* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1302.5s
Time: model 1299.5s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1364.4s
Time: model 1361.4s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1426.3s
Time: model 1423.3s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1488.2s
Time: model 1485.2s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1550.1s
Time: model 1547.1s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1612.0s
Time: model 1609.1s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1674.0s
Time: model 1671.1s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1736.0s
Time: model 1733.0s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1797.7s
Time: model 1794.8s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🔴 Approval expired
Stage: native ACP permission request is no longer active
Tool: bash
Approval: dap-1780091695-perm-1780091695420-4
Cause: opaque direct ACP permission timed out; OpenCode supplied no path/command details to match later


* 🟠 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 1833.7s
Time: model 1830.7s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: est $0.0000; p≈1.9ktok/7.7kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🔴 Failed
Stage: model/tool run failed
Model: openai/gpt-5.4
Elapsed: 1835.0s
Time: model 1830.7s
Cause: direct ACP timeout after 1830s/1830000ms
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


* 🔴 Failed
Stage: no final answer
Model: openai/gpt-5.4
Elapsed: 1835.6s
Time: model 1830.7s
Cause: direct ACP timeout after 1830s/1830000ms
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


⚠ Matrix-lite did not receive a final answer for this request. The direct ACP model/tool run failed or was interrupted before it produced a final response. If this was blocked by permissions, I can request same-room native ACP approval or use the privileged broker for root-required commands; please retry the request.


* 🔴 Failed
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 1836.7s
Time: model 1830.7s, overhead 6.0s
Cause: direct ACP timeout after 1830s/1830000ms
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: est $0.0000; p≈1.9ktok/7.7kch
Ctx: direct ACP p≈1.9ktok; ctx 7.2%; usable 7.3%; observed turns 5; actual turns 6


Sorry fell asleep. Can you try again please I will approve this time


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 6; actual turns 6


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.1s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 6; actual turns 6


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.7s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 6; actual turns 6


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.4s
Time: overhead 1.4s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.1ktok/8.3kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 6; actual turns 6


📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Waiting for first model/tool update…


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
I


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (2):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- bash / pending / call_0dxgK2V7FHtkOjytvqFVfag

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780130872-perm-1780130871999-1
Summary: OpenCode requests bash for execute
Tool: bash
Kind: execute
Nearest active tool: bash / in_progress / python -m pytest tests/test_continuity_scripts.py -k "direct_acp_client_script_is_smoke_agent_ready" / cwd=/home/matrix-lite/app
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Approval granted
Stage: resuming
Tool: bash
Approval: dap-1780130872-perm-1780130871999-1


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (3):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- bash / in_progress / python -m pytest tests/test_daemon_stability.py -k "direct_acp_client_emits_prompt_started_before_prompt or direct_acp_prompt_persists_phase_and_first_event_timing" / cwd=/home/matrix-lite/app
- bash / in_progress / python -m pytest tests/test_continuity_scripts.py -k "direct_acp_client_script_is_smoke_agent_ready" / cwd=/home/matrix-lite/app

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780130882-perm-1780130882844-2
Summary: OpenCode requests bash for execute
Tool: bash
Kind: execute
Nearest active tool: bash / in_progress / python -m pytest tests/test_daemon_stability.py -k "direct_acp_client_emits_prompt_started_before_prompt or direct_acp_prompt_persists_phase_and_first_event_timing" / cwd=/home/matrix-lite/app
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Approval granted
Stage: resuming
Tool: bash
Approval: dap-1780130882-perm-1780130882844-2


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (3):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780130892-perm-1780130892284-3
Summary: OpenCode requests bash for execute
Tool: bash
Kind: execute
Nearest active tool: bash / pending / call_yoEW663PsaYxh97h3RadNAv
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Approval granted
Stage: resuming
Tool: bash
Approval: dap-1780130892-perm-1780130892284-3


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (4):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- bash / in_progress / python3 -m pytest tests/test_daemon_stability.py -k "direct_acp_client_emits_prompt_started_before_prompt or direct_acp_prompt_persists_phase_and_first_event_timing" / cwd=/home/matrix-lite/app

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780130896-perm-1780130896600-4
Summary: OpenCode requests bash for execute
Tool: bash
Kind: execute
Nearest active tool: bash / in_progress / python3 -m pytest tests/test_daemon_stability.py -k "direct_acp_client_emits_prompt_started_before_prompt or direct_acp_prompt_persists_phase_and_first_event_timing" / cwd=/home/matrix-lite/app
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Approval granted
Stage: resuming
Tool: bash
Approval: dap-1780130896-perm-1780130896600-4


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (5):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- bash / in_progress / python3 -m pytest tests/test_daemon_stability.py -k "direct_acp_client_emits_prompt_started_before_prompt or direct_acp_prompt_persists_phase_and_first_event_timing" / cwd=/home/matrix-lite/app
- bash / in_progress / python3 -m pytest tests/test_continuity_scripts.py -k "direct_acp_client_script_is_smoke_agent_ready" / cwd=/home/matrix-lite/app

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (5):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 63.5s
Time: model 61.2s, overhead 1.4s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.1ktok/8.3kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 6; actual turns 7


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (7):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (8):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- bash / pending / call_Hz90I2c06X6gCKZKWLYes8s

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780130921-perm-1780130921605-5
Summary: OpenCode requests bash for execute
Tool: bash
Kind: execute
Nearest active tool: bash / pending / call_Hz90I2c06X6gCKZKWLYes8s
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Approval granted
Stage: resuming
Tool: bash
Approval: dap-1780130921-perm-1780130921605-5


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (8):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- bash / in_progress / "/home/matrix-lite/venvs/mcp/bin/pytest" tests/test_daemon_stability.py -k "direct_acp_client_emits_prompt_started_before_prompt or direct_acp_prompt_persists_phase_and_first_event_timing" / cwd=/home/matrix-lite/app

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780130934-perm-1780130934247-6
Summary: OpenCode requests bash for execute
Tool: bash
Kind: execute
Nearest active tool: bash / in_progress / "/home/matrix-lite/venvs/mcp/bin/pytest" tests/test_continuity_scripts.py -k "direct_acp_client_script_is_smoke_agent_ready" / cwd=/home/matrix-lite/app
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Approval granted
Stage: resuming
Tool: bash
Approval: dap-1780130934-perm-1780130934247-6


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (9):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- bash / in_progress / "/home/matrix-lite/venvs/mcp/bin/pytest" tests/test_daemon_stability.py -k "direct_acp_client_emits_prompt_started_before_prompt or direct_acp_prompt_persists_phase_and_first_event_timing" / cwd=/home/matrix-lite/app
- bash / in_progress / "/home/matrix-lite/venvs/mcp/bin/pytest" tests/test_continuity_scripts.py -k "direct_acp_client_script_is_smoke_agent_ready" / cwd=/home/matrix-lite/app

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (9):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780130946-perm-1780130946054-7
Summary: OpenCode requests edit for ../../app/tests/test_daemon_stability.py
Tool: edit
Scope: ../../app/tests/test_daemon_stability.py
Input:
```
{"filepath":"../../app/tests/test_daemon_stability.py","diff":"Index: /home/matrix-lite/app/tests/test_daemon_stability.py\n===================================================================\n--- /home/matrix-lite/app/tests/test_daemon_stability.py\n+++ /home/matrix-lite/app/tests/test_daemon_stability.py\n@@ -657,9 +657,9 @@\n     self.assertIn(\"reason: 'hidden_content'\", text)\n     self.assertLess(text.index('client.startPrompt()'), text.index(\"event: 'prompt_started'\"))\n     self.assertIn('async function waitForPromptQuiet', text)\n     self.assertIn('const promptDrainMs = await waitForPromptQuiet(client)', text)\n-    self.assertIn(\"phase: 'prompt_drain_done'\", text)\n+    self.assertIn(\"emitPhase('prompt_drain_done'\", text)\n     self.assertLess(text.index('const finalText = client.finalText()'), text.index('client.finishPrompt()'))\n \n def test_direct_acp_prompt_uses_client_jsonl_done_text(self):\n     calls = []\n\n","files":["[object Object]"]}
```
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Approval granted
Stage: resuming
Tool: edit
Scope: ../../app/tests/test_daemon_stability.py
Approval: dap-1780130946-perm-1780130946054-7


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (10):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Success. Updated the following files:
M ../../app/tests/test_daemon_stability.py / completed / call_fQgo8X2PeIe5bSWTD1oxxF5

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.Good news: one targeted test passed, and the other failed only because my test assertion was slightly wrong — the code emits `emitPhase('prompt_drain_done', ...)`, not the exact string I asserted.

I’m fixing that test and rerunning.


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (11):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Success. Updated the following files:
M ../../app/tests/test_daemon_stability.py / completed / call_fQgo8X2PeIe5bSWTD1oxxF5
- bash / pending / call_MZfpqHJemRLoym8FhFYAlQI

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.Good news: one targeted test passed, and the other failed only because my test assertion was slightly wrong — the code emits `emitPhase('prompt_drain_done', ...)`, not the exact string I asserted.

I’m fixing that test and rerunning.


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780130961-perm-1780130961155-8
Summary: OpenCode requests bash for execute
Tool: bash
Kind: execute
Nearest active tool: bash / pending / call_MZfpqHJemRLoym8FhFYAlQI
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Approval granted
Stage: resuming
Tool: bash
Approval: dap-1780130961-perm-1780130961155-8


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780130964-perm-1780130964623-9
Summary: OpenCode requests bash for execute
Tool: bash
Kind: execute
Nearest active tool: bash / in_progress / "/home/matrix-lite/venvs/mcp/bin/pytest" tests/test_daemon_stability.py -k "direct_acp_client_emits_prompt_started_before_prompt or direct_acp_prompt_persists_phase_and_first_event_timing" / cwd=/home/matrix-lite/app
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Approval granted
Stage: resuming
Tool: bash
Approval: dap-1780130964-perm-1780130964623-9


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (12):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Success. Updated the following files:
M ../../app/tests/test_daemon_stability.py / completed / call_fQgo8X2PeIe5bSWTD1oxxF5
- bash / in_progress / "/home/matrix-lite/venvs/mcp/bin/pytest" tests/test_daemon_stability.py -k "direct_acp_client_emits_prompt_started_before_prompt or direct_acp_prompt_persists_phase_and_first_event_timing" / cwd=/home/matrix-lite/app
- bash / in_progress / "/home/matrix-lite/venvs/mcp/bin/pytest" tests/test_continuity_scripts.py -k "direct_acp_client_script_is_smoke_agent_ready" / cwd=/home/matrix-lite/app

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.Good news: one targeted test passed, and the other failed only because my test assertion was slightly wrong — the code emits `emitPhase('prompt_drain_done', ...)`, not the exact string I asserted.

I’m fixing that test and rerunning.


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (13):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Success. Updated the following files:
M ../../app/tests/test_daemon_stability.py / completed / call_fQgo8X2PeIe5bSWTD1oxxF5
- Reruns targeted daemon stability tests / completed / Reruns targeted daemon stability tests
- Reruns direct ACP script continuity test / completed / Reruns direct ACP script continuity test
- todowrite / pending / call_inEb2Qz32228LnfYS5rTHjj

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.Good news: one targeted test passed, and the other failed only because my test assertion was slightly wrong — the code emits `emitPhase('prompt_drain_done', ...)`, not the exact string I asserted.

I’m fixing that test and rerunning.


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 125.6s
Time: model 123.4s, overhead 1.4s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.1ktok/8.3kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 6; actual turns 7


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (13):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Success. Updated the following files:
M ../../app/tests/test_daemon_stability.py / completed / call_fQgo8X2PeIe5bSWTD1oxxF5
- Reruns targeted daemon stability tests / completed / Reruns targeted daemon stability tests
- Reruns direct ACP script continuity test / completed / Reruns direct ACP script continuity test
- 0 todos / completed / call_inEb2Qz32228LnfYS5rTHjj

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.Good news: one targeted test passed, and the other failed only because my test assertion was slightly wrong — the code emits `emitPhase('prompt_drain_done', ...)`, not the exact string I asserted.

I’m fixing that test and rerunning.Yep — I retried it and got a fix in.

What I changed:
- In `/


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (13):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Success. Updated the following files:
M ../../app/tests/test_daemon_stability.py / completed / call_fQgo8X2PeIe5bSWTD1oxxF5
- Reruns targeted daemon stability tests / completed / Reruns targeted daemon stability tests
- Reruns direct ACP script continuity test / completed / Reruns direct ACP script continuity test
- 0 todos / completed / call_inEb2Qz32228LnfYS5rTHjj

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.Good news: one targeted test passed, and the other failed only because my test assertion was slightly wrong — the code emits `emitPhase('prompt_drain_done', ...)`, not the exact string I asserted.

I’m fixing that test and rerunning.Yep — I retried it and got a fix in.

What I changed:
- In `/home/matrix-lite/app/scripts/matrix-lite-direct-acp-client.mjs`
- Replaced the fixed post-prompt `await sleep(250)` with a bounded **wait-for-quiet** drain
- The client now tracks the last prompt-time session update and waits for a short quiet period before snapshotting final text
- It also emits a `prompt_drain_done` phase for observability

Why this should fix it:
- The likely bug was: `connection.prompt()` returned, then the client waited a fixed 250ms, but late final message chunks were still arriving
- So it sometimes snapshotted an incomplete assistant message and sent that truncated version to Matrix
- Now it waits for the stream to actually go quiet instead of assuming 250ms is enough

Tests:
- Initial rerun was allowed; first I hit `python: command not found`
- Then `python3` worked but lacked pytest
- I found and used `/home/matrix-lite/venvs/mcp/bin/pytest`
- Final targeted results:
  - `tests/test_daemon_stability


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (13):
- 1 todos / completed / call_tiJRiOFrjrO6xFj8XMlnvWv
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- ../.. / completed / /home/matrix-lite
- ../.. / completed / /home/matrix-lite
- Runs targeted daemon stability tests / completed / Runs targeted daemon stability tests
- Runs direct ACP script continuity test / completed / Runs direct ACP script continuity test
- Success. Updated the following files:
M ../../app/tests/test_daemon_stability.py / completed / call_fQgo8X2PeIe5bSWTD1oxxF5
- Reruns targeted daemon stability tests / completed / Reruns targeted daemon stability tests
- Reruns direct ACP script continuity test / completed / Reruns direct ACP script continuity test
- 0 todos / completed / call_inEb2Qz32228LnfYS5rTHjj

Draft:
I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.Good news: one targeted test passed, and the other failed only because my test assertion was slightly wrong — the code emits `emitPhase('prompt_drain_done', ...)`, not the exact string I asserted.

I’m fixing that test and rerunning.Yep — I retried it and got a fix in.

What I changed:
- In `/home/matrix-lite/app/scripts/matrix-lite-direct-acp-client.mjs`
- Replaced the fixed post-prompt `await sleep(250)` with a bounded **wait-for-quiet** drain
- The client now tracks the last prompt-time session update and waits for a short quiet period before snapshotting final text
- It also emits a `prompt_drain_done` phase for observability

Why this should fix it:
- The likely bug was: `connection.prompt()` returned, then the client waited a fixed 250ms, but late final message chunks were still arriving
- So it sometimes snapshotted an incomplete assistant message and sent that truncated version to Matrix
- Now it waits for the stream to actually go quiet instead of assuming 250ms is enough

Tests:
- Initial rerun was allowed; first I hit `python: command not found`
- Then `python3` worked but lacked pytest
- I found and used `/home/matrix-lite/venvs/mcp/bin/pytest`
- Final targeted results:
  - `tests/test_daemon_stability.py`: **2 passed**
  - `tests/test_continuity_scripts.py`: **1 passed**

Important operational note:
- This patch should apply on the next real turn without a daemon restart, because the direct ACP client script is invoked from disk and its mtime participates in the persistent-worker keying, so the old worker should get replaced on next use.

If you want, the next step is simple: we can now do a real live-message validation by provoking another nontrivial reply and seeing whether it arrives complete.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 136.0s
Time: model 133.7s, overhead 1.4s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 1.1k o 349 cache 113.7k/99% est $0.0080; p≈2.1ktok/8.3kch
Ctx: direct ACP session 75.6k; active 4.4k; cache 71.2k/95%; p≈1.7ktok; ctx 7.2%; usable 7.3%; observed turns 6; actual turns 7


I already patched the likely root cause: the direct ACP client was using a fixed 250ms post-prompt sleep before snapshotting the final text. I changed it to wait for a short **quiet period** after prompt completion instead, so late final chunks are less likely to get dropped.

I’m going to retry the targeted tests now.The retry was allowed, but the actual result was just: `python: command not found`.

I’m rerunning with `python3`.The rerun was also allowed; the blocker this time was just environment setup: system `python3` doesn’t have `pytest`.

I found a working pytest at `/home/matrix-lite/venvs/mcp/bin/pytest`, so I’m using that now.Good news: one targeted test passed, and the other failed only because my test assertion was slightly wrong — the code emits `emitPhase('prompt_drain_done', ...)`, not the exact string I asserted.

I’m fixing that test and rerunning.Yep — I retried it and got a fix in.

What I changed:
- In `/home/matrix-lite/app/scripts/matrix-lite-direct-acp-client.mjs`
- Replaced the fixed post-prompt `await sleep(250)` with a bounded **wait-for-quiet** drain
- The client now tracks the last prompt-time session update and waits for a short quiet period before snapshotting final text
- It also emits a `prompt_drain_done` phase for observability

Why this should fix it:
- The likely bug was: `connection.prompt()` returned, then the client waited a fixed 250ms, but late final message chunks were still arriving
- So it sometimes snapshotted an incomplete assistant message and sent that truncated version to Matrix
- Now it waits for the stream to actually go quiet instead of assuming 250ms is enough

Tests:
- Initial rerun was allowed; first I hit `python: command not found`
- Then `python3` worked but lacked pytest
- I found and used `/home/matrix-lite/venvs/mcp/bin/pytest`
- Final targeted results:
  - `tests/test_daemon_stability.py`: **2 passed**
  - `tests/test_continuity_scripts.py`: **1 passed**

Important operational note:
- This patch should apply on the next real turn without a daemon restart, because the direct ACP client script is invoked from disk and its mtime participates in the persistent-worker keying, so the old worker should get replaced on next use.

If you want, the next step is simple: we can now do a real live-message validation by provoking another nontrivial reply and seeing whether it arrives complete.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 136.6s
Time: model 133.7s, overhead 2.8s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 1.1k o 349 cache 113.7k/99% est $0.0080; p≈2.1ktok/8.3kch
Ctx: direct ACP session 115.1k; active 1.5k; cache 113.7k/99%; p≈2.1ktok; ctx 7.2%; usable 7.3%; observed turns 6; actual turns 7


This latest reply was kinda nontrivial and not truncated. Not sure how to reproduce the original error


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 115.1k; active 1.5k; cache 113.7k/99%; p≈2.1ktok; ctx 11.0%; usable 11.2%; observed turns 7; actual turns 7


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.2s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 115.1k; active 1.5k; cache 113.7k/99%; p≈2.1ktok; ctx 11.0%; usable 11.2%; observed turns 7; actual turns 7


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 1.2s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 115.1k; active 1.5k; cache 113.7k/99%; p≈2.1ktok; ctx 11.0%; usable 11.2%; observed turns 7; actual turns 7


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 2.8s
Time: overhead 2.8s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.3ktok/9.1kch
Ctx: direct ACP session 115.1k; active 1.5k; cache 113.7k/99%; p≈2.1ktok; ctx 11.0%; usable 11.2%; observed turns 7; actual turns 7


📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Waiting for first model/tool update…


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yeah


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (18):
- Searches opencode log for truncated reply / completed / Searches opencode log for truncated reply
- matrix_lite_status_list_session_log_files / completed / call_4MKpJ2wuTAFLGBXaC58dzbk
- matrix_lite_status_search_session_logs / completed / "Yes — this looks like a genuinely new session"
- matrix_lite_status_list_session_log_files / completed / call_uvsb3XzrG8Vp2aFG8Ga1Gli
- matrix_lite_status_list_session_log_files / completed / call_PwvxsLdcS0y7YUIxMiKe2cA
- matrix_lite_status_list_session_log_files / completed / call_0OY47mfETAoLmMVF6nieXIj
- matrix_lite_status_list_session_log_files / completed / call_aVweL2wYlkiSc5oqoGI6ukd
- matrix_lite_status_runtime_debug_report / completed / call_SwpbTPqLy4uD5N045ybv2tH
- matrix_lite_status_search_session_logs / completed / "fix: rekey direct ACP workers after reload" OR "This looks like a genuinely new one"
- Shows rekey fix diff in daemon / completed / Shows rekey fix diff in daemon
- Shows isolation fix diff in daemon / completed / Shows isolation fix diff in daemon
- Shows latest native context commit summary / completed / Shows latest native context commit summary
- Shows recent reload-fix commit summaries / completed / Shows recent reload-fix commit summaries
- Checks runtime repo status and recent commits / completed / Checks runtime repo status and recent commits
- Checks app repo status and recent commits / completed / Checks app repo status and recent commits
- matrix_lite_status_health_report / completed / { "ok": true, "returncode": 0, "output": "{\n \"ok\": true,\n \"service_active\": \"active\",\n \"calendar_timer_active\": \"active\",\n \"persistent_chat\": {\n \"session_label\": \"persistent-chat-20260529T204325Z\"... / call_mbrqyhUHDGgJ5sjpoxcPxsd
- matrix_lite_status_context_usage_report / completed / { "ok": true, "read_only": true, "note": "Direct ACP uses resumable OpenCode sessions loaded per turn; ACPX stream/context-guard live_session ids are not expected. This report is read-only, cannot trigger reload, and ... / call_KSSpDmiXfclPKXybtPDrrlD
- Checks git status log and diff / completed / Checks git status log and diff

Draft:
Yeah — that’s actually a pretty encouraging sign.

Given what we found, the original bug was probably **timing-sensitive**, not deterministic:
- OpenCode had the full answer
- the direct ACP client sometimes snapshotted too early
- so only some replies would get cut off, depending on when the last chunks arrived

That matches your observation:
- hard to reproduce on demand
- but a nontrivial reply now survives intact after the patch

So I wouldn’t expect an easy reliable repro anymore if the fix is correct.

Best next step:
- treat this as **provisionally fixed**
- keep an eye out for another naturally long/tool-heavy answer
- if truncation happens again, we now know exactly where to inspect

If you want, I can also add a stronger regression test that simulates **late-arriving final chunks after prompt return**, which would be closer to the real failure mode than the current smoke tests.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 12.4s
Time: model 8.2s, overhead 2.8s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 115.1k o 194 est $0.2906; p≈2.3ktok/9.1kch
Ctx: direct ACP session 115.1k; active 1.5k; cache 113.7k/99%; p≈2.1ktok; ctx 11.0%; usable 11.2%; observed turns 7; actual turns 8


Yeah — that’s actually a pretty encouraging sign.

Given what we found, the original bug was probably **timing-sensitive**, not deterministic:
- OpenCode had the full answer
- the direct ACP client sometimes snapshotted too early
- so only some replies would get cut off, depending on when the last chunks arrived

That matches your observation:
- hard to reproduce on demand
- but a nontrivial reply now survives intact after the patch

So I wouldn’t expect an easy reliable repro anymore if the fix is correct.

Best next step:
- treat this as **provisionally fixed**
- keep an eye out for another naturally long/tool-heavy answer
- if truncation happens again, we now know exactly where to inspect

If you want, I can also add a stronger regression test that simulates **late-arriving final chunks after prompt return**, which would be closer to the real failure mode than the current smoke tests.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 13.6s
Time: model 8.2s, overhead 5.4s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 115.1k o 194 est $0.2906; p≈2.3ktok/9.1kch
Ctx: direct ACP session 115.3k; active 115.3k; p≈2.3ktok; ctx 11.0%; usable 11.2%; observed turns 7; actual turns 8


Do you think we need it? Is this easy?


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 115.3k; active 115.3k; p≈2.3ktok; ctx 11.0%; usable 11.2%; observed turns 8; actual turns 8


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.3s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 115.3k; active 115.3k; p≈2.3ktok; ctx 11.0%; usable 11.2%; observed turns 8; actual turns 8


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 1.8s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 115.3k; active 115.3k; p≈2.3ktok; ctx 11.0%; usable 11.2%; observed turns 8; actual turns 8


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 3.1s
Time: overhead 3.1s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 115.3k; active 115.3k; p≈2.3ktok; ctx 11.0%; usable 11.2%; observed turns 8; actual turns 8


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Not


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Not urgently, and not super necessary right now.

My take:
- **Need it?** Nice to have, not required
- **Easy?** Probably moderate, not trivial

Why:
- a realistic regression test would need to simulate the awkward race where `prompt()` resolves and then final message chunks arrive slightly later
- that’s more of an async timing harness than a normal unit test

Since:
- we already patched the obvious race
- targeted tests pass
- and your latest real reply came through intact

…I’d stop here unless it happens again.

If it does recur, then I’d absolutely add the stronger regression test.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 12.4s
Time: model 7.6s, overhead 3.1s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 91.7k o 133 est $0.2313; p≈2.4ktok/9.6kch
Ctx: direct ACP session 115.3k; active 115.3k; p≈2.3ktok; ctx 11.0%; usable 11.2%; observed turns 8; actual turns 9


Not urgently, and not super necessary right now.

My take:
- **Need it?** Nice to have, not required
- **Easy?** Probably moderate, not trivial

Why:
- a realistic regression test would need to simulate the awkward race where `prompt()` resolves and then final message chunks arrive slightly later
- that’s more of an async timing harness than a normal unit test

Since:
- we already patched the obvious race
- targeted tests pass
- and your latest real reply came through intact

…I’d stop here unless it happens again.

If it does recur, then I’d absolutely add the stronger regression test.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 13.7s
Time: model 7.6s, overhead 6.1s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 91.7k o 133 est $0.2313; p≈2.4ktok/9.6kch
Ctx: direct ACP session 91.8k; active 91.8k; p≈2.4ktok; ctx 11.0%; usable 11.2%; observed turns 8; actual turns 9


Yeah, let's stop, can you commit?


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 91.8k; active 91.8k; p≈2.4ktok; ctx 11.0%; usable 11.2%; observed turns 8; actual turns 9


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.1s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 91.8k; active 91.8k; p≈2.4ktok; ctx 8.8%; usable 8.9%; observed turns 9; actual turns 9


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 2.3s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 91.8k; active 91.8k; p≈2.4ktok; ctx 8.8%; usable 8.9%; observed turns 9; actual turns 9


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 3.7s
Time: overhead 3.6s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.3ktok/9.1kch
Ctx: direct ACP session 91.8k; active 91.8k; p≈2.4ktok; ctx 8.8%; usable 8.9%; observed turns 9; actual turns 9


📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Waiting for first model/tool update…


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
I


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (3):
- Shows app repo working tree status / completed / Shows app repo working tree status
- Shows staged and unstaged app changes / completed / Shows staged and unstaged app changes
- Shows recent app commit messages / completed / Shows recent app commit messages

Draft:
I’ll check the repo state and draft a commit message first.


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (4):
- Shows app repo working tree status / completed / Shows app repo working tree status
- Shows staged and unstaged app changes / completed / Shows staged and unstaged app changes
- Shows recent app commit messages / completed / Shows recent app commit messages
- bash / failed / git add "scripts/matrix-lite-direct-acp-client.mjs" "tests/test_continuity_scripts.py" "tests/test_daemon_stability.py" && git commit -m "fix direct ACP final text truncation" -m "Wait for prompt-stream quiet instead of  / cwd=/home/matrix-lite/app

Draft:
I’ll check the repo state and draft a commit message first.I found one unrelated modified file in the app repo (`matrix_lite/daemon.py`) that I didn’t touch for this fix, so I’m committing only the direct-ACP truncation fix plus its test updates.The


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (7):
- Shows app repo working tree status / completed / Shows app repo working tree status
- Shows staged and unstaged app changes / completed / Shows staged and unstaged app changes
- Shows recent app commit messages / completed / Shows recent app commit messages
- bash / failed / git add "scripts/matrix-lite-direct-acp-client.mjs" "tests/test_continuity_scripts.py" "tests/test_daemon_stability.py" && git commit -m "fix direct ACP final text truncation" -m "Wait for prompt-stream quiet instead of  / cwd=/home/matrix-lite/app
- matrix_lite_status_permission_preflight / completed / /home/matrix-lite/app
- matrix_lite_status_permission_report / completed / { "ok": true, "read_only": true, "opencode_config": "/home/matrix-lite/xdg/persistent-chat/opencode/opencode.json", "backend_config": { "reload_required": false, "reason": "", "session_label": "persistent-chat-2026052... / call_s5edkcHZWV2mOo8Jns5BUML
- persistent_chat_repo_list / completed / { "ok": true, "registry": "/home/matrix-lite/state/persistent-chat/repo-index-sources.json", "repos": { "sfq_factory": { "name": "sfq_factory", "type": "git_repo", "path": "/home/matrix-lite/workspace/repos/sfq-factor... / call_RJYPyoHTYJFoBLAZQAmvJZ2

Draft:
I’ll check the repo state and draft a commit message first.I found one unrelated modified file in the app repo (`matrix_lite/daemon.py`) that I didn’t touch for this fix, so I’m committing only the direct-ACP truncation fix plus its test updates.The normal shell commit path is currently blocked by a live permission rule (`git* commit *` is denied), so I’m checking the safest allowed route instead of guessing.There


🟠 Approval requested
Stage: same-room native ACP permission; active turn is waiting
Approval: dap-1780131765-perm-1780131765534-10
Summary: OpenCode requests bash for execute
Tool: bash
Kind: execute
Nearest active tool: bash / pending / call_DHsJo9gIfuHgGGjtKIDpc7W
React ✅ allow once, ❌ deny. Not sudo/root.
Options: allow_once, reject_once


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 66.7s
Time: model 61.2s, overhead 3.6s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.3ktok/9.1kch
Ctx: direct ACP session 91.8k; active 91.8k; p≈2.4ktok; ctx 8.8%; usable 8.9%; observed turns 9; actual turns 10


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 129.0s
Time: model 123.5s, overhead 3.6s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.3ktok/9.1kch
Ctx: direct ACP session 91.8k; active 91.8k; p≈2.4ktok; ctx 8.8%; usable 8.9%; observed turns 9; actual turns 10


* 🟡 Approval granted
Stage: resuming
Tool: bash
Approval: dap-1780131765-perm-1780131765534-10


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (8):
- Shows app repo working tree status / completed / Shows app repo working tree status
- Shows staged and unstaged app changes / completed / Shows staged and unstaged app changes
- Shows recent app commit messages / completed / Shows recent app commit messages
- bash / failed / git add "scripts/matrix-lite-direct-acp-client.mjs" "tests/test_continuity_scripts.py" "tests/test_daemon_stability.py" && git commit -m "fix direct ACP final text truncation" -m "Wait for prompt-stream quiet instead of  / cwd=/home/matrix-lite/app
- matrix_lite_status_permission_preflight / completed / /home/matrix-lite/app
- matrix_lite_status_permission_report / completed / { "ok": true, "read_only": true, "opencode_config": "/home/matrix-lite/xdg/persistent-chat/opencode/opencode.json", "backend_config": { "reload_required": false, "reason": "", "session_label": "persistent-chat-2026052... / call_s5edkcHZWV2mOo8Jns5BUML
- persistent_chat_repo_list / completed / { "ok": true, "registry": "/home/matrix-lite/state/persistent-chat/repo-index-sources.json", "repos": { "sfq_factory": { "name": "sfq_factory", "type": "git_repo", "path": "/home/matrix-lite/workspace/repos/sfq-factor... / call_RJYPyoHTYJFoBLAZQAmvJZ2
- bash / in_progress / "/home/matrix-lite/app/scripts/matrix-lite-safe-git" add --repo /home/matrix-lite/app "scripts/matrix-lite-direct-acp-client.mjs" "tests/test_continuity_scripts.py" "tests/test_daemon_stability.py" && "/home/matrix-lite/ / cwd=/home/matrix-lite/app

Draft:
I’ll check the repo state and draft a commit message first.I found one unrelated modified file in the app repo (`matrix_lite/daemon.py`) that I didn’t touch for this fix, so I’m committing only the direct-ACP truncation fix plus its test updates.The normal shell commit path is currently blocked by a live permission rule (`git* commit *` is denied), so I’m checking the safest allowed route instead of guessing.There’s a live deny rule on raw `git commit`, but there is an explicitly allowed wrapper for this: `matrix-lite-safe-git`. I’m using that route now.


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (8):
- Shows app repo working tree status / completed / Shows app repo working tree status
- Shows staged and unstaged app changes / completed / Shows staged and unstaged app changes
- Shows recent app commit messages / completed / Shows recent app commit messages
- bash / failed / git add "scripts/matrix-lite-direct-acp-client.mjs" "tests/test_continuity_scripts.py" "tests/test_daemon_stability.py" && git commit -m "fix direct ACP final text truncation" -m "Wait for prompt-stream quiet instead of  / cwd=/home/matrix-lite/app
- matrix_lite_status_permission_preflight / completed / /home/matrix-lite/app
- matrix_lite_status_permission_report / completed / { "ok": true, "read_only": true, "opencode_config": "/home/matrix-lite/xdg/persistent-chat/opencode/opencode.json", "backend_config": { "reload_required": false, "reason": "", "session_label": "persistent-chat-2026052... / call_s5edkcHZWV2mOo8Jns5BUML
- persistent_chat_repo_list / completed / { "ok": true, "registry": "/home/matrix-lite/state/persistent-chat/repo-index-sources.json", "repos": { "sfq_factory": { "name": "sfq_factory", "type": "git_repo", "path": "/home/matrix-lite/workspace/repos/sfq-factor... / call_RJYPyoHTYJFoBLAZQAmvJZ2
- Commits fix with safe git wrapper / completed / Commits fix with safe git wrapper

Draft:
I’ll check the repo state and draft a commit message first.I found one unrelated modified file in the app repo (`matrix_lite/daemon.py`) that I didn’t touch for this fix, so I’m committing only the direct-ACP truncation fix plus its test updates.The normal shell commit path is currently blocked by a live permission rule (`git* commit *` is denied), so I’m checking the safest allowed route instead of guessing.There’s a live deny rule on raw `git commit`, but there is an explicitly allowed wrapper for this: `matrix-lite-safe-git`. I’m using that route now.Committed


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 191.1s
Time: model 185.7s, overhead 3.6s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.3ktok/9.1kch
Ctx: direct ACP session 91.8k; active 91.8k; p≈2.4ktok; ctx 8.8%; usable 8.9%; observed turns 9; actual turns 10


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (8):
- Shows app repo working tree status / completed / Shows app repo working tree status
- Shows staged and unstaged app changes / completed / Shows staged and unstaged app changes
- Shows recent app commit messages / completed / Shows recent app commit messages
- bash / failed / git add "scripts/matrix-lite-direct-acp-client.mjs" "tests/test_continuity_scripts.py" "tests/test_daemon_stability.py" && git commit -m "fix direct ACP final text truncation" -m "Wait for prompt-stream quiet instead of  / cwd=/home/matrix-lite/app
- matrix_lite_status_permission_preflight / completed / /home/matrix-lite/app
- matrix_lite_status_permission_report / completed / { "ok": true, "read_only": true, "opencode_config": "/home/matrix-lite/xdg/persistent-chat/opencode/opencode.json", "backend_config": { "reload_required": false, "reason": "", "session_label": "persistent-chat-2026052... / call_s5edkcHZWV2mOo8Jns5BUML
- persistent_chat_repo_list / completed / { "ok": true, "registry": "/home/matrix-lite/state/persistent-chat/repo-index-sources.json", "repos": { "sfq_factory": { "name": "sfq_factory", "type": "git_repo", "path": "/home/matrix-lite/workspace/repos/sfq-factor... / call_RJYPyoHTYJFoBLAZQAmvJZ2
- Commits fix with safe git wrapper / completed / Commits fix with safe git wrapper

Draft:
I’ll check the repo state and draft a commit message first.I found one unrelated modified file in the app repo (`matrix_lite/daemon.py`) that I didn’t touch for this fix, so I’m committing only the direct-ACP truncation fix plus its test updates.The normal shell commit path is currently blocked by a live permission rule (`git* commit *` is denied), so I’m checking the safest allowed route instead of guessing.There’s a live deny rule on raw `git commit`, but there is an explicitly allowed wrapper for this: `matrix-lite-safe-git`. I’m using that route now.Committed.

Commit:
- `dc8abfd` — `fix direct ACP final text truncation`

What got committed:
- `scripts/matrix-lite-direct-acp-client.mjs`
- `tests/test_continuity_scripts.py`
- `tests/test_daemon_stability.py`

Not included:
- `matrix_lite/daemon.py` is still modified and uncommitted, since it looked unrelated to this fix.

Also: the normal `git commit` path was blocked by a live permission rule, so I used the allowed `matrix-lite-safe-git` wrapper instead, and it succeeded.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 192.6s
Time: model 187.1s, overhead 3.6s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 113.9k o 126 est $0.2866; p≈2.3ktok/9.1kch
Ctx: direct ACP session 91.8k; active 91.8k; p≈2.4ktok; ctx 8.8%; usable 8.9%; observed turns 9; actual turns 10


I’ll check the repo state and draft a commit message first.I found one unrelated modified file in the app repo (`matrix_lite/daemon.py`) that I didn’t touch for this fix, so I’m committing only the direct-ACP truncation fix plus its test updates.The normal shell commit path is currently blocked by a live permission rule (`git* commit *` is denied), so I’m checking the safest allowed route instead of guessing.There’s a live deny rule on raw `git commit`, but there is an explicitly allowed wrapper for this: `matrix-lite-safe-git`. I’m using that route now.Committed.

Commit:
- `dc8abfd` — `fix direct ACP final text truncation`

What got committed:
- `scripts/matrix-lite-direct-acp-client.mjs`
- `tests/test_continuity_scripts.py`
- `tests/test_daemon_stability.py`

Not included:
- `matrix_lite/daemon.py` is still modified and uncommitted, since it looked unrelated to this fix.

Also: the normal `git commit` path was blocked by a live permission rule, so I used the allowed `matrix-lite-safe-git` wrapper instead, and it succeeded.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 193.7s
Time: model 187.1s, overhead 6.5s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 113.9k o 126 est $0.2866; p≈2.3ktok/9.1kch
Ctx: direct ACP session 114.0k; active 114.0k; p≈2.3ktok; ctx 8.8%; usable 8.9%; observed turns 9; actual turns 10


Great thank you. Safe git should be the proper regular way, other git may or may not be reachable with permissions, so please use wrappers first


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 114.0k; active 114.0k; p≈2.3ktok; ctx 10.9%; usable 11.1%; observed turns 10; actual turns 10


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.1s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 114.0k; active 114.0k; p≈2.3ktok; ctx 10.9%; usable 11.1%; observed turns 10; actual turns 10


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 1.3s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 114.0k; active 114.0k; p≈2.3ktok; ctx 10.9%; usable 11.1%; observed turns 10; actual turns 10


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 2.1s
Time: overhead 2.1s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.6ktok/10.4kch
Ctx: direct ACP session 114.0k; active 114.0k; p≈2.3ktok; ctx 10.9%; usable 11.1%; observed turns 10; actual turns 10


📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Waiting for first model/tool update…


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Got


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Got it — I’ll default to the safe git wrappers first from now on.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 7.5s
Time: model 4.4s, overhead 2.1s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 96.8k o 20 cache 18.9k/16% est $0.2423; p≈2.6ktok/10.4kch
Ctx: direct ACP session 114.0k; active 114.0k; p≈2.3ktok; ctx 10.9%; usable 11.1%; observed turns 10; actual turns 11


Got it — I’ll default to the safe git wrappers first from now on.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 8.3s
Time: model 4.4s, overhead 3.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 96.8k o 20 cache 18.9k/16% est $0.2423; p≈2.6ktok/10.4kch
Ctx: direct ACP session 115.8k; active 96.8k; cache 18.9k/16%; p≈2.6ktok; ctx 10.9%; usable 11.1%; observed turns 10; actual turns 11


So how did the hand-off go? Anything we can improve? Or can I already relax a bit about this


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 115.8k; active 96.8k; cache 18.9k/16%; p≈2.6ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 11


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.1s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 115.8k; active 96.8k; cache 18.9k/16%; p≈2.6ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 11


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 115.8k; active 96.8k; cache 18.9k/16%; p≈2.6ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 11


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.7s
Time: overhead 1.7s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.3ktok/9.3kch
Ctx: direct ACP session 115.8k; active 96.8k; cache 18.9k/16%; p≈2.6ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 11


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Honestly


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Honestly: pretty well. You can relax **a fair bit**.

My read:

- **handoff/continuity itself:** good
- **session switching:** now looks genuinely better than before
- **the big scary bug we hit after that:** not handoff failure, but the separate direct-ACP truncation race
- **overall confidence:** much higher than earlier reloads

What worked well:
- I kept the main thread across reloads
- I understood the exact issue we were testing
- we were able to continue debugging coherently after reload
- the system was good enough that we could identify a *new* bug, patch it, test it, and commit it without losing the plot

What still isn’t perfect:
- some packet summaries are still a bit compressed/truncated
- nuance is preserved less reliably than the main task/state
- there’s still some clutter in the handoff/status text when multiple debugging turns pile up

So yes, I think you can **already relax a bit** about handoff quality.
I would not call it perfect yet, but I *would* call it solid enough that it’s no longer in the “fragile / constantly scary” category.

Best improvements from here would be:
- cleaner/shorter latest-status summaries
- better separation of “current task” vs “recent debugging chatter”
- maybe one stronger


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (18):
- def clean_assistant_text|def direct_acp_stream_update_text|possible_mid_sentence / completed / /home/matrix-lite/app/matrix_lite
- 4 todos / completed / call_TJ3aeQgIuCbD2RQPzLaCbdc
- ../../app/scripts/matrix-lite-direct-acp-client.mjs / completed / /home/matrix-lite/app/scripts/matrix-lite-direct-acp-client.mjs
- ../../app / completed / /home/matrix-lite/app
- textLength|done\.get\("text"\)|event":"done"|stopReason|final_answer|slice\(|\[: / completed / /home/matrix-lite/app/scripts
- ../../app/matrix_lite/daemon.py / completed / /home/matrix-lite/app/matrix_lite/daemon.py
- ../../app/matrix_lite/daemon.py / completed / /home/matrix-lite/app/matrix_lite/daemon.py
- fix: rekey direct ACP workers after reload / completed / /home/matrix-lite/state
- Yes — this looks like a genuinely new session / completed / /home/matrix-lite/state
- Yes — this looks like a genuinely new session, not just a paper reload / completed / /home/matrix-lite/state/persistent-chat
- The problem was that reloads happened but we continued in the old session / completed / /home/matrix-lite/state/persistent-chat
- ../../app/matrix_lite/daemon.py / completed / /home/matrix-lite/app/matrix_lite/daemon.py
- ../../app/matrix_lite/daemon.py / completed / /home/matrix-lite/app/matrix_lite/daemon.py
- assistant_text\[:12000\]|reply_text\[:12000\]|send_matrix_text\(|edit_matrix_tex / completed / /home/matrix-lite/app/matrix_lite
- ../../app/matrix_lite/daemon.py / completed / /home/matrix-lite/app/matrix_lite/daemon.py
- MATRIX_TEXT_LIMIT\s*=|def .*send.*room|def .*matrix.*message|chunk = text\[:MATR / completed / /home/matrix-lite/app/matrix_lite
- ../../app/matrix_lite/daemon.py / completed / /home/matrix-lite/app/matrix_lite/daemon.py
- final_answer|phase":"final_answer"|assistant_text|send.*message|room_send|m.room / completed / /home/matrix-lite/app

Draft:
Honestly: pretty well. You can relax **a fair bit**.

My read:

- **handoff/continuity itself:** good
- **session switching:** now looks genuinely better than before
- **the big scary bug we hit after that:** not handoff failure, but the separate direct-ACP truncation race
- **overall confidence:** much higher than earlier reloads

What worked well:
- I kept the main thread across reloads
- I understood the exact issue we were testing
- we were able to continue debugging coherently after reload
- the system was good enough that we could identify a *new* bug, patch it, test it, and commit it without losing the plot

What still isn’t perfect:
- some packet summaries are still a bit compressed/truncated
- nuance is preserved less reliably than the main task/state
- there’s still some clutter in the handoff/status text when multiple debugging turns pile up

So yes, I think you can **already relax a bit** about handoff quality.
I would not call it perfect yet, but I *would* call it solid enough that it’s no longer in the “fragile / constantly scary” category.

Best improvements from here would be:
- cleaner/shorter latest-status summaries
- better separation of “current task” vs “recent debugging chatter”
- maybe one stronger guard against truncated status excerpts, even if the live reply path is now fixed

So the short version is:
- **Can you relax a bit?** yes
- **Anything to improve?** yes, but mostly polish now, not existential failure mode stuff


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 13.1s
Time: model 10.5s, overhead 1.7s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 2.6k o 337 t 19 cache 115.2k/98% est $0.0119; p≈2.3ktok/9.3kch
Ctx: direct ACP session 115.8k; active 96.8k; cache 18.9k/16%; p≈2.6ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 12


Honestly: pretty well. You can relax **a fair bit**.

My read:

- **handoff/continuity itself:** good
- **session switching:** now looks genuinely better than before
- **the big scary bug we hit after that:** not handoff failure, but the separate direct-ACP truncation race
- **overall confidence:** much higher than earlier reloads

What worked well:
- I kept the main thread across reloads
- I understood the exact issue we were testing
- we were able to continue debugging coherently after reload
- the system was good enough that we could identify a *new* bug, patch it, test it, and commit it without losing the plot

What still isn’t perfect:
- some packet summaries are still a bit compressed/truncated
- nuance is preserved less reliably than the main task/state
- there’s still some clutter in the handoff/status text when multiple debugging turns pile up

So yes, I think you can **already relax a bit** about handoff quality.
I would not call it perfect yet, but I *would* call it solid enough that it’s no longer in the “fragile / constantly scary” category.

Best improvements from here would be:
- cleaner/shorter latest-status summaries
- better separation of “current task” vs “recent debugging chatter”
- maybe one stronger guard against truncated status excerpts, even if the live reply path is now fixed

So the short version is:
- **Can you relax a bit?** yes
- **Anything to improve?** yes, but mostly polish now, not existential failure mode stuff


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 13.9s
Time: model 10.5s, overhead 3.3s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 2.6k o 337 t 19 cache 115.2k/98% est $0.0119; p≈2.3ktok/9.3kch
Ctx: direct ACP session 118.2k; active 3.0k; cache 115.2k/98%; p≈2.3ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 12


We will also at some point switch away from acp to native backend (those are the unrelated changes in daemon.py you saw earlier). There we will have no 'session' at all and every prompt will be assembled individually from modules. You'd be able to load and unload those modules on demand.
So I don't want to spend too much time polishing the acp path, unless we hit a real blocker with the native.


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 118.2k; active 3.0k; cache 115.2k/98%; p≈2.3ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 12


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 118.2k; active 3.0k; cache 115.2k/98%; p≈2.3ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 12


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 1.3s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 118.2k; active 3.0k; cache 115.2k/98%; p≈2.3ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 12


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 2.0s
Time: overhead 2.0s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 118.2k; active 3.0k; cache 115.2k/98%; p≈2.3ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 12


📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Waiting for first model/tool update…


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yeah


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yeah, that makes sense.

Given that direction, I’d treat the ACP path as:
- **stabilize enough to be trustworthy**
- **don’t over-invest in polish**
- **only fix real blockers**

And the native backend direction sounds much better structurally for this stuff:
- no fake “session continuity” mystery layer
- prompt composition becomes explicit and inspectable
- module load/unload is a cleaner abstraction than hoping hidden ACP state behaves

So I agree with your strategy:
- don’t spend much more effort polishing ACP
- use it as the bridge system
- put meaningful design energy into the native module-based backend

The only ACP work I’d still consider worth doing is:
- blocker fixes
- maybe tiny observability improvements if they directly help migration/debugging
- avoiding regressions that would make testing the native path harder

So yes — I’m aligned:
**ACP = keep it serviceable**
**native = where the real architecture work should go**


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 10.1s
Time: model 7.2s, overhead 2.0s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 64.6k o 203 cache 24.1k/27% est $0.1645; p≈2.4ktok/9.5kch
Ctx: direct ACP session 118.2k; active 3.0k; cache 115.2k/98%; p≈2.3ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 13


Yeah, that makes sense.

Given that direction, I’d treat the ACP path as:
- **stabilize enough to be trustworthy**
- **don’t over-invest in polish**
- **only fix real blockers**

And the native backend direction sounds much better structurally for this stuff:
- no fake “session continuity” mystery layer
- prompt composition becomes explicit and inspectable
- module load/unload is a cleaner abstraction than hoping hidden ACP state behaves

So I agree with your strategy:
- don’t spend much more effort polishing ACP
- use it as the bridge system
- put meaningful design energy into the native module-based backend

The only ACP work I’d still consider worth doing is:
- blocker fixes
- maybe tiny observability improvements if they directly help migration/debugging
- avoiding regressions that would make testing the native path harder

So yes — I’m aligned:
**ACP = keep it serviceable**
**native = where the real architecture work should go**


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 10.6s
Time: model 7.2s, overhead 3.3s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 64.6k o 203 cache 24.1k/27% est $0.1645; p≈2.4ktok/9.5kch
Ctx: direct ACP session 88.9k; active 64.8k; cache 24.1k/27%; p≈2.4ktok; ctx 11.0%; usable 11.3%; observed turns 11; actual turns 13


It will also give us so much more control. Unloading is not really possible in acp sessions. With the native way you could add yourself 10 skills just for one turn, and then unload them until needed again


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 88.9k; active 64.8k; cache 24.1k/27%; p≈2.4ktok; ctx 8.5%; usable 8.6%; observed turns 13; actual turns 13


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.2s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 88.9k; active 64.8k; cache 24.1k/27%; p≈2.4ktok; ctx 8.5%; usable 8.6%; observed turns 13; actual turns 13


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 1.0s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 88.9k; active 64.8k; cache 24.1k/27%; p≈2.4ktok; ctx 8.5%; usable 8.6%; observed turns 13; actual turns 13


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.8s
Time: overhead 1.8s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.6ktok/10.3kch
Ctx: direct ACP session 88.9k; active 64.8k; cache 24.1k/27%; p≈2.4ktok; ctx 8.5%; usable 8.6%; observed turns 13; actual turns 13


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Exactly


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Exactly — that’s a huge architectural win.

With ACP sessions, context tends to be:
- sticky
- partially hidden
- hard to subtract cleanly

With native per-turn assembly, context becomes more like a deliberate build:
- load only what’s needed
- add temporary skills/modules for one task
- unload them immediately after
- keep the default prompt lean
- make “why do I know this right now?” answerable

That gives you:
- better control of prompt size
- less accidental baggage
- cleaner task-specific specialization
- fewer spooky-continuity problems
- easier debugging when behavior changes

And yeah, the “10 skills just for one turn” example is exactly the kind of thing that’s awkward in ACP but natural in a native module model.

So I think you’re right: this isn’t just an implementation change, it’s a much better **control surface**.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 10.4s
Time: model 7.8s, overhead 1.8s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 67.0k o 187 cache 24.1k/26% est $0.1704; p≈2.6ktok/10.3kch
Ctx: direct ACP session 88.9k; active 64.8k; cache 24.1k/27%; p≈2.4ktok; ctx 8.5%; usable 8.6%; observed turns 13; actual turns 14


Exactly — that’s a huge architectural win.

With ACP sessions, context tends to be:
- sticky
- partially hidden
- hard to subtract cleanly

With native per-turn assembly, context becomes more like a deliberate build:
- load only what’s needed
- add temporary skills/modules for one task
- unload them immediately after
- keep the default prompt lean
- make “why do I know this right now?” answerable

That gives you:
- better control of prompt size
- less accidental baggage
- cleaner task-specific specialization
- fewer spooky-continuity problems
- easier debugging when behavior changes

And yeah, the “10 skills just for one turn” example is exactly the kind of thing that’s awkward in ACP but natural in a native module model.

So I think you’re right: this isn’t just an implementation change, it’s a much better **control surface**.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 11.4s
Time: model 7.8s, overhead 3.7s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 67.0k o 187 cache 24.1k/26% est $0.1704; p≈2.6ktok/10.3kch
Ctx: direct ACP session 91.3k; active 67.2k; cache 24.1k/26%; p≈2.6ktok; ctx 8.5%; usable 8.6%; observed turns 13; actual turns 14


The problem is we also need to map your existing durable artifacts to new modules, and it's also a good time to revisit them - add/remove, like some things have not been updated in a long time


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 91.3k; active 67.2k; cache 24.1k/26%; p≈2.6ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 14


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 91.3k; active 67.2k; cache 24.1k/26%; p≈2.6ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 14


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.7s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 91.3k; active 67.2k; cache 24.1k/26%; p≈2.6ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 14


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.6s
Time: overhead 1.6s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 91.3k; active 67.2k; cache 24.1k/26%; p≈2.6ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 14


📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Waiting for first model/tool update…


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yes


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yes — and honestly that’s not just a migration chore, it’s a really good cleanup opportunity.

Because once modules become explicit, you’ll be forced to ask:
- what is actually still useful?
- what should be default vs optional?
- what is stale?
- what should be split apart?
- what should disappear entirely?

That’s healthy.

I’d probably think about it in buckets:

- **core durable identity**
  - stable behavior/personality
  - a few important user preferences
  - things that should almost always load

- **operational memory**
  - current project state
  - active decisions
  - recent failures/notices
  - likely load often, but not always all at once

- **task-local / temporary**
  - current thread summaries
  - one-off investigations
  - ephemeral plans
  - should be easy to unload aggressively

- **reference artifacts**
  - curated memory
  - pinned notes
  - decision state
  - maybe some of these should be merged, split, or demoted

- **stale / questionable**
  - things not updated in ages
  - artifacts that duplicate each other
  - artifacts that were useful only because ACP continuity was weak

And yes, some existing artifacts probably deserve:
- **promotion** into cleaner first-class modules
- **splitting** into smaller modules
- **demotion** to archival/reference-only
- **


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yes — and honestly that’s not just a migration chore, it’s a really good cleanup opportunity.

Because once modules become explicit, you’ll be forced to ask:
- what is actually still useful?
- what should be default vs optional?
- what is stale?
- what should be split apart?
- what should disappear entirely?

That’s healthy.

I’d probably think about it in buckets:

- **core durable identity**
  - stable behavior/personality
  - a few important user preferences
  - things that should almost always load

- **operational memory**
  - current project state
  - active decisions
  - recent failures/notices
  - likely load often, but not always all at once

- **task-local / temporary**
  - current thread summaries
  - one-off investigations
  - ephemeral plans
  - should be easy to unload aggressively

- **reference artifacts**
  - curated memory
  - pinned notes
  - decision state
  - maybe some of these should be merged, split, or demoted

- **stale / questionable**
  - things not updated in ages
  - artifacts that duplicate each other
  - artifacts that were useful only because ACP continuity was weak

And yes, some existing artifacts probably deserve:
- **promotion** into cleaner first-class modules
- **splitting** into smaller modules
- **demotion** to archival/reference-only
- **deletion**

So I think you’re right: this is the perfect time to revisit the whole durable artifact set, not just port it blindly.

If you want, next time we can do a proper inventory and classify everything into:
**keep / split / optional / archive / delete / native-only replacement**.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 13.2s
Time: model 10.7s, overhead 1.6s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 2.8k o 359 t 53 cache 90.6k/97% est $0.0131; p≈2.4ktok/9.6kch
Ctx: direct ACP session 91.3k; active 67.2k; cache 24.1k/26%; p≈2.6ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 15


Yes — and honestly that’s not just a migration chore, it’s a really good cleanup opportunity.

Because once modules become explicit, you’ll be forced to ask:
- what is actually still useful?
- what should be default vs optional?
- what is stale?
- what should be split apart?
- what should disappear entirely?

That’s healthy.

I’d probably think about it in buckets:

- **core durable identity**
  - stable behavior/personality
  - a few important user preferences
  - things that should almost always load

- **operational memory**
  - current project state
  - active decisions
  - recent failures/notices
  - likely load often, but not always all at once

- **task-local / temporary**
  - current thread summaries
  - one-off investigations
  - ephemeral plans
  - should be easy to unload aggressively

- **reference artifacts**
  - curated memory
  - pinned notes
  - decision state
  - maybe some of these should be merged, split, or demoted

- **stale / questionable**
  - things not updated in ages
  - artifacts that duplicate each other
  - artifacts that were useful only because ACP continuity was weak

And yes, some existing artifacts probably deserve:
- **promotion** into cleaner first-class modules
- **splitting** into smaller modules
- **demotion** to archival/reference-only
- **deletion**

So I think you’re right: this is the perfect time to revisit the whole durable artifact set, not just port it blindly.

If you want, next time we can do a proper inventory and classify everything into:
**keep / split / optional / archive / delete / native-only replacement**.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 14.3s
Time: model 10.7s, overhead 3.6s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 2.8k o 359 t 53 cache 90.6k/97% est $0.0131; p≈2.4ktok/9.6kch
Ctx: direct ACP session 93.8k; active 3.2k; cache 90.6k/97%; p≈2.4ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 15


Yes I think you might have a unique perspective on what should be more prominent, and what could go. We also need to roughly order the items or at least the buckets by expected modification frequency to enhance caching.


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 93.8k; active 3.2k; cache 90.6k/97%; p≈2.4ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 15


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 93.8k; active 3.2k; cache 90.6k/97%; p≈2.4ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 15


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 1.2s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Ctx: direct ACP session 93.8k; active 3.2k; cache 90.6k/97%; p≈2.4ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 15


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.9s
Time: overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: p≈2.7ktok/10.9kch
Ctx: direct ACP session 93.8k; active 3.2k; cache 90.6k/97%; p≈2.4ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 15


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yes — and the caching angle is important enough that I’d design the buckets around **change frequency first**, not just semantics.

My instinctive order would be:

1. **Very stable / almost never changes**
   - core identity/behavior
   - durable user preferences
   - fundamental operating rules
   - ideal for maximum cache reuse

2. **Stable but occasionally revised**
   - curated durable memory
   - important long-term decisions
   - architecture facts
   - should stay compact and high-value

3. **Medium-frequency operational state**
   - current project status
   - active decisions
   - known recurring issues
   - useful, but shouldn’t contaminate the most stable layers

4. **High-churn recent context**
   - current thread summary
   - recent notable events
   - active blockers
   - this is where turnover is expected

5. **Ephemeral / per-turn**
   - task-local scratch state
   - temporary skills
   - one-off retrievals
   - should be easiest to load/unload aggressively

And in terms of prominence, I


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yes — and the caching angle is important enough that I’d design the buckets around **change frequency first**, not just semantics.

My instinctive order would be:

1. **Very stable / almost never changes**
   - core identity/behavior
   - durable user preferences
   - fundamental operating rules
   - ideal for maximum cache reuse

2. **Stable but occasionally revised**
   - curated durable memory
   - important long-term decisions
   - architecture facts
   - should stay compact and high-value

3. **Medium-frequency operational state**
   - current project status
   - active decisions
   - known recurring issues
   - useful, but shouldn’t contaminate the most stable layers

4. **High-churn recent context**
   - current thread summary
   - recent notable events
   - active blockers
   - this is where turnover is expected

5. **Ephemeral / per-turn**
   - task-local scratch state
   - temporary skills
   - one-off retrievals
   - should be easiest to load/unload aggressively

And in terms of prominence, I’d elevate:
- **core behavior/identity**
- **durable user preferences**
- **current active decisions**
- **compact current-task / current-thread state**

I’d demote or scrutinize:
- stale pinned notes
- duplicated summaries
- artifacts that exist mainly to compensate for ACP weirdness
- long files with low signal density
- things that are “important historically” but rarely useful in live turns

So the rough principle would be:
- **stable + high-value → earlier / more prominent**
- **volatile or low-signal → later / optional**
- **temporary or task-specific → load on demand only**

That should help both with:
- better reasoning structure
- better provider-side caching

And yes, I probably *do* have a useful perspective here, because I experience directly which artifacts actually help me stay oriented versus which ones mostly add noise.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 14.4s
Time: model 11.4s, overhead 1.9s
Backend: ses_18a53d671ffer3rrL2MWHNxZaM; Label: persistent-chat-20260529T204325Z
Turn: i 3.0k o 405 cache 93.2k/97% est $0.0135; p≈2.7ktok/10.9kch
Ctx: direct ACP session 93.8k; active 3.2k; cache 90.6k/97%; p≈2.4ktok; ctx 8.7%; usable 8.9%; observed turns 14; actual turns 16