured. Assistant: I see the structure clearly now. Let me add a proper decision thread and update the recent topics — that's the right structured tracking you asked for.Let me add a structured decision thread and update the recent topics to track all this properly.Done. Here's how I mapped your responses into structured tracking: **Decision thread** `smallcode-inspired-improvements-2026-05-18` (in `decision-state.json`): | # | Idea | Priority | Scope | Your call | |---|------|----------|-------|-----------| | 1 | Forgiving tool parser | Deferred | — | Later, complex | | 2 | 2-stage tool routing | Medium | Subagents only | Good for background agents | | 3 | Patch-first editing | **High** | Global | "Need our own robust version" | | 4 | Early-stop detection | Needs design | Global | Open question on architecture | | 5 | Model profiles | Medium | Subagents only | Primarily for background agents | **Action items** added to `actions.jsonl`: - Design robust `apply_patch` primitive (high) - Design early-stop detection (low) - Add model profiles for subagents (medium) - Test curated memory + prompts across DeepSeek Pro/Flash (medium) **Open questions** captured: - How to add early-stop in current ACP ar …[truncated] User: hmm so you think we don't need an explicit text todo.md and you can just carry this in your decision state? i am not complaining, just wondering if this will work long term? Assistant: Fair question. I think the current setup works **for now**, but it's worth being honest about the trade-offs: **Why structured JSON works:** - Survives reloads better than markdown (no format drift) - Agents (heartbeat, reflection, subagents) can read/update it programmatically - Keeps metadata attached — priority, scope, status, timestamps - The decision thread pattern already proved itself with `obs-features` and `safe-agent-patch-workflow` **Where it could fail long-term:** - You can't glance at it directly — you have to ask me or read a file - `decision-state.json` could become a junk drawer if we don't prune completed threads - Format rigidity means adding ad-hoc notes requires a schema decision - If I'm down or mid-reload, you can't just open `todo.md` in an editor and see what's pending **My honest take:** For *agent-maintained* tracking (decisions, prioritized actions with scope), the JSON approach is better — it's what the heartbeat/reflection pipeline already consumes. But if you ever want self-service visibility without asking me, a companion `todo.md` with a simplified view wouldn't hurt. They'd serve different purposes: the JSON is the source of truth, the markdown …[truncated] User: yes let's try the decision state to test it, but please also copy this in a markdown as i can't read json well Assistant: Makes total sense. Let me create a human-readable markdown dashboard that mirrors the JSON decision state + actions.Done. Created `/home/matrix-lite/state/persistent-chat/todo.md` as the human-readable dashboard. It mirrors the JSON decision state and action items in plain markdown with: - **Checkbox action items** sorted by priority (high → medium → low/deferred) - **Decision threads** with status indicators (🔴 active, 🟢 approved, 🔵 informational) - **Open questions** listed under each thread - **File facts** at the bottom The division of labor is: - **`decision-state.json`** — source of truth, parsed by agents/scripts - **`todo.md`** — human dashboard, regenerated/updated when things change - **`actions.jsonl`** — lightweight action item queue for the synthesis pipeline When something changes, I'll keep both in sync. That work for you? User: can you publish it? Assistant: Sure — here it is: # To-Do & Decision Dashboard Generated: 2026-05-18T12:58Z Source of truth: `decision-state.json` + `actions.jsonl` (edits should go there) --- ## Active Action Items ### High Priority - [ ] **Design robust `apply_patch` primitive** — search-and-replace edit safe for smaller models. Motivated by GLM truncation incident; GPT-5.5 already thinks in patches. *(SmallCode-inspired)* ### Medium Priority - [ ] **Add model profiles for subagents** — per-model config: context length, tool format, prompt style, strengths/weaknesses. Primarily for background agents. *(SmallCode-inspired)* - [ ] **Test curated memory + prompts across models** — check vibe compatibility with DeepSeek Pro (spirals, hysterical), DeepSeek Flash (very terse), others. Can prompting mitigate quirks? *(SmallCode-inspired)* - [ ] **Re-apply plan/general step limit → 1** — lost to May 16 failure cascade. - [ ] **Investigate candidates pipeline gap** — no new memory candidates since May 16 packet restructuring. ### Low / Deferred - [ ] **Design early-stop detection** — detect repetition loops / runaway output within current ACP structure. *(SmallCode-inspired, needs architecture design)* - [ ] **A …[truncated] Recent incomplete/failed turns that still matter for continuity: - 2026-05-17T17:19:21.968268Z user said: Hmm I hope this doesn't break anything but in any case you should be able to edit those status: user_only; reason: queued_for_conversation - 2026-05-18T09:21:52.960196Z user said: test test status: failed; reason: ACPX completed without a final assistant message - 2026-05-18T12:59:59.318327Z user said: no, i meant publish on pages not here, this is fine too but let's also test if the pages work now status: user_only; reason: queued_for_conversation Recent/current attachment metadata, if any: None Message this user replied to, if any: None Queued/batched messages, if any: None Per-turn volatile reminders: - Answer normally and concisely. Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. - Use the live capability context above as the source of truth for current debug/capability tools; call capability/permission/context MCP tools when uncertain instead of relying on stale boot knowledge. - If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag from your stable prompt; do not only describe approval in prose. - If recent incomplete/failed turns mention an unhandled user intent, address it now before moving on. - Use attachment/reply metadata when present; otherwise ignore empty metadata sections. - Do not mention internal Matrix-lite metadata unless the user asks. User message: no, i meant publish on pages not here, this is fine too but let's also test if the pages work now


You are Persistent Assistant running through Matrix-lite. Use the bootstrapped character/session context, live turn packet, and room-local conversation to answer the user naturally. Conversation metadata: - conversation_key: persistent:main - session_label: persistent-chat-20260518T123431Z - prompt_package: None - shared_memory_profile: None - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $QOgLLh712kiD0P2glHyAhWrO8337FSHyyRZVqn9rg-w - reply_to_id: None - thread_root_id: None Persistent-chat memory/continuity context: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet Generated: 2026-05-18T13:00:05.356542+00:00 ## Live context ## Recent reload note # Recent Reload Note Generated: 2026-05-18T12:34:49.081738Z Result: ok Reason: restart persistent-chat Old session: persistent-chat-20260517T115406Z New session: persistent-chat-20260518T123431Z Curation: skipped; ok=True; reason=disabled Packet health: turn=True; session=True; restore_alias=True; stale_turn=False; stale_session=False Details: /home/matrix-lite/state/persistent-chat/reload-state.json If context seems missing, inspect the pre-reload handoff, restore/session packet, and canonical perpetual log before assuming memory loss. ## Backend restart/reload events Recent backend restart/reload events (must be visible to user/agents): - 2026-05-18T14:34:32+02:00: starting; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=? backend=(none) ctx=unavailable unavailable - 2026-05-18T14:34:50+02:00: finished; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=persistent-chat-20260518T123431Z backend=ses_1c4eb4208ffe7u72UUkCBd67PV ctx=31123/200000 acpx usage_update ## Background synthesis notices Background synthesis notices (actionable): - 2026-05-18T12:23:24Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=225420 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:30:49Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T12:33:54Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - If relevant, inspect the source report/log before acting; notices are pointers, not full context. Live runtime capability context: Runtime details are dynamic; use Matrix-lite status/capability/permission/context tools when current paths, timers, repo access, or reload policy matter. Do not rely on boot-time guesses. Recent room-local conversation: User: hmm so you think we don't need an explicit text todo.md and you can just carry this in your decision state? i am not complaining, just wondering if this will work long term? Assistant: Fair question. I think the current setup works **for now**, but it's worth being honest about the trade-offs: **Why structured JSON works:** - Survives reloads better than markdown (no format drift) - Agents (heartbeat, reflection, subagents) can read/update it programmatically - Keeps metadata attached — priority, scope, status, timestamps - The decision thread pattern already proved itself with `obs-features` and `safe-agent-patch-workflow` **Where it could fail long-term:** - You can't glance at it directly — you have to ask me or read a file - `decision-state.json` could become a junk drawer if we don't prune completed threads - Format rigidity means adding ad-hoc notes requires a schema decision - If I'm down or mid-reload, you can't just open `todo.md` in an editor and see what's pending **My honest take:** For *agent-maintained* tracking (decisions, prioritized actions with scope), the JSON approach is better — it's what the heartbeat/reflection pipeline already consumes. But if you ever want self-service visibility without asking me, a companion `todo.md` with a simplified view wouldn't hurt. They'd serve different purposes: the JSON is the source of truth, the markdown …[truncated] User: yes let's try the decision state to test it, but please also copy this in a markdown as i can't read json well Assistant: Makes total sense. Let me create a human-readable markdown dashboard that mirrors the JSON decision state + actions.Done. Created `/home/matrix-lite/state/persistent-chat/todo.md` as the human-readable dashboard. It mirrors the JSON decision state and action items in plain markdown with: - **Checkbox action items** sorted by priority (high → medium → low/deferred) - **Decision threads** with status indicators (🔴 active, 🟢 approved, 🔵 informational) - **Open questions** listed under each thread - **File facts** at the bottom The division of labor is: - **`decision-state.json`** — source of truth, parsed by agents/scripts - **`todo.md`** — human dashboard, regenerated/updated when things change - **`actions.jsonl`** — lightweight action item queue for the synthesis pipeline When something changes, I'll keep both in sync. That work for you? User: can you publish it? Assistant: Sure — here it is: # To-Do & Decision Dashboard Generated: 2026-05-18T12:58Z Source of truth: `decision-state.json` + `actions.jsonl` (edits should go there) --- ## Active Action Items ### High Priority - [ ] **Design robust `apply_patch` primitive** — search-and-replace edit safe for smaller models. Motivated by GLM truncation incident; GPT-5.5 already thinks in patches. *(SmallCode-inspired)* ### Medium Priority - [ ] **Add model profiles for subagents** — per-model config: context length, tool format, prompt style, strengths/weaknesses. Primarily for background agents. *(SmallCode-inspired)* - [ ] **Test curated memory + prompts across models** — check vibe compatibility with DeepSeek Pro (spirals, hysterical), DeepSeek Flash (very terse), others. Can prompting mitigate quirks? *(SmallCode-inspired)* - [ ] **Re-apply plan/general step limit → 1** — lost to May 16 failure cascade. - [ ] **Investigate candidates pipeline gap** — no new memory candidates since May 16 packet restructuring. ### Low / Deferred - [ ] **Design early-stop detection** — detect repetition loops / runaway output within current ACP structure. *(SmallCode-inspired, needs architecture design)* - [ ] **A …[truncated] User: no, i meant publish on pages not here, this is fine too but let's also test if the pages work now Assistant: Ah, you mean publish to Matrix-lite pages, not just paste it here. Let me figure out how that works.Let me publish the todo.md to Matrix-lite pages.Published successfully. Let me verify it's serving:Published successfully. The file landed at `/home/matrix-lite/pages/todo.md` — you should be able to see it at **https://pages.nvdll.org/todo.md**. The publish itself worked (the CLI reported `ok: true` with metadata), though the public URL returns a 401 for me — that might be an auth config thing on the pages server or it might only serve to certain origins. Let me know if you can see it on your end, and if not I can check the pages server config. Recent incomplete/failed turns that still matter for continuity: - 2026-05-17T17:19:21.968268Z user said: Hmm I hope this doesn't break anything but in any case you should be able to edit those status: user_only; reason: queued_for_conversation - 2026-05-18T09:21:52.960196Z user said: test test status: failed; reason: ACPX completed without a final assistant message - 2026-05-18T13:04:02.408999Z user said: great thank you. observability is great - you see this item? • [ ] **Re-apply plan/general step limit → 1** — lost to May 16 failure cascade. this should already have been applied during the cascade, please confirm. Your step limit should be 80, 20 for curation/model hearbeat, 1 for plan/general so we see if they are unexpectedly in use status: user_only; reason: queued_for_conversation Recent/current attachment metadata, if any: None Message this user replied to, if any: None Queued/batched messages, if any: None Per-turn volatile reminders: - Answer normally and concisely. Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. - Use the live capability context above as the source of truth for current debug/capability tools; call capability/permission/context MCP tools when uncertain instead of relying on stale boot knowledge. - If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag from your stable prompt; do not only describe approval in prose. - If recent incomplete/failed turns mention an unhandled user intent, address it now before moving on. - Use attachment/reply metadata when present; otherwise ignore empty metadata sections. - Do not mention internal Matrix-lite metadata unless the user asks. User message: great thank you. observability is great - you see this item? • [ ] **Re-apply plan/general step limit → 1** — lost to May 16 failure cascade. this should already have been applied during the cascade, please confirm. Your step limit should be 80, 20 for curation/model hearbeat, 1 for plan/general so we see if they are unexpectedly in use


Ah, you mean publish to Matrix-lite pages, not just paste it here. Let me figure out how that works.


Let me publish the todo.md to Matrix-lite pages.


Published successfully. Let me verify it's serving:


Published successfully. The file landed at `/home/matrix-lite/pages/todo.md` — you should be able to see it at **https://pages.nvdll.org/todo.md**. The publish itself worked (the CLI reported `ok: true` with metadata), though the public URL returns a 401 for me — that might be an auth config thing on the pages server or it might only serve to certain origins. Let me know if you can see it on your end, and if not I can check the pages server config.


You're right — let me check the current step limits and fix that.


Confirmed — the step limits are **already in place**: | Agent | Steps | |-------|-------| | **build** (main) | 80 | | **model-heartbeat** | 20 | | **plan** | 1 | | **general** | 1 | That stale action item was never cleaned up after the cascade applied the change. Let me fix that now.


Good catch — that was a stale item I should have cleaned up. Here's the **verified state**: - **build**: `steps: 80` ✓ - **model-heartbeat**: `steps: 20` ✓ - **plan**: `steps: 1` ✓ - **general**: `steps: 1` ✓ The limits were already applied during the failure cascade on May 16; the action item just wasn't marked resolved. I've now: - Marked it resolved in `actions.jsonl` - Updated `todo.md` with a checkmark and verified values - The markers are: if `plan` or `general` ever use more than 1 step, that's visible in the telemetry and means something unexpected is consuming them


You are Persistent Assistant running through Matrix-lite. Use the bootstrapped character/session context, live turn packet, and room-local conversation to answer the user naturally. Conversation metadata: - conversation_key: persistent:main - session_label: persistent-chat-20260518T123431Z - prompt_package: None - shared_memory_profile: None - room_id: !CZLwoJfCyftA7oA5CVj2gIEKWqyv1lu01r0oFboEqZg - source_event_id: $G1i6IB4Fb0i71ozA6g0XehLAXvggbHKG1bX7yuaPA2o - reply_to_id: None - thread_root_id: None Persistent-chat memory/continuity context: Persistent-chat memory/continuity context: mode: turn_packet # Persistent Chat Turn Packet Generated: 2026-05-18T13:05:15.226282+00:00 ## Live context ## Recent reload note # Recent Reload Note Generated: 2026-05-18T12:34:49.081738Z Result: ok Reason: restart persistent-chat Old session: persistent-chat-20260517T115406Z New session: persistent-chat-20260518T123431Z Curation: skipped; ok=True; reason=disabled Packet health: turn=True; session=True; restore_alias=True; stale_turn=False; stale_session=False Details: /home/matrix-lite/state/persistent-chat/reload-state.json If context seems missing, inspect the pre-reload handoff, restore/session packet, and canonical perpetual log before assuming memory loss. ## Backend restart/reload events Recent backend restart/reload events (must be visible to user/agents): - 2026-05-18T14:34:32+02:00: starting; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=? backend=(none) ctx=unavailable unavailable - 2026-05-18T14:34:50+02:00: finished; reason=restart persistent-chat; old=persistent-chat-20260517T115406Z backend=ses_1c59bcf07ffeqslkj7QeqnpjFW ctx=238502/200000 acpx usage_update; new=persistent-chat-20260518T123431Z backend=ses_1c4eb4208ffe7u72UUkCBd67PV ctx=31123/200000 acpx usage_update ## Background synthesis notices Background synthesis notices (actionable): - 2026-05-18T12:33:54Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=238502 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T13:05:14Z [notice] Persistent-chat context warning: Persistent-chat active context near threshold: metric=240582, warn=160000, reload=190000, max=200000, label=persistent-chat-20260518T123431Z (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - 2026-05-18T13:05:14Z [warning] Persistent-chat reload recommended: context guard recommends reload before overflow active_metric=240582 threshold=190000 max=200000; main agent should prepare a pre-reload handoff and trigger persistent-chat-reload when ready. (source: /home/matrix-lite/state/persistent-chat/context-guard.json) - If relevant, inspect the source report/log before acting; notices are pointers, not full context. Live runtime capability context: Runtime details are dynamic; use Matrix-lite status/capability/permission/context tools when current paths, timers, repo access, or reload policy matter. Do not rely on boot-time guesses. Recent room-local conversation: User: yes let's try the decision state to test it, but please also copy this in a markdown as i can't read json well Assistant: Makes total sense. Let me create a human-readable markdown dashboard that mirrors the JSON decision state + actions.Done. Created `/home/matrix-lite/state/persistent-chat/todo.md` as the human-readable dashboard. It mirrors the JSON decision state and action items in plain markdown with: - **Checkbox action items** sorted by priority (high → medium → low/deferred) - **Decision threads** with status indicators (🔴 active, 🟢 approved, 🔵 informational) - **Open questions** listed under each thread - **File facts** at the bottom The division of labor is: - **`decision-state.json`** — source of truth, parsed by agents/scripts - **`todo.md`** — human dashboard, regenerated/updated when things change - **`actions.jsonl`** — lightweight action item queue for the synthesis pipeline When something changes, I'll keep both in sync. That work for you? User: can you publish it? Assistant: Sure — here it is: # To-Do & Decision Dashboard Generated: 2026-05-18T12:58Z Source of truth: `decision-state.json` + `actions.jsonl` (edits should go there) --- ## Active Action Items ### High Priority - [ ] **Design robust `apply_patch` primitive** — search-and-replace edit safe for smaller models. Motivated by GLM truncation incident; GPT-5.5 already thinks in patches. *(SmallCode-inspired)* ### Medium Priority - [ ] **Add model profiles for subagents** — per-model config: context length, tool format, prompt style, strengths/weaknesses. Primarily for background agents. *(SmallCode-inspired)* - [ ] **Test curated memory + prompts across models** — check vibe compatibility with DeepSeek Pro (spirals, hysterical), DeepSeek Flash (very terse), others. Can prompting mitigate quirks? *(SmallCode-inspired)* - [ ] **Re-apply plan/general step limit → 1** — lost to May 16 failure cascade. - [ ] **Investigate candidates pipeline gap** — no new memory candidates since May 16 packet restructuring. ### Low / Deferred - [ ] **Design early-stop detection** — detect repetition loops / runaway output within current ACP structure. *(SmallCode-inspired, needs architecture design)* - [ ] **A …[truncated] User: no, i meant publish on pages not here, this is fine too but let's also test if the pages work now Assistant: Ah, you mean publish to Matrix-lite pages, not just paste it here. Let me figure out how that works.Let me publish the todo.md to Matrix-lite pages.Published successfully. Let me verify it's serving:Published successfully. The file landed at `/home/matrix-lite/pages/todo.md` — you should be able to see it at **https://pages.nvdll.org/todo.md**. The publish itself worked (the CLI reported `ok: true` with metadata), though the public URL returns a 401 for me — that might be an auth config thing on the pages server or it might only serve to certain origins. Let me know if you can see it on your end, and if not I can check the pages server config. User: great thank you. observability is great - you see this item? • [ ] **Re-apply plan/general step limit → 1** — lost to May 16 failure cascade. this should already have been applied during the cascade, please confirm. Your step limit should be 80, 20 for curation/model hearbeat, 1 for plan/general so we see if they are unexpectedly in use Assistant: You're right — let me check the current step limits and fix that.Confirmed — the step limits are **already in place**: | Agent | Steps | |-------|-------| | **build** (main) | 80 | | **model-heartbeat** | 20 | | **plan** | 1 | | **general** | 1 | That stale action item was never cleaned up after the cascade applied the change. Let me fix that now.Good catch — that was a stale item I should have cleaned up. Here's the **verified state**: - **build**: `steps: 80` ✓ - **model-heartbeat**: `steps: 20` ✓ - **plan**: `steps: 1` ✓ - **general**: `steps: 1` ✓ The limits were already applied during the failure cascade on May 16; the action item just wasn't marked resolved. I've now: - Marked it resolved in `actions.jsonl` - Updated `todo.md` with a checkmark and verified values - The markers are: if `plan` or `general` ever use more than 1 step, that's visible in the telemetry and means something unexpected is consuming them Recent incomplete/failed turns that still matter for continuity: - 2026-05-17T17:19:21.968268Z user said: Hmm I hope this doesn't break anything but in any case you should be able to edit those status: user_only; reason: queued_for_conversation - 2026-05-18T09:21:52.960196Z user said: test test status: failed; reason: ACPX completed without a final assistant message - 2026-05-18T13:10:16.810490Z user said: won't decision state and actions become noisy for you if we keep adding more stuff there? i guess structured jsons are better than scattered files but we need to keep track of stale or outdated items status: user_only; reason: queued_for_conversation Recent/current attachment metadata, if any: [ { "event_id": "$Rz-BZg2imij6ZjQ5G7nUEJcAhNbX-zJU0_dwGHovlXs", "sender_id": "@gleb:matrix.nvdll.org", "text": "sfq_architecture_report (1).docx", "attachment": { "body": "sfq_architecture_report (1).docx", "download": { "event_id": "$Rz-BZg2imij6ZjQ5G7nUEJcAhNbX-zJU0_dwGHovlXs", "filename": "sfq_architecture_report _1_.docx", "mime": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "mxc_url": "mxc://matrix.nvdll.org/zbJeis8GQ6LWOcTVk5uHkwIcQ5e2zRh8", "path": "/home/matrix-lite/state/inbox/Rz-BZg2imij6ZjQ5G7nUEJcAhNbX-zJU0_dwGHovlXs/sfq_architecture_report _1_.docx", "size": 30115 }, "encrypted": false, "filename": null, "local_path": "/home/matrix-lite/state/inbox/Rz-BZg2imij6ZjQ5G7nUEJcAhNbX-zJU0_dwGHovlXs/sfq_architecture_report _1_.docx", "mime": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "msgtype": "m.file", "mxc_url": "mxc://matrix.nvdll.org/zbJeis8GQ6LWOcTVk5uHkwIcQ5e2zRh8", "size": 30115 }, "logged_at": "2026-05-15T23:05:36.164808Z" } ] Message this user replied to, if any: None Queued/batched messages, if any: None Per-turn volatile reminders: - Answer normally and concisely. Put only user-visible answer text inside <matrix_lite_final>...</matrix_lite_final>. - Use the live capability context above as the source of truth for current debug/capability tools; call capability/permission/context MCP tools when uncertain instead of relying on stale boot knowledge. - If permission is needed or a bridge denies a tool, emit the structured Matrix-lite approval tag from your stable prompt; do not only describe approval in prose. - If recent incomplete/failed turns mention an unhandled user intent, address it now before moving on. - Use attachment/reply metadata when present; otherwise ignore empty metadata sections. - Do not mention internal Matrix-lite metadata unless the user asks. User message: won't decision state and actions become noisy for you if we keep adding more stuff there? i guess structured jsons are better than scattered files but we need to keep track of stale or outdated items


Fair question. The honest answer is: **yes, it will become noisy** if we don't actively manage it. The current system works because this session is young — but let me be upfront about the failure modes: **What I've already seen go stale:** - That "Re-apply step limit" item sat resolved for 2 days without being cleared - The "search-engine-comparison" decision thread is basically settled trivia, not an active decision - Old resolved actions accumulate in `actions.jsonl` with no cleanup **What should happen (but doesn't yet automatically):** | Problem | Fix needed | |---------|-----------| | Resolved actions accumulate | `prune-state` helper exists but needs to be called regularly — should be part of the heartbeat | | Decision threads become historical notes | Threads that are "settled knowledge" (not open decisions) should migrate to `curated-memory.md` and be removed from decision state | | No TTL for stale items | Could tag items with a review-by date; heartbeat flags anything past it | | Manual cleanup burden on me | I can do it, but if I forget, noise builds up | **The heartbeat already has `prune-state` access.** The model-heartbeat agent has permission to run `persistent-chat-memory prune-state *` — that's the tool for this. But I don't think the heartbeat currently calls it proactively. Want me to add "periodic stale-item pruning" to the heartbeat's responsibilities in the decision state? That way old resolved actions and settled threads get archived automatically on each heartbeat cycle rather than requiring me to notice them.