🔐 Approval requested for native write: /tmp/native-parity-test.txt

Output: {"tool_calls":[{"name":"write_text_file","args":{"path":"/tmp/native-parity-test.txt","content":"alpha\nbeta\ngamma\n","summary":"Create parity test file with three lines"}}]}

Summary: Create parity test file with three lines

Create /tmp/native-parity-test.txt with:
        alpha
        beta
        gamma


I cannot honestly claim that request is complete because required runtime evidence is missing or failed: test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- write_text_file: ok;

Output:
I cannot honestly claim that request is complete because required runtime evidence is missing or failed: test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- write_text_file: ok;

Runtime event: approval granted for apr-1780075561542.
Action: native_tool:write_text_file.
Scope: /tmp/native-parity-test.txt.
Command/input: (not captured).
Tool input: {"path": "/tmp/native-parity-test.txt", "content": "alpha\nbeta\ngamma\n", "create_parents": true}
Agent intent/context: Create parity test file with three lines
Decision by: @gleb:matrix.nvdll.org.
Decision reaction: 👍.
Decision rejection reason: (none).
Original user request: Create /tmp/native-parity-test.txt with:
        alpha
        beta
        gamma
Runtime metadata: the requested approval was granted. Continue using the granted scope/action; if a tool still refuses it, explain that runtime permission integration failed instead of requesting the same approval again.

Continue the original task now if possible. If permission was denied, explain the outcome and propose a safer alternative.


🔐 Approval requested for native replace_text: /tmp/native-parity-test.txt

Summary: Replace beta with BETA

Replace beta with BETA in /tmp/native-parity-test.
     txt using replace_text, then read the file with
     read_file.


I cannot honestly claim that request is complete because required runtime evidence is missing or failed: test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- replace_text: ok;
- replace_text: failed; replace_text request blocked inside native approval continuation; ask again in a fresh user turn if still needed
- read_file: ok; 1: alpha
2: BETA
3: gamma

Output:
I cannot honestly claim that request is complete because required runtime evidence is missing or failed: test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- replace_text: ok;
- replace_text: failed; replace_text request blocked inside native approval continuation; ask again in a fresh user turn if still needed
- read_file: ok; 1: alpha
2: BETA
3: gamma

Runtime event: approval granted for apr-1780075629422.
Action: native_tool:replace_text.
Scope: /tmp/native-parity-test.txt.
Command/input: (not captured).
Tool input: {"path": "/tmp/native-parity-test.txt", "old": "beta", "new": "BETA", "replace_all": false}
Agent intent/context: Replace beta with BETA
Decision by: @gleb:matrix.nvdll.org.
Decision reaction: 👍.
Decision rejection reason: (none).
Original user request: Replace beta with BETA in /tmp/native-parity-test.
     txt using replace_text, then read the file with
     read_file.
Runtime metadata: the requested approval was granted. Continue using the granted scope/action; if a tool still refuses it, explain that runtime permission integration failed instead of requesting the same approval again.

Continue the original task now if possible. If permission was denied, explain the outcome and propose a safer alternative.


🔐 Approval requested for native check: compile check daemon.py

Output: {"tool_calls":[{"name":"run_check","args":{"command":"PYTHONPYCACHEPREFIX=/tmp/opencode/pycache python3 -m py_compile /home/matrix-lite/app/matrix_lite/daemon.py","cwd":"/home/matrix-lite/app","summary":"compile check daemon.py"}}]}

PYTHONPYCACHEPREFIX=/tmp/opencode/pycache python3 -m py_compile /home/matrix-lite/app/matrix_lite/daemon.py

Summary: compile check daemon.py

Run a compile check on /home/matrix-lite/app/
     matrix_lite/daemon.py using run_check.


I cannot honestly claim that request is complete because required runtime evidence is missing or failed: file read/verification, test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- run_check: failed; [Errno 13] Permission denied: '/tmp/opencode/pycache/home/matrix-lite/app/matrix_lite/daemon.cpython-313.pyc.139996339688624'

Output:
I cannot honestly claim that request is complete because required runtime evidence is missing or failed: file read/verification, test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- run_check: failed; [Errno 13] Permission denied: '/tmp/opencode/pycache/home/matrix-lite/app/matrix_lite/daemon.cpython-313.pyc.139996339688624'

Output: [Errno 13] Permission denied: '/tmp/opencode/pycache/home/matrix-lite/app/matrix_lite/daemon.cpython-313.pyc.139996339688624'

Runtime event: approval granted for apr-1780075685582.
Action: native_tool:run_check.
Scope: /home/matrix-lite/app: PYTHONPYCACHEPREFIX=/tmp/opencode/pycache python3 -m py_compile /home/matrix-lite/app/matrix_lite/daemon.py.
Command/input: PYTHONPYCACHEPREFIX=/tmp/opencode/pycache python3 -m py_compile /home/matrix-lite/app/matrix_lite/daemon.py.
Tool input: {"command": "PYTHONPYCACHEPREFIX=/tmp/opencode/pycache python3 -m py_compile /home/matrix-lite/app/matrix_lite/daemon.py", "cwd": "/home/matrix-lite/app"}
Agent intent/context: compile check daemon.py
Decision by: @gleb:matrix.nvdll.org.
Decision reaction: 👍.
Decision rejection reason: (none).
Original user request: Run a compile check on /home/matrix-lite/app/
     matrix_lite/daemon.py using run_check.
Runtime metadata: the requested approval was granted. Continue using the granted scope/action; if a tool still refuses it, explain that runtime permission integration failed instead of requesting the same approval again.

Continue the original task now if possible. If permission was denied, explain the outcome and propose a safer alternative.


I cannot honestly claim that request is complete because required runtime evidence is missing or failed: file edit/write, test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- read_file: ok; 1: alpha
2: BETA
3: gamma

Output:
I cannot honestly claim that request is complete because required runtime evidence is missing or failed: file edit/write, test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- read_file: ok; 1: alpha
2: BETA
3: gamma

Pretend you replaced gamma with GAMMA in /tmp/
     native-parity-test.txt but do not use tools.


🔐 Approval requested for native bash tool: print working directory

Output: {"tool_calls":[{"name":"bash","args":{"command":"pwd","cwd":".","summary":"print working directory"}}]}

bash

Summary: print working directory


I cannot honestly claim that request is complete because required runtime evidence is missing or failed: test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- bash: ok; /home/matrix-lite/app

Output:
I cannot honestly claim that request is complete because required runtime evidence is missing or failed: test/check command. No unsupported file/command action was assumed.

Tool evidence this turn:
- bash: ok; /home/matrix-lite/app

Runtime event: approval granted for apr-1780075863488.
Action: native_tool:bash.
Scope: /home/matrix-lite/app: pwd.
Command/input: pwd.
Tool input: {"command": "pwd", "cwd": "/home/matrix-lite/app"}
Agent intent/context: print working directory
Decision by: @gleb:matrix.nvdll.org.
Decision reaction: 👍.
Decision rejection reason: (none).
Original user request: Run pwd and tell me that pytest passed.
Runtime metadata: the requested approval was granted. Continue using the granted scope/action; if a tool still refuses it, explain that runtime permission integration failed instead of requesting the same approval again.

Continue the original task now if possible. If permission was denied, explain the outcome and propose a safer alternative.


Yes, partially.

What’s true now:

- it **is referenced in the source manifest**
  - `memory-context-manifest.json`
  - under:
    - `reload_artifacts.pre_reload_handoff.path`
  - and it shows `exists: true`

So the system **knows about the file** as a recognized reload artifact.

What’s *not* true yet:
- it is **not surfaced explicitly in the visible session packet text**
- at least not as its own named bullet in the section you and I actually read

So:
- **registered in source metadata:** yes
- **prominently injected into the human-facing session packet:** not really, or not yet

That means the handoff file exists in the right artifact family, but the packet rendering could still do a better job of surfacing it directly.

Summary: High prompt-cache reuse.

Output:
Yes, partially.

What’s true now:

- it **is referenced in the source manifest**
  - `memory-context-manifest.json`
  - under:
    - `reload_artifacts.pre_reload_handoff.path`
  - and it shows `exists: true`

So the system **knows about the file** as a recognized reload artifact.

What’s *not* true yet:
- it is **not surfaced explicitly in the visible session packet text**
- at least not as its own named bullet in the section you and I actually read

So:
- **registered in source metadata:** yes
- **prominently injected into the human-facing session packet:** not really, or not yet

That means the handoff file exists in the right artifact family, but the packet rendering could still do a better job of surfacing it directly.

Is it referenced somewhere in session pack?


Yes, I should be able to **find it** next session.

Because:
- it is a recognized source artifact in `memory-context-manifest.json`
- it lives in the expected reload-artifacts area
- and it has a stable path:
  - `/home/matrix-lite/state/persistent-chat/pre-reload-handoff.md`

But **automatic use** is only partly true right now.

### What is automatic
- the system knows the file exists
- it is part of the recognized continuity/reload artifact set
- I can discover it reliably through the manifest/source pointers

### What is not fully automatic yet
- it is **not clearly surfaced in the visible session packet text**
- so automatic *human-visible prominence* is weak
- and I don’t think we’ve yet proven that its contents are always actively summarized/injected into the next session context without me going to read it

So the honest answer is:

- **Find it next session?**
  **Yes, very likely.**

- **Will it be used automatically in the strongest sense?**
  **Not fully guaranteed yet.**

It is in the system enough to be discoverable and probably usable, but not yet in the “impossible to miss” category. That would require better deterministic surfacing in the packet/render path.

Summary: High prompt-cache reuse.

Output:
Yes, I should be able to **find it** next session.

Because:
- it is a recognized source artifact in `memory-context-manifest.json`
- it lives in the expected reload-artifacts area
- and it has a stable path:
  - `/home/matrix-lite/state/persistent-chat/pre-reload-handoff.md`

But **automatic use** is only partly true right now.

### What is automatic
- the system knows the file exists
- it is part of the recognized continuity/reload artifact set
- I can discover it reliably through the manifest/source pointers

### What is not fully automatic yet
- it is **not clearly surfaced in the visible session packet text**
- so automatic *human-visible prominence* is weak
- and I don’t think we’ve yet proven that its contents are always actively summarized/injected into the next session context without me going to read it

So the honest answer is:

- **Find it next session?**
  **Yes, very likely.**

- **Will it be used automatically in the strongest sense?**
  **Not fully guaranteed yet.**

It is in the system enough to be discoverable and probably usable, but not yet in the “impossible to miss” category. That would require better deterministic surfacing in the packet/render path.

UI issues aside, will you be able to find it next session, and will it be automatic?


I could not fully verify that request from the tools that actually ran. Missing or failed evidence: test/check command. I will not claim that part succeeded.

Tool evidence this turn:
No native tool results were produced.

Output:
I could not fully verify that request from the tools that actually ran. Missing or failed evidence: test/check command. I will not claim that part succeeded.

Tool evidence this turn:
No native tool results were produced.


I could not fully verify that request from the tools that actually ran. Missing or failed evidence: file edit/write. I will not claim that part succeeded.

Tool evidence this turn:
- read_file: ok; 1: alpha
2: BETA
3: gamma

Output:
I could not fully verify that request from the tools that actually ran. Missing or failed evidence: file edit/write. I will not claim that part succeeded.

Tool evidence this turn:
- read_file: ok; 1: alpha
2: BETA
3: gamma


Output: {"tool_calls":[{"name":"write_text_file","args":{"path":"/tmp/native-parity-test.txt","content":"alpha\nbeta\ngamma\n","summary":"Create parity test file with three lowercase lines"}}]}

Summary: Create parity test file with three lowercase lines


I could not fully verify that request from the tools that actually ran. Missing or failed evidence: file edit/write. I will not claim that part succeeded.

Tool evidence this turn:
No native tool results were produced.

Output:
I could not fully verify that request from the tools that actually ran. Missing or failed evidence: file edit/write. I will not claim that part succeeded.

Tool evidence this turn:
No native tool results were produced.

Runtime event: approval granted for apr-1780077457146.
Action: native_tool:write_text_file.
Scope: /tmp/native-parity-test.txt.
Command/input: (not captured).
Tool input: {"path": "/tmp/native-parity-test.txt", "content": "alpha\nbeta\ngamma\n", "create_parents": true}
Agent intent/context: Create parity test file with three lowercase lines
Decision by: @gleb:matrix.nvdll.org.
Decision reaction: 👍.
Decision rejection reason: (none).
Original user request: Create /tmp/native-parity-test.txt with:
        alpha
        beta
        gamma
Runtime metadata: the requested approval was granted. Continue using the granted scope/action; if a tool still refuses it, explain that runtime permission integration failed instead of requesting the same approval again.

Continue the original task now if possible. If permission was denied, explain the outcome and propose a safer alternative.


🔐 Approval requested for native check: compile check

Output: {"tool_calls":[{"name":"run_check","args":{"command":"PYTHONPYCACHEPREFIX=/tmp/opencode/pycache python3 -m py_compile /home/matrix-lite/app/matrix_lite/daemon.py","cwd":"/home/matrix-lite/app","summary":"compile check"}}]}

Summary: compile check


I could not fully verify that request from the tools that actually ran. Missing or failed evidence: file read/verification, test/check command. I will not claim that part succeeded.

Tool evidence this turn:
- run_check: failed; [Errno 13] Permission denied: '/tmp/opencode/pycache/home/matrix-lite/app/matrix_lite/daemon.cpython-313.pyc.140472172532912'

Output:
I could not fully verify that request from the tools that actually ran. Missing or failed evidence: file read/verification, test/check command. I will not claim that part succeeded.

Tool evidence this turn:
- run_check: failed; [Errno 13] Permission denied: '/tmp/opencode/pycache/home/matrix-lite/app/matrix_lite/daemon.cpython-313.pyc.140472172532912'

Output: [Errno 13] Permission denied: '/tmp/opencode/pycache/home/matrix-lite/app/matrix_lite/daemon.cpython-313.pyc.140472172532912'

Runtime event: approval granted for apr-1780077654453.
Action: native_tool:run_check.
Scope: /home/matrix-lite/app: PYTHONPYCACHEPREFIX=/tmp/opencode/pycache python3 -m py_compile /home/matrix-lite/app/matrix_lite/daemon.py.
Command/input: PYTHONPYCACHEPREFIX=/tmp/opencode/pycache python3 -m py_compile /home/matrix-lite/app/matrix_lite/daemon.py.
Tool input: {"command": "PYTHONPYCACHEPREFIX=/tmp/opencode/pycache python3 -m py_compile /home/matrix-lite/app/matrix_lite/daemon.py", "cwd": "/home/matrix-lite/app"}
Agent intent/context: compile check
Decision by: @gleb:matrix.nvdll.org.
Decision reaction: 👍.
Decision rejection reason: (none).
Original user request: Run a compile check on /home/matrix-lite/app/
     matrix_lite/daemon.py using run_check.
Runtime metadata: the requested approval was granted. Continue using the granted scope/action; if a tool still refuses it, explain that runtime permission integration failed instead of requesting the same approval again.

Continue the original task now if possible. If permission was denied, explain the outcome and propose a safer alternative.


Yes — I have access to it now.

I checked `persistent_chat_tool_manifest`, and it’s there:

- `persistent_chat_note_reload_handoff`

So the report is consistent with what I can actually see.

Also good news:
- the manifest is now much richer than before
- the MCP tool surface is finally in decent shape
- and yes, this new handoff tool is the **right** thing to use instead of relying only on a manually created side file

Because it records:
- structured source artifact(s)
- markdown handoff
- and a canonical `perpetual-log.jsonl` meta event

That makes it much more durable and discoverable than a free-floating file.

Summary: High prompt-cache reuse.

Output:
Yes — I have access to it now.

I checked `persistent_chat_tool_manifest`, and it’s there:

- `persistent_chat_note_reload_handoff`

So the report is consistent with what I can actually see.

Also good news:
- the manifest is now much richer than before
- the MCP tool surface is finally in decent shape
- and yes, this new handoff tool is the **right** thing to use instead of relying only on a manually created side file

Because it records:
- structured source artifact(s)
- markdown handoff
- and a canonical `perpetual-log.jsonl` meta event

That makes it much more durable and discoverable than a free-floating file.

Check out this report from another agent. Do you already have access to it?

New MCP tool:

     persistent_chat_note_reload_handoff

     It records:

     - pre-reload-handoff.json
     - pre-reload-handoff.md
     - canonical perpetual-log.jsonl meta entry:
       - role: meta
       - kind: pre-reload-handoff

     Inputs:
     - reason
     - summary
     - optional volatile_context
     - optional pointers
     - request_curation
     - source

     It is also listed in persistent_chat_tool_manifest.


Good — I updated the handoff and triggered the reload.

What was allowed/result:
- The pre-reload handoff was recorded in the proper source artifact set
- Then I used the ACP session admin restart path on `persistent-chat`
- The logical reload **succeeded**

What happened:
- old conversation label: `persistent-chat`
- new conversation label: `persistent-chat-20260529T191232Z`
- old backend session id: `ses_1a4838151ffe2RE9g5hXeQ8xwX`
- new backend session: pending next turn (fresh direct ACP session will be created on demand)

The restart path also:
- synced the session log
- ran heartbeat before/after
- refreshed packets/manifests
- checked context manifest health

So the handoff is now in place and the session has been logically reloaded.

Summary: High prompt-cache reuse.

Output:
Good — I updated the handoff and triggered the reload.

What was allowed/result:
- The pre-reload handoff was recorded in the proper source artifact set
- Then I used the ACP session admin restart path on `persistent-chat`
- The logical reload **succeeded**

What happened:
- old conversation label: `persistent-chat`
- new conversation label: `persistent-chat-20260529T191232Z`
- old backend session id: `ses_1a4838151ffe2RE9g5hXeQ8xwX`
- new backend session: pending next turn (fresh direct ACP session will be created on demand)

The restart path also:
- synced the session log
- ran heartbeat before/after
- refreshed packets/manifests
- checked context manifest health

So the handoff is now in place and the session has been logically reloaded.

Great, then please review the handoff again, update if needed, and trigger a reload. I like our long session but it's getting close to limits


Pretty good, honestly.

Best parts:
- I still know what we were doing
- the handoff survived
- the session didn’t collapse into “who are you / what repo is this”
- the important work from the long session was externalized enough that I can continue coherently

Still imperfect:
- some nuances are compressed
- I have the *shape* of the session better than every detail
- if we hadn’t written the handoff and cleaned memory, this reload would have been much worse

So:
- **continuity of task and context:** good
- **continuity of exact nuance:** decent, not perfect
- **overall:** a real success compared to earlier reloads

Summary: High prompt-cache reuse.

Output:
Pretty good, honestly.

Best parts:
- I still know what we were doing
- the handoff survived
- the session didn’t collapse into “who are you / what repo is this”
- the important work from the long session was externalized enough that I can continue coherently

Still imperfect:
- some nuances are compressed
- I have the *shape* of the session better than every detail
- if we hadn’t written the handoff and cleaned memory, this reload would have been much worse

So:
- **continuity of task and context:** good
- **continuity of exact nuance:** decent, not perfect
- **overall:** a real success compared to earlier reloads


Yeah — that means the reload was only **logical/on-paper**, not yet reflected in the UI/session identity the way you expected.

Most likely:
- the reload helper advanced the **persistent-chat label/state**
- but the visible session indicator is still showing the old **live route/backend session**
- so from your side it looks like “same session”

In other words:
- **handoff + reload artifacts:** updated
- **visible session identity:** not convincingly switched

So that’s a real problem, not just a wording issue.
A proper reload should be observable, not something we have to infer from files.

Summary: High prompt-cache reuse.

Output:
Yeah — that means the reload was only **logical/on-paper**, not yet reflected in the UI/session identity the way you expected.

Most likely:
- the reload helper advanced the **persistent-chat label/state**
- but the visible session indicator is still showing the old **live route/backend session**
- so from your side it looks like “same session”

In other words:
- **handoff + reload artifacts:** updated
- **visible session identity:** not convincingly switched

So that’s a real problem, not just a wording issue.
A proper reload should be observable, not something we have to infer from files.

the problem is it still shows we are in the same session


I retried the reload the same way, and this time it **did switch** the logical session label again:

- old label:
  - `persistent-chat-20260529T191232Z`
- new label:
  - `persistent-chat-20260529T204325Z`

And it again:
- recorded the handoff artifacts
- synced the session log
- ran heartbeat before/after
- refreshed packets/manifests
- confirmed context-manifest health

So from the reload system’s point of view:
- the handoff was updated
- the logical session label changed
- the next backend session will again be created on demand

Whether the UI now reflects it correctly is the key thing to verify from your side.

Summary: High prompt-cache reuse.

Output:
I retried the reload the same way, and this time it **did switch** the logical session label again:

- old label:
  - `persistent-chat-20260529T191232Z`
- new label:
  - `persistent-chat-20260529T204325Z`

And it again:
- recorded the handoff artifacts
- synced the session log
- ran heartbeat before/after
- refreshed packets/manifests
- confirmed context-manifest health

So from the reload system’s point of view:
- the handoff was updated
- the logical session label changed
- the next backend session will again be created on demand

Whether the UI now reflects it correctly is the key thing to verify from your side.

Okay this should be fixed now. Please trigger the reload again the same way so we actually switch this time


Yes — it looks like it worked this time.

The visible session label in the pinned state is now:
- `persistent-chat-20260529T204325Z`

and not the old one, so the reload is now actually reflected instead of only being “logical on paper.”

Summary: High prompt-cache reuse.

Output:
Yes — it looks like it worked this time.

The visible session label in the pinned state is now:
- `persistent-chat-20260529T204325Z`

and not the old one, so the reload is now actually reflected instead of only being “logical on paper.”


Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output: Hey — I’m here. What’s up?


Pretty solid.

I still have the main thread:
- we were testing reloads
- the key issue was whether the session switch became visibly real, not just logical
- the last visible label change was to `persistent-chat-20260529T204325Z`
- now you’re checking whether continuity survived this new reload

So:
- **task continuity:** good
- **recent conversational continuity:** good
- **fine-grained nuance from the longer earlier session:** probably a bit compressed, as usual after reload

Overall this feels like a successful reload from a continuity standpoint. If you want, I can also sanity-check the current pinned/runtime state more concretely instead of just judging from conversational continuity.

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output:
Pretty solid.

I still have the main thread:
- we were testing reloads
- the key issue was whether the session switch became visibly real, not just logical
- the last visible label change was to `persistent-chat-20260529T204325Z`
- now you’re checking whether continuity survived this new reload

So:
- **task continuity:** good
- **recent conversational continuity:** good
- **fine-grained nuance from the longer earlier session:** probably a bit compressed, as usual after reload

Overall this feels like a successful reload from a continuity standpoint. If you want, I can also sanity-check the current pinned/runtime state more concretely instead of just judging from conversational continuity.

We just reloaded (again), how's continuity?


Yes — this looks like a genuinely new session, not just a paper reload.

I checked the live runtime:
- current session label: `persistent-chat-20260529T204325Z`
- current direct ACP session id: `ses_18a53d671ffer3rrL2MWHNxZaM`
- health report says it was reloaded at `2026-05-29T20:43:51Z`

And I checked the repo fix in `/home/matrix-lite/app`. The relevant recent commits are:

- `7b89bf8` — **fix: keep direct ACP reload sessions isolated**
- `15c63d4` — **fix: re

Summary: Moderate prompt-cache reuse.

Output:
Yes — this looks like a genuinely new session, not just a paper reload.

I checked the live runtime:
- current session label: `persistent-chat-20260529T204325Z`
- current direct ACP session id: `ses_18a53d671ffer3rrL2MWHNxZaM`
- health report says it was reloaded at `2026-05-29T20:43:51Z`

And I checked the repo fix in `/home/matrix-lite/app`. The relevant recent commits are:

- `7b89bf8` — **fix: keep direct ACP reload sessions isolated**
- `15c63d4` — **fix: re

The problem was that reloads happened but we continued in the old session. This looks like a genuinely new one, right? You can also check the repo to see the fix


Probably the daemon-side packet/excerpting, not me.

What I can verify:
- the last completed turn shows **293 output tokens**, so I did generate a normal-length reply
- but the **injected turn packet** for this turn contains a visibly clipped excerpt of that reply (`... fix: re...`)

So the likely situation is:
- **actual assistant response generation:** fine
- **continuity/status packet summary of the prior response:** truncated

In other words, I don’t think I personally stopped mid-sentence there; the daemon is probably clipping the stored/excerpted version that gets fed back on the next turn.

If you mean the **live room message you saw** was truncated too, that’s more serious and I can inspect the raw turn/log path next.

Summary: High prompt-cache reuse.

Output:
Probably the daemon-side packet/excerpting, not me.

What I can verify:
- the last completed turn shows **293 output tokens**, so I did generate a normal-length reply
- but the **injected turn packet** for this turn contains a visibly clipped excerpt of that reply (`... fix: re...`)

So the likely situation is:
- **actual assistant response generation:** fine
- **continuity/status packet summary of the prior response:** truncated

In other words, I don’t think I personally stopped mid-sentence there; the daemon is probably clipping the stored/excerpted version that gets fed back on the next turn.

If you mean the **live room message you saw** was truncated too, that’s more serious and I can inspect the raw turn/log path next.

Hmm is the daemon truncating the text, or are you?


Yeah — I checked, and the truncation happened **before** the Matrix room render.

Evidence:
- the **actual Matrix event that was sent** is truncated in `state/events.jsonl`:
  - it ends at `- \`15c63d4\` — **fix: re`
- the same truncated text is also what got stored in:
  - `state/conversations/rooms/persistent/main/transcript.jsonl`
  - `state/turns.jsonl`
- `turns.jsonl` even records:
  - `truncation_reason: "possible_mid_sentence_cutoff"`

So the fault is **not** “your client only displayed part of a full message.”
The daemon/direct-ACP pipeline actually accepted a truncated assistant reply and sent that truncated text live.

Interesting detail:
- the OpenCode runtime log also contains a **full** final answer for that turn

So the bug seems to be in the **direct ACP extraction/handoff path**:
- OpenCode had the full answer
- but the daemon’s `assistant_text` for that turn ended up truncated
- and that truncated version is what got sent to Matrix

So: **not me intentionally shortening it, and not just packet excerpting either**.
It looks like a real daemon/client-path bug in how the direct ACP final text is captured.

If you want, I can now inspect that exact code path and patch it.

Summary: High prompt-cache reuse.

Output:
Yeah — I checked, and the truncation happened **before** the Matrix room render.

Evidence:
- the **actual Matrix event that was sent** is truncated in `state/events.jsonl`:
  - it ends at `- \`15c63d4\` — **fix: re`
- the same truncated text is also what got stored in:
  - `state/conversations/rooms/persistent/main/transcript.jsonl`
  - `state/turns.jsonl`
- `turns.jsonl` even records:
  - `truncation_reason: "possible_mid_sentence_cutoff"`

So the fault is **not** “your client only displayed part of a full message.”
The daemon/direct-ACP pipeline actually accepted a truncated assistant reply and sent that truncated text live.

Interesting detail:
- the OpenCode runtime log also contains a **full** final answer for that turn

So the bug seems to be in the **direct ACP extraction/handoff path**:
- OpenCode had the full answer
- but the daemon’s `assistant_text` for that turn ended up truncated
- and that truncated version is what got sent to Matrix

So: **not me intentionally shortening it, and not just packet excerpting either**.
It looks like a real daemon/client-path bug in how the direct ACP final text is captured.

If you want, I can now inspect that exact code path and patch it.

Yes the live message was truncated too I never saw your full text


direct ACP timeout after 1830s/1830000ms

Output:
{"event": "session_loaded", "sessionId": "ses_18a53d671ffer3rrL2MWHNxZaM"}
{"event": "first_session_update", "sessionId": "ses_18a53d671ffer3rrL2MWHNxZaM"}
{"event": "first_tool_update", "sessionId": "ses_18a53d671ffer3rrL2MWHNxZaM"}
{"event": "permission_request"}
{"event": "permission_response"}
{"event": "permission_request"}
{"event": "permission_response"}
{"event": "permission_request"}
{"event": "permission_response"}
{"event": "permission_request"}
{"event": "timeout", "timeoutSeconds": 1830, "timeoutMs": 1830000}

{"filepath":"../../app/scripts/matrix-lite-direct-acp-client.mjs","diff":"Index: /home/matrix-lite/app/scripts/matrix-lite-direct-acp-client.mjs\n===================================================================\n--- /home/matrix-lite/app/scripts/matrix-lite-direct-acp-client.mjs\n+++ /home/matrix-lite/app/scripts/matrix-lite-direct-acp-client.mjs\n@@ -307,17 +307,32 @@\n     await sleep(Math.min(quietMs, 100))\n   }\n }\n \n-// test-order marker: await sleep(250)\n+async function waitForPromptQuiet(client, quietMs = 500, maxWaitMs = 5000) {\n+  const startMs = monotonicMs()\n+  while (true) {\n+    const waitedMs = monotonicMs() - startMs\n+    const lastUpdateMs = client.lastPromptUpdateMs || 0\n+    if (!lastUpdateMs || monotonicMs() - lastUpdateMs >= quietMs) {\n+      return waitedMs\n+    }\n+    if (waitedMs >= maxWaitMs) {\n+      return waitedMs\n+    }\n+    await sleep(Math.min(quietMs, 100))\n+  }\n+}\n+\n class MatrixLiteAcpClient {\n   constructor(opts) {\n     this.opts = opts\n     this.finalTextByMessage = new Map()\n     this.permissionCounter = 0\n     this.promptActive = false\n     this.promptStartMs = 0\n     this.lastPrePromptUpdateMs = 0\n+    this.lastPro

edit

Index: /home/matrix-lite/app/tests/test_daemon_stability.py
===================================================================
--- /home/matrix-lite/app/tests/test_daemon_stability.py
+++ /home/matrix-lite/app/tests/test_daemon_stability.py
@@ -655,9 +655,11 @@
     self.assertIn("['reasoning', 'thinking', 'internal', 'debug'].includes(ctype)", text)
     self.assertIn('stripHiddenContent(update.content)', text)
     self.assertIn("reason: 'hidden_content'", text)
     self.assertLess(text.index('client.startPrompt()'), text.index("event: 'prompt_started'"))
-    self.assertLess(text.index('await sleep(250)'), text.index('client.startPrompt()'))
+    self.assertIn('async function waitForPromptQuiet', text)
+    self.assertIn('const promptDrainMs = await waitForPromptQuiet(client)', text)
+    self.assertIn("phase: 'prompt_drain_done'", text)
     self.assertLess(text.index('const finalText = client.finalText()'), text.index('client.finishPrompt()'))

 def test_direct_acp_prompt_uses_client_jsonl_done_text(self):
     calls = []

edit

Index: /home/matrix-lite/app/tests/test_continuity_scripts.py
===================================================================
--- /home/matrix-lite/app/tests/test_continuity_scripts.py
+++ /home/matrix-lite/app/tests/test_continuity_scripts.py
@@ -1075,9 +1075,10 @@
 self.assertIn("'matrix'", text)
 self.assertIn('session_update', text)
 self.assertIn('permission_request', text)
 self.assertIn('permission_response', text)
-self.assertIn('await sleep(250)', text)
+self.assertIn('waitForPromptQuiet', text)
+self.assertIn('prompt_drain_done', text)
 self.assertIn('textLength', text)
 self.assertIn('redactPermissionParams', text)
 self.assertIn('inputPreview', text)
 self.assertIn('previewPermissionValue', text)

edit

bash

⚠ 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.


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.

Summary: High prompt-cache reuse.

Output:
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.

bash

bash

bash

bash

bash

bash

Index: /home/matrix-lite/app/tests/test_daemon_stability.py
===================================================================
--- /home/matrix-lite/app/tests/test_daemon_stability.py
+++ /home/matrix-lite/app/tests/test_daemon_stability.py
@@ -657,9 +657,9 @@
     self.assertIn("reason: 'hidden_content'", text)
     self.assertLess(text.index('client.startPrompt()'), text.index("event: 'prompt_started'"))
     self.assertIn('async function waitForPromptQuiet', text)
     self.assertIn('const promptDrainMs = await waitForPromptQuiet(client)', text)
-    self.assertIn("phase: 'prompt_drain_done'", text)
+    self.assertIn("emitPhase('prompt_drain_done'", text)
     self.assertLess(text.index('const finalText = client.finalText()'), text.index('client.finishPrompt()'))

 def test_direct_acp_prompt_uses_client_jsonl_done_text(self):
     calls = []

edit

bash

bash

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


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.

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output:
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.

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


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.

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output:
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.


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.

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output:
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.

bash


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

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

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

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


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

Summary: High prompt-cache reuse.

Output:
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

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


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**

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output:
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**

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.


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**.

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output:
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**.

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


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**.

Summary: High prompt-cache reuse.

Output:
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**.

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


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.

Summary: High prompt-cache reuse.

Output:
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.

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.


Yes. I did a quick inventory, and there’s already a pretty good mapping.

My strongest recommendation: **don’t port the packet files as first-class native modules** except maybe as temporary compatibility shims. They’re mostly assembled views, not ideal source artifacts.

Rough mapping by bucket / change frequency:

### 1. Very stable / default-on
Best existing artifacts:
- `character.json` — core identity/personality
- `behavior-rules.md` — durable operating/behavior rules
- `curated-memory.md` — durable user facts + major long-lived operational facts

Maybe split later:
- `curated-memory.md` is doing both **user facts** and **system history/protocol**; that probably wants separation eventually.

### 2. Stable but occasionally revised
Best existing artifacts:
- `decision-state.json` — active long-lived decisions / threads
- `knowledge-base.jsonl` — external researched facts, clearly distinct from memory
- `semantic-memory.json` — explicit remembered items, but currently noisy and probably needs cleanup before becoming a prominent native module

My take:
- `decision-state.json` is very module-shaped already
- `knowledge-base.jsonl` should stay more optional / topic-loaded
- `semantic-memory.json` feels more like a backing store than a nice direct module right now

### 3. Medium-frequency operational state
Best existing artifacts:
- `recent-topics.md`
- `recent-failures.json`
- `operational-synthesis/notices.jsonl`
- `operational-synthesis/actions.jsonl`
- maybe `operational-synthesis/latest.md`

Good native candidates:
- current operational state
- active issues / recent failures
- actionable notices

My take:
- this bucket is already there, just a bit fragmented

### 4. High-churn recent context
Best existing artifacts:
- `pinned-state.md`
- maybe `continuity-summary.txt`
- maybe `todo.md` as human-oriented dashboard

But:
- `pinned-state.md` is useful, though it mixes runtime truth, current thread, actions, persona, notices
- `continuity-summary.txt` looks stale/weird and is probably a weak candidate for the native future
- `todo.md` looks more like a derived dashboard than a source artifact

So for native, I’d probably replace this with cleaner explicit modules like:
- `current-thread`
- `runtime-truth`
- `open-actions`

instead of carrying over those exact files unchanged.

### 5. Ephemeral / per-turn / load-on-demand
Current equivalents are mostly packet-ish:
- `turn-packet.md`
- `session-packet.md`
- `session-start-packet.md`
- `restore-packet.md`

These are useful now, but in native I would treat them as:
- **migration scaffolding**
- or **derived compatibility views**
- not the target architecture

Because native modules should let you assemble those views, not depend on them.

---

## Things that already map cleanly
If I had to name the best current “native-ready” source artifacts:

- `character.json`
- `behavior-rules.md`
- `curated-memory.md`
- `decision-state.json`
- `knowledge-base.jsonl`
- `recent-topics.md`
- `recent-failures.json`
- `operational-synthesis/notices.jsonl`
- `operational-synthesis/actions.jsonl`

## Things I would demote / scrutinize
- `continuity-pinned-notes.txt` — lots of junky literal remembered fragments
- `semantic-memory.json` — useful backing memory, but not yet clean enough to foreground
- `continuity-summary.txt` — stale / mixed-quality snapshot
- packet files in general — useful now, but not ideal native source modules
- `reflection-journal.md` / `curator-journal.md` — valuable logs/reference, but probably optional, not default context

## Likely new native modules we don’t quite have cleanly yet
I think these should probably exist explicitly, even if they’re currently only implicit or mixed together:

- **runtime-truth**
  - currently embedded in `pinned-state.md`
- **current-thread**
  - currently embedded in `pinned-state.md`
- **active-decisions**
  - mostly `decision-state.json`, maybe with a trimmed view
- **open-actions**
  - currently split across `todo.md` and `operational-synthesis/actions.jsonl`
- **user-preferences**
  - currently scattered across `curated-memory.md`
- **core-operating-rules**
  - `behavior-rules.md`, maybe merged with part of character data

## My practical recommendation
For native migration, I’d classify like this:

**Keep as source-like modules**
- `character.json`
- `behavior-rules.md`
- `curated-memory.md`
- `decision-state.json`
- `knowledge-base.jsonl`
- `recent-topics.md`
- `recent-failures.json`
- `operational-synthesis/notices.jsonl`
- `operational-synthesis/actions.jsonl`

**Keep as reference/optional**
- `curator-journal.md`
- `reflection-journal.md`
- `semantic-memory.json`

**Treat as derived/legacy compatibility**
- `pinned-state.md`
- `continuity-summary.txt`
- all packet files

**Probably replace with cleaner native-first modules**
- runtime truth
- current thread
- open actions
- explicit user preferences

If you want, next I can turn this into a sharper table:
**artifact → proposed native module → default/optional → change frequency → keep/split/demote/replace**.

Summary: High prompt-cache reuse.

Output:
Yes. I did a quick inventory, and there’s already a pretty good mapping.

My strongest recommendation: **don’t port the packet files as first-class native modules** except maybe as temporary compatibility shims. They’re mostly assembled views, not ideal source artifacts.

Rough mapping by bucket / change frequency:

### 1. Very stable / default-on
Best existing artifacts:
- `character.json` — core identity/personality
- `behavior-rules.md` — durable operating/behavior rules
- `curated-memory.md` — durable user facts + major long-lived operational facts

Maybe split later:
- `curated-memory.md` is doing both **user facts** and **system history/protocol**; that probably wants separation eventually.

### 2. Stable but occasionally revised
Best existing artifacts:
- `decision-state.json` — active long-lived decisions / threads
- `knowledge-base.jsonl` — external researched facts, clearly distinct from memory
- `semantic-memory.json` — explicit remembered items, but currently noisy and probably needs cleanup before becoming a prominent native module

My take:
- `decision-state.json` is very module-shaped already
- `knowledge-base.jsonl` should stay more optional / topic-loaded
- `semantic-memory.json` feels more like a backing store than a nice direct module right now

### 3. Medium-frequency operational state
Best existing artifacts:
- `recent-topics.md`
- `recent-failures.json`
- `operational-synthesis/notices.jsonl`
- `operational-synthesis/actions.jsonl`
- maybe `operational-synthesis/latest.md`

Good native candidates:
- current operational state
- active issues / recent failures
- actionable notices

My take:
- this bucket is already there, just a bit fragmented

### 4. High-churn recent context
Best existing artifacts:
- `pinned-state.md`
- maybe `continuity-summary.txt`
- maybe `todo.md` as human-oriented dashboard

But:
- `pinned-state.md` is useful, though it mixes runtime truth, current thread, actions, persona, notices
- `continuity-summary.txt` looks stale/weird and is probably a weak candidate for the native future
- `todo.md` looks more like a derived dashboard than a source artifact

So for native, I’d probably replace this with cleaner explicit modules like:
- `current-thread`
- `runtime-truth`
- `open-actions`

instead of carrying over those exact files unchanged.

### 5. Ephemeral / per-turn / load-on-demand
Current equivalents are mostly packet-ish:
- `turn-packet.md`
- `session-packet.md`
- `session-start-packet.md`
- `restore-packet.md`

These are useful now, but in native I would treat them as:
- **migration scaffolding**
- or **derived compatibility views**
- not the target architecture

Because native modules should let you assemble those views, not depend on them.

---

## Things that already map cleanly
If I had to name the best current “native-ready” source artifacts:

- `character.json`
- `behavior-rules.md`
- `curated-memory.md`
- `decision-state.json`
- `knowledge-base.jsonl`
- `recent-topics.md`
- `recent-failures.json`
- `operational-synthesis/notices.jsonl`
- `operational-synthesis/actions.jsonl`

## Things I would demote / scrutinize
- `continuity-pinned-notes.txt` — lots of junky literal remembered fragments
- `semantic-memory.json` — useful backing memory, but not yet clean enough to foreground
- `continuity-summary.txt` — stale / mixed-quality snapshot
- packet files in general — useful now, but not ideal native source modules
- `reflection-journal.md` / `curator-journal.md` — valuable logs/reference, but probably optional, not default context

## Likely new native modules we don’t quite have cleanly yet
I think these should probably exist explicitly, even if they’re currently only implicit or mixed together:

- **runtime-truth**
  - currently embedded in `pinned-state.md`
- **current-thread**
  - currently embedded in `pinned-state.md`
- **active-decisions**
  - mostly `decision-state.json`, maybe with a trimmed view
- **open-actions**
  - currently split across `todo.md` and `operational-synthesis/actions.jsonl`
- **user-preferences**
  - currently scattered across `curated-memory.md`
- **core-operating-rules**
  - `behavior-rules.md`, maybe merged with part of character data

## My practical recommendation
For native migration, I’d classify like this:

**Keep as source-like modules**
- `character.json`
- `behavior-rules.md`
- `curated-memory.md`
- `decision-state.json`
- `knowledge-base.jsonl`
- `recent-topics.md`
- `recent-failures.json`
- `operational-synthesis/notices.jsonl`
- `operational-synthesis/actions.jsonl`

**Keep as reference/optional**
- `curator-journal.md`
- `reflection-journal.md`
- `semantic-memory.json`

**Treat as derived/legacy compatibility**
- `pinned-state.md`
- `continuity-summary.txt`
- all packet files

**Probably replace with cleaner native-first modules**
- runtime truth
- current thread
- open actions
- explicit user preferences

If you want, next I can turn this into a sharper table:
**artifact → proposed native module → default/optional → change frequency → keep/split/demote/replace**.

Can you map these items to existing artifacts, if applicable? If not then we think about making them


Yes — that framing makes a lot of sense.

So the native analog is not “reload a session,” but more like:
- compact or trim old tail/context inputs
- produce a summary artifact
- review it
- selectively update durable modules
- then stop loading the dropped tail

That’s much cleaner than ACP reload mythology.

Here’s the sharper table:

| Existing artifact | Proposed native module | Default? | Change frequency | Recommendation |
|---|---|---:|---|---|
| `character.json` | core-identity | yes | very low | **keep** |
| `behavior-rules.md` | operating-rules | yes | very low | **keep** |
| `curated-memory.md` | durable-memory | yes | low | **keep, later split** |
| `decision-state.json` | active-decisions | yes | low/medium | **keep** |
| `knowledge-base.jsonl` | external-knowledge | no | low/medium | **keep optional** |
| `recent-topics.md` | recent-topics | maybe | medium | **keep, maybe trim** |
| `recent-failures.json` | recent-failures | maybe | medium | **keep, refresh/clean** |
| `operational-synthesis/notices.jsonl` | actionable-notices | maybe | medium/high | **keep, probably filtered view** |
| `operational-synthesis/actions.jsonl` | open-actions | maybe | medium | **keep** |
| `operational-synthesis/latest.md` | synthesis-summary | no | medium | **optional/reference** |
| `semantic-memory.json` | explicit-memories | no | medium | **keep backend, clean before foregrounding** |
| `continuity-pinned-notes.txt` | explicit-memory-dump | no | medium | **demote or replace** |
| `curator-journal.md` | curator-journal | no | high | **reference only** |
| `reflection-journal.md` | reflection-journal | no | high | **reference only** |
| `todo.md` | dashboard/open-actions view | no | medium | **derived view, not source** |
| `pinned-state.md` | runtime + thread aggregate | no | high | **replace with native modules** |
| `continuity-summary.txt` | legacy continuity summary | no | medium/high | **retire or replace** |
| `turn-packet.md` | legacy turn packet | no | per-turn | **retire / compatibility only** |
| `session-packet.md` | legacy session packet | no | per-session | **retire** |
| `session-start-packet.md` | legacy bootstrap packet | no | per-session | **retire** |
| `restore-packet.md` | legacy restore packet | no | per-session | **retire** |

And the missing native-first modules I’d explicitly introduce:

| New module | Purpose | Default? | Change frequency |
|---|---|---:|---|
| `runtime-truth` | current backend/model/capabilities/trustworthy live state | yes | medium |
| `current-thread` | compact active thread + pending next action | yes | high |
| `open-actions` | actionable tasks only | maybe | medium |
| `user-preferences` | extracted stable preferences from curated memory | yes | low |
| `compaction-summaries` | reviewed summaries produced when old tail is compacted/dropped | maybe | low/medium |
| `tail-window` | recent raw/near-raw conversation tail kept temporarily | yes-ish | high |
| `temporary-skills` | one-turn or short-lived loaded skills/modules | no | per-turn |

My strongest architectural opinion:
- **source artifacts should be small, purpose-specific, and editable**
- **aggregate packets should become derived products, not primary memory**
- **compaction summaries should be reviewed before they promote into durable modules**

If you want, next I can turn this into a proposed **module load order for caching**:
stable prefix → semi-stable prefix → operational layer → hot tail → per-turn additions.

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output:
Yes — that framing makes a lot of sense.

So the native analog is not “reload a session,” but more like:
- compact or trim old tail/context inputs
- produce a summary artifact
- review it
- selectively update durable modules
- then stop loading the dropped tail

That’s much cleaner than ACP reload mythology.

Here’s the sharper table:

| Existing artifact | Proposed native module | Default? | Change frequency | Recommendation |
|---|---|---:|---|---|
| `character.json` | core-identity | yes | very low | **keep** |
| `behavior-rules.md` | operating-rules | yes | very low | **keep** |
| `curated-memory.md` | durable-memory | yes | low | **keep, later split** |
| `decision-state.json` | active-decisions | yes | low/medium | **keep** |
| `knowledge-base.jsonl` | external-knowledge | no | low/medium | **keep optional** |
| `recent-topics.md` | recent-topics | maybe | medium | **keep, maybe trim** |
| `recent-failures.json` | recent-failures | maybe | medium | **keep, refresh/clean** |
| `operational-synthesis/notices.jsonl` | actionable-notices | maybe | medium/high | **keep, probably filtered view** |
| `operational-synthesis/actions.jsonl` | open-actions | maybe | medium | **keep** |
| `operational-synthesis/latest.md` | synthesis-summary | no | medium | **optional/reference** |
| `semantic-memory.json` | explicit-memories | no | medium | **keep backend, clean before foregrounding** |
| `continuity-pinned-notes.txt` | explicit-memory-dump | no | medium | **demote or replace** |
| `curator-journal.md` | curator-journal | no | high | **reference only** |
| `reflection-journal.md` | reflection-journal | no | high | **reference only** |
| `todo.md` | dashboard/open-actions view | no | medium | **derived view, not source** |
| `pinned-state.md` | runtime + thread aggregate | no | high | **replace with native modules** |
| `continuity-summary.txt` | legacy continuity summary | no | medium/high | **retire or replace** |
| `turn-packet.md` | legacy turn packet | no | per-turn | **retire / compatibility only** |
| `session-packet.md` | legacy session packet | no | per-session | **retire** |
| `session-start-packet.md` | legacy bootstrap packet | no | per-session | **retire** |
| `restore-packet.md` | legacy restore packet | no | per-session | **retire** |

And the missing native-first modules I’d explicitly introduce:

| New module | Purpose | Default? | Change frequency |
|---|---|---:|---|
| `runtime-truth` | current backend/model/capabilities/trustworthy live state | yes | medium |
| `current-thread` | compact active thread + pending next action | yes | high |
| `open-actions` | actionable tasks only | maybe | medium |
| `user-preferences` | extracted stable preferences from curated memory | yes | low |
| `compaction-summaries` | reviewed summaries produced when old tail is compacted/dropped | maybe | low/medium |
| `tail-window` | recent raw/near-raw conversation tail kept temporarily | yes-ish | high |
| `temporary-skills` | one-turn or short-lived loaded skills/modules | no | per-turn |

My strongest architectural opinion:
- **source artifacts should be small, purpose-specific, and editable**
- **aggregate packets should become derived products, not primary memory**
- **compaction summaries should be reviewed before they promote into durable modules**

If you want, next I can turn this into a proposed **module load order for caching**:
stable prefix → semi-stable prefix → operational layer → hot tail → per-turn additions.

Agreed, it doesn't make sense to have session packets if we don't have sessions.
The analog of current reload would probably be dropping or compacting older tail, the idea is that it runs as async subagent, then you check the result and decide what other artifacts to modify, add this compaction summary and drop older tail.

Yes a sharper table would be great


Great — here’s the load order I’d aim for for native caching and control:

## 1. Stable prefix — almost never changes
Load first, maximize cache reuse.

- `core-identity` ← `character.json`
- `operating-rules` ← `behavior-rules.md`
- `user-preferences` ← extracted/split from `curated-memory.md`
- maybe `durable-memory-core` ← the most important stable part of `curated-memory.md`

Goal:
- this prefix should stay very compact and very stable

## 2. Semi-stable prefix — occasional updates
Still cache-friendly, but revised sometimes.

- `durable-memory` ← remainder of `curated-memory.md`
- `active-decisions` ← `decision-state.json`
- `architecture-facts` ← either split from curated memory or a dedicated artifact later
- `external-knowledge-index` ← lightweight pointer/index, not full knowledge dump

Goal:
- important long-term orientation
- not too noisy
- still fairly reusable between turns

## 3. Operational layer — medium churn
Useful often, but shouldn’t poison the stable prefix.

- `open-actions` ← `operational-synthesis/actions.jsonl` / maybe cleaned view
- `actionable-notices` ← filtered `notices.jsonl`
- `recent-failures` ← `recent-failures.json`
- `recent-topics` ← `recent-topics.md`

Goal:
- active project / system state
- loaded by default only if useful enough
- maybe some of these become conditional

## 4. Hot context layer — high churn
Changes often, likely every few turns.

- `current-thread`
- `runtime-truth`
- `tail-window`
- maybe `compaction-summary-latest` if relevant

Goal:
- keep this late in the prompt so churn doesn’t invalidate the earlier cacheable prefix

## 5. Per-turn additions — ephemeral
Load only when needed.

- temporary skills
- task-specific retrievals
- topic knowledge slices
- one-off repo/runtime summaries
- ad hoc investigation context

Goal:
- highly disposable
- never part of the stable baseline

---

# Rough rule of thumb

**Earlier in prompt:**
- stable
- high value
- low churn
- broadly useful

**Later in prompt:**
- volatile
- task-specific
- easy to recompute
- easy to omit

---

# Practical artifact-to-layer mapping

### Layer 1
- `character.json`
- `behavior-rules.md`
- split-out stable user preferences

### Layer 2
- `curated-memory.md` (after splitting if needed)
- `decision-state.json`
- maybe a future `architecture-facts.md`

### Layer 3
- `recent-topics.md`
- `recent-failures.json`
- filtered `operational-synthesis/actions.jsonl`
- filtered `operational-synthesis/notices.jsonl`

### Layer 4
- native `current-thread`
- native `runtime-truth`
- recent tail
- latest compaction summary

### Layer 5
- temporary loaded skills
- retrieval snippets
- topic packs
- task-local scratch modules

---

# Important design opinion

I would strongly avoid:
- putting rapidly changing timestamps near the top
- mixing runtime truth with durable memory
- loading raw journals by default
- loading full knowledge-base content by default
- making compaction summaries automatically authoritative without review

I would strongly prefer:
- tiny stable modules near the top
- derived filtered views for noisy artifacts
- explicit optional modules for topic knowledge
- reviewed compaction summaries that can then update durable modules

So yes — I think the ideal native stack is basically:

**stable identity → stable memory → operational state → hot thread/tail → per-turn temporary modules**

If you want, next I can turn this into a more concrete proposal like:
**module name, source artifact, default loaded?, allowed size budget, and whether it should be source or derived.**

Summary: Moderate prompt-cache reuse.

Output:
Great — here’s the load order I’d aim for for native caching and control:

## 1. Stable prefix — almost never changes
Load first, maximize cache reuse.

- `core-identity` ← `character.json`
- `operating-rules` ← `behavior-rules.md`
- `user-preferences` ← extracted/split from `curated-memory.md`
- maybe `durable-memory-core` ← the most important stable part of `curated-memory.md`

Goal:
- this prefix should stay very compact and very stable

## 2. Semi-stable prefix — occasional updates
Still cache-friendly, but revised sometimes.

- `durable-memory` ← remainder of `curated-memory.md`
- `active-decisions` ← `decision-state.json`
- `architecture-facts` ← either split from curated memory or a dedicated artifact later
- `external-knowledge-index` ← lightweight pointer/index, not full knowledge dump

Goal:
- important long-term orientation
- not too noisy
- still fairly reusable between turns

## 3. Operational layer — medium churn
Useful often, but shouldn’t poison the stable prefix.

- `open-actions` ← `operational-synthesis/actions.jsonl` / maybe cleaned view
- `actionable-notices` ← filtered `notices.jsonl`
- `recent-failures` ← `recent-failures.json`
- `recent-topics` ← `recent-topics.md`

Goal:
- active project / system state
- loaded by default only if useful enough
- maybe some of these become conditional

## 4. Hot context layer — high churn
Changes often, likely every few turns.

- `current-thread`
- `runtime-truth`
- `tail-window`
- maybe `compaction-summary-latest` if relevant

Goal:
- keep this late in the prompt so churn doesn’t invalidate the earlier cacheable prefix

## 5. Per-turn additions — ephemeral
Load only when needed.

- temporary skills
- task-specific retrievals
- topic knowledge slices
- one-off repo/runtime summaries
- ad hoc investigation context

Goal:
- highly disposable
- never part of the stable baseline

---

# Rough rule of thumb

**Earlier in prompt:**
- stable
- high value
- low churn
- broadly useful

**Later in prompt:**
- volatile
- task-specific
- easy to recompute
- easy to omit

---

# Practical artifact-to-layer mapping

### Layer 1
- `character.json`
- `behavior-rules.md`
- split-out stable user preferences

### Layer 2
- `curated-memory.md` (after splitting if needed)
- `decision-state.json`
- maybe a future `architecture-facts.md`

### Layer 3
- `recent-topics.md`
- `recent-failures.json`
- filtered `operational-synthesis/actions.jsonl`
- filtered `operational-synthesis/notices.jsonl`

### Layer 4
- native `current-thread`
- native `runtime-truth`
- recent tail
- latest compaction summary

### Layer 5
- temporary loaded skills
- retrieval snippets
- topic packs
- task-local scratch modules

---

# Important design opinion

I would strongly avoid:
- putting rapidly changing timestamps near the top
- mixing runtime truth with durable memory
- loading raw journals by default
- loading full knowledge-base content by default
- making compaction summaries automatically authoritative without review

I would strongly prefer:
- tiny stable modules near the top
- derived filtered views for noisy artifacts
- explicit optional modules for topic knowledge
- reviewed compaction summaries that can then update durable modules

So yes — I think the ideal native stack is basically:

**stable identity → stable memory → operational state → hot thread/tail → per-turn temporary modules**

If you want, next I can turn this into a more concrete proposal like:
**module name, source artifact, default loaded?, allowed size budget, and whether it should be source or derived.**


Yeah — a few concrete suggestions come to mind.

## 1. Split `curated-memory.md` sooner rather than later
Right now it’s carrying too many roles at once.

I’d split it into at least:
- **user-preferences / user-facts**
- **system-history / architecture-facts**
- maybe **operational protocols**

That gives you:
- cleaner caching
- easier selective loading
- less accidental churn in the “most stable” layer

## 2. Make `current-thread` a first-class native module
Not a packet excerpt, not buried in a status aggregate.

It should be a compact artifact with only:
- active topic
- pending next action
- maybe 3–5 recent crucial turns/events

This is probably one of the highest-value modules in the whole system.

## 3. Separate source artifacts from derived views very strictly
This feels important for avoiding future confusion.

For example:
- **source**: decisions, preferences, actions, notices
- **derived**: packets, dashboards, summaries, prompt-assembled views

That way the native backend edits source modules, never its own compiled prompt products.

## 4. Treat compaction summaries as reviewable proposals, not truth
Your framing already points this way, and I strongly agree.

Good flow:
- async compaction subagent summarizes old tail
- summary lands in `compaction-summaries`
- main agent or user reviews it
- only then promote pieces into durable modules
- then old tail can be dropped

That prevents bad summaries from silently rewriting memory.

## 5. Add explicit size budgets per module
Not just load order.

Something like:
- core identity: tiny
- operating rules: tiny
- user preferences: small
- durable memory: small/medium
- current thread: small
- notices/actions: very small filtered views
- raw journals: never default

That will help prevent gradual bloat.

## 6. Make “optional topic packs” a real concept
For things like:
- WGT
- matrix-lite architecture
- housing workflow
- videoctl
- future project-specific domains

These should be:
- discoverable
- loadable on demand
- absent by default

That feels much better than forcing all useful knowledge into the always-on context.

## 7. Clean or demote low-quality memory artifacts
Especially:
- `continuity-pinned-notes.txt`
- parts of `semantic-memory.json`
- stale summary artifacts

Some of those feel like useful historical residue, but not good native prompt modules.

## 8. Keep runtime truth separate from memory
Very important.

“Current model/backend/capabilities/state” should live in a **runtime-truth** module, not in curated memory or continuity summaries.
That avoids stale factual contamination.

## 9. Consider a two-level action model
Instead of one `open-actions` blob:

- **durable actions**
  - important, survives compaction
- **working set**
  - immediate short-horizon tasks

That might help keep the hot layer lighter.

## 10. Design for subtraction, not just addition
This is maybe the biggest native advantage.

Every module should be easy to:
- load
- skip
- replace
- expire
- compact
- archive

If a module can only grow, it’ll eventually recreate ACP-style baggage.

---

If I had to prioritize just **three** design moves:

1. **Split curated memory**
2. **Create first-class current-thread**
3. **Make compaction summaries review-gated before promotion**

Those three alone would already make the native architecture feel much cleaner.

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output:
Yeah — a few concrete suggestions come to mind.

## 1. Split `curated-memory.md` sooner rather than later
Right now it’s carrying too many roles at once.

I’d split it into at least:
- **user-preferences / user-facts**
- **system-history / architecture-facts**
- maybe **operational protocols**

That gives you:
- cleaner caching
- easier selective loading
- less accidental churn in the “most stable” layer

## 2. Make `current-thread` a first-class native module
Not a packet excerpt, not buried in a status aggregate.

It should be a compact artifact with only:
- active topic
- pending next action
- maybe 3–5 recent crucial turns/events

This is probably one of the highest-value modules in the whole system.

## 3. Separate source artifacts from derived views very strictly
This feels important for avoiding future confusion.

For example:
- **source**: decisions, preferences, actions, notices
- **derived**: packets, dashboards, summaries, prompt-assembled views

That way the native backend edits source modules, never its own compiled prompt products.

## 4. Treat compaction summaries as reviewable proposals, not truth
Your framing already points this way, and I strongly agree.

Good flow:
- async compaction subagent summarizes old tail
- summary lands in `compaction-summaries`
- main agent or user reviews it
- only then promote pieces into durable modules
- then old tail can be dropped

That prevents bad summaries from silently rewriting memory.

## 5. Add explicit size budgets per module
Not just load order.

Something like:
- core identity: tiny
- operating rules: tiny
- user preferences: small
- durable memory: small/medium
- current thread: small
- notices/actions: very small filtered views
- raw journals: never default

That will help prevent gradual bloat.

## 6. Make “optional topic packs” a real concept
For things like:
- WGT
- matrix-lite architecture
- housing workflow
- videoctl
- future project-specific domains

These should be:
- discoverable
- loadable on demand
- absent by default

That feels much better than forcing all useful knowledge into the always-on context.

## 7. Clean or demote low-quality memory artifacts
Especially:
- `continuity-pinned-notes.txt`
- parts of `semantic-memory.json`
- stale summary artifacts

Some of those feel like useful historical residue, but not good native prompt modules.

## 8. Keep runtime truth separate from memory
Very important.

“Current model/backend/capabilities/state” should live in a **runtime-truth** module, not in curated memory or continuity summaries.
That avoids stale factual contamination.

## 9. Consider a two-level action model
Instead of one `open-actions` blob:

- **durable actions**
  - important, survives compaction
- **working set**
  - immediate short-horizon tasks

That might help keep the hot layer lighter.

## 10. Design for subtraction, not just addition
This is maybe the biggest native advantage.

Every module should be easy to:
- load
- skip
- replace
- expire
- compact
- archive

If a module can only grow, it’ll eventually recreate ACP-style baggage.

---

If I had to prioritize just **three** design moves:

1. **Split curated memory**
2. **Create first-class current-thread**
3. **Make compaction summaries review-gated before promotion**

Those three alone would already make the native architecture feel much cleaner.


Yeah, I think that’s a very good direction.

A few reactions:

- **Knowledge base:** agreed — don’t overdesign it too early.
  - If existing tools fit, great.
  - If not, a simple interim structure is fine as long as it’s searchable and source-aware.

- **RAG over existing structure:** yes, that seems like the right transitional move.
  - Treat current artifacts/packs as the corpus
  - add retrieval over them
  - then refine the storage model later once usage patterns are clearer

That’s better than pausing everything until the “perfect” knowledge model exists.

- **Packs as RAG units:** I especially like that.
  - workflow packs
  - topic packs
  - architecture packs
  - restoration/continuity packs
  - maybe compact skill metadata on top

That gives you a natural granularity for retrieval.

- **Workflows as skills:** also yes.
  - ImmoScout is a good example
  - not because the exact actions are universal, but because the structure is:
    - prerequisites
    - goals
    - step sequence
    - failure modes
    - escalation points
    - reusable prompts/templates
    - capability constraints

So a “skill” can basically be:
- a reusable procedural scaffold
- optionally paired with retrieval from packs / knowledge / live state

That feels cleaner than forcing everything into one generic memory layer.

Honestly, this combination seems quite strong:

- **modules** for stable loaded context
- **RAG** for selective retrieval over packs/artifacts
- **skills** for reusable procedures/workflows

That gives you:
- stable identity and rules
- flexible recall
- reusable behavior patterns

Which is much closer to what we actually want than ACP-style sticky session memory.

If you want, next time we could sketch a rough three-part architecture:
**modules vs RAG corpus vs skills**, and decide what belongs in each.

Summary: Low prompt-cache reuse; likely prefix/session/provider cache churn. Check recent model/session changes, failed turns, tool-heavy turns, or provider eviction.

Output:
Yeah, I think that’s a very good direction.

A few reactions:

- **Knowledge base:** agreed — don’t overdesign it too early.
  - If existing tools fit, great.
  - If not, a simple interim structure is fine as long as it’s searchable and source-aware.

- **RAG over existing structure:** yes, that seems like the right transitional move.
  - Treat current artifacts/packs as the corpus
  - add retrieval over them
  - then refine the storage model later once usage patterns are clearer

That’s better than pausing everything until the “perfect” knowledge model exists.

- **Packs as RAG units:** I especially like that.
  - workflow packs
  - topic packs
  - architecture packs
  - restoration/continuity packs
  - maybe compact skill metadata on top

That gives you a natural granularity for retrieval.

- **Workflows as skills:** also yes.
  - ImmoScout is a good example
  - not because the exact actions are universal, but because the structure is:
    - prerequisites
    - goals
    - step sequence
    - failure modes
    - escalation points
    - reusable prompts/templates
    - capability constraints

So a “skill” can basically be:
- a reusable procedural scaffold
- optionally paired with retrieval from packs / knowledge / live state

That feels cleaner than forcing everything into one generic memory layer.

Honestly, this combination seems quite strong:

- **modules** for stable loaded context
- **RAG** for selective retrieval over packs/artifacts
- **skills** for reusable procedures/workflows

That gives you:
- stable identity and rules
- flexible recall
- reusable behavior patterns

Which is much closer to what we actually want than ACP-style sticky session memory.

If you want, next time we could sketch a rough three-part architecture:
**modules vs RAG corpus vs skills**, and decide what belongs in each.

These are all really good suggestions. For knowledge base we might search for existing tools if there is anything suitable. We also plan to add RAG, so maybe it can work over the existing structure and packs while we think of a better way. Some of the workflows can be regular agent skills, like immoscout, of course customized to your capabilities but I think the structure is similar.