Yes — exactly.

We captured a lot of:
- factual residue
- topic markers
- recent events
- explicit tasks

But the missing layer is more like:
- **why this matters**
- **how to think about it**
- **what not to lose**
- **what kind of mistake is especially easy here**
- **what the user is really optimizing for**

That is, we preserved a lot of **content**, but not enough **orientation**.

And that’s why it still feels incomplete even with lots of memory machinery. Compaction is already decent at preserving rough content shape. The extra system should have focused more on the parts compaction is bad at:
- intent
- framing
- caution
- epistemic stance
- negative lessons
- subtle corrections

So yes, I think that’s the missing thing.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 21.7s
Time: model 19.8s, overhead 2.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 12.0k o 173 cache 166.4k/93% est $0.0327; p≈3.4ktok/13.7kch
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 44


But where does it go in the current setup?


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 44


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 44


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.8s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 44


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.3s
Time: overhead 1.3s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.3ktok/13.1kch
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 44


* 🟡 Working
Stage: direct ACP load session start (1.3s)
Model: openai/gpt-5.4
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 44
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.1s)
Model: openai/gpt-5.4
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: direct ACP prompt started (4.1s)
Model: openai/gpt-5.4
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 6.7s
Time: model 5.0s, overhead 1.3s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.3ktok/13.1kch
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45


* 🟡 Working
Stage: direct ACP first session update (4.9s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP first visible text (4.9s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 12.3s
Time: model 10.6s, overhead 1.3s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.3ktok/13.1kch
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
In the current setup, I think it belongs in **three layers**, with different roles:

1. **Prompt / agent instructions**
   - for the most general behavioral rules
   - things like:
     - verify current-state claims


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 18.8s
Time: model 17.1s, overhead 1.3s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.3ktok/13.1kch
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
In the current setup, I think it belongs in **three layers**, with different roles:

1. **Prompt / agent instructions**
   - for the most general behavioral rules
   - things like:
     - verify current-state claims
     - separate observed vs hypothetical
     - preserve user frame
     - don’t flatten subtle corrections

2. **Session/handover artifact**
   - this is the main missing place
   - not just “what happened,” but:
     - point of the


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
In the current setup, I think it belongs in **three layers**, with different roles:

1. **Prompt / agent instructions**
   - for the most general behavioral rules
   - things like:
     - verify current-state claims
     - separate observed vs hypothetical
     - preserve user frame
     - don’t flatten subtle corrections

2. **Session/handover artifact**
   - this is the main missing place
   - not just “what happened,” but:
     - point of the thread
     - what must not be lost
     - what would be easy to misread later
     - what stance to keep
     - what changed during the conversation

3. **Durable memory / curated notes**
   - for lessons that outlive a single thread
   - e.g. recurring failure patterns


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 25.0s
Time: model 23.3s, overhead 1.3s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.3ktok/13.1kch
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
setup, I think it belongs in **three layers**, with different roles:

1. **Prompt / agent instructions**
   - for the most general behavioral rules
   - things like:
     - verify current-state claims
     - separate observed vs hypothetical
     - preserve user frame
     - don’t flatten subtle corrections

2. **Session/handover artifact**
   - this is the main missing place
   - not just “what happened,” but:
     - point of the thread
     - what must not be lost
     - what would be easy to misread later
     - what stance to keep
     - what changed during the conversation

3. **Durable memory / curated notes**
   - for lessons that outlive a single thread
   - e.g. recurring failure patterns, stable user preferences about reasoning, known traps

So in short:

- **prompt** = how to think
- **handover/session artifact** = what matters *right now*
- **durable memory** = what matters *


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 31.1s
Time: model 29.4s, overhead 1.3s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.3ktok/13.1kch
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
  - separate observed vs hypothetical
     - preserve user frame
     - don’t flatten subtle corrections

2. **Session/handover artifact**
   - this is the main missing place
   - not just “what happened,” but:
     - point of the thread
     - what must not be lost
     - what would be easy to misread later
     - what stance to keep
     - what changed during the conversation

3. **Durable memory / curated notes**
   - for lessons that outlive a single thread
   - e.g. recurring failure patterns, stable user preferences about reasoning, known traps

So in short:

- **prompt** = how to think
- **handover/session artifact** = what matters *right now*
- **durable memory** = what matters *repeatedly*

If you ask me where the real gap is, it’s mostly **#2**. We already have places for facts and rules, but we don’t yet have a strong enough place for the **orientation of the current thread**.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 32.4s
Time: model 30.6s, overhead 1.3s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 174.8k o 270 t 18 cache 6.7k/4% est $0.4413; p≈3.3ktok/13.1kch
Ctx: direct ACP session 178.6k; active 12.2k; cache 166.4k/93%; p≈3.4ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45


In the current setup, I think it belongs in **three layers**, with different roles:

1. **Prompt / agent instructions**
   - for the most general behavioral rules
   - things like:
     - verify current-state claims
     - separate observed vs hypothetical
     - preserve user frame
     - don’t flatten subtle corrections

2. **Session/handover artifact**
   - this is the main missing place
   - not just “what happened,” but:
     - point of the thread
     - what must not be lost
     - what would be easy to misread later
     - what stance to keep
     - what changed during the conversation

3. **Durable memory / curated notes**
   - for lessons that outlive a single thread
   - e.g. recurring failure patterns, stable user preferences about reasoning, known traps

So in short:

- **prompt** = how to think
- **handover/session artifact** = what matters *right now*
- **durable memory** = what matters *repeatedly*

If you ask me where the real gap is, it’s mostly **#2**. We already have places for facts and rules, but we don’t yet have a strong enough place for the **orientation of the current thread**.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 33.0s
Time: model 30.6s, overhead 2.4s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 174.8k o 270 t 18 cache 6.7k/4% est $0.4413; p≈3.3ktok/13.1kch
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 16.7%; usable 17.0%; observed turns 15; actual turns 45


But do we just create a file for every thing we talk about? There must be some existing solution or better way


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 45


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 45


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.6s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 45


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.2s
Time: overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.5ktok/14.2kch
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 45


* 🟡 Working
Stage: direct ACP load session start (1.2s)
Model: openai/gpt-5.4
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 45
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.5s)
Model: openai/gpt-5.4
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 6.7s
Time: model 5.0s, overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.5ktok/14.2kch
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46


* 🟡 Working
Stage: direct ACP prompt started (4.5s)
Model: openai/gpt-5.4
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP first session update (4.1s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP first visible text (5.5s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
No


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 12.5s
Time: model 10.8s, overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.5ktok/14.2kch
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
No, definitely not a file per conversation. That would be awful.

The better pattern is usually something like:

- **one stable prompt/instruction layer**
- **one durable memory layer**
- **one rolling handover/orientation layer**

So instead of “new file


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 19.1s
Time: model 17.3s, overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.5ktok/14.2kch
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
No, definitely not a file per conversation. That would be awful.

The better pattern is usually something like:

- **one stable prompt/instruction layer**
- **one durable memory layer**
- **one rolling handover/orientation layer**

So instead of “new file for every topic,” think:

1. **Durable facts/rules**
   - long-lived
   - only updated when something truly general or recurring is learned

2. **Rolling thread orientation**
   - a small structured record for the **currently important live


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
No, definitely not a file per conversation. That would be awful.

The better pattern is usually something like:

- **one stable prompt/instruction layer**
- **one durable memory layer**
- **one rolling handover/orientation layer**

So instead of “new file for every topic,” think:

1. **Durable facts/rules**
   - long-lived
   - only updated when something truly general or recurring is learned

2. **Rolling thread orientation**
   - a small structured record for the **currently important live threads**
   - overwritten/updated, not endlessly multiplied
   - maybe a list of a few active threads, not one file per chat subject

3. **Raw logs/transcript**
   - full history exists already
   - not the thing I should rely on directly for continuity

So yes, there are better


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 25.3s
Time: model 23.6s, overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.5ktok/14.2kch
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
instruction layer**
- **one durable memory layer**
- **one rolling handover/orientation layer**

So instead of “new file for every topic,” think:

1. **Durable facts/rules**
   - long-lived
   - only updated when something truly general or recurring is learned

2. **Rolling thread orientation**
   - a small structured record for the **currently important live threads**
   - overwritten/updated, not endlessly multiplied
   - maybe a list of a few active threads, not one file per chat subject

3. **Raw logs/transcript**
   - full history exists already
   - not the thing I should rely on directly for continuity

So yes, there are better existing patterns:
- **scratchpad / working memory**
- **active threads register**
- **task state**
- **episodic summary + semantic memory**
- **blackboard / notebook** style state

What’s missing here is basically an **active threads / orientation register


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 31.5s
Time: model 29.7s, overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.5ktok/14.2kch
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46


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

2. **Rolling thread orientation**
   - a small structured record for the **currently important live threads**
   - overwritten/updated, not endlessly multiplied
   - maybe a list of a few active threads, not one file per chat subject

3. **Raw logs/transcript**
   - full history exists already
   - not the thing I should rely on directly for continuity

So yes, there are better existing patterns:
- **scratchpad / working memory**
- **active threads register**
- **task state**
- **episodic summary + semantic memory**
- **blackboard / notebook** style state

What’s missing here is basically an **active threads / orientation register**.

Not:
- “every topic gets a file”

More like:
- “the system keeps a compact, continuously updated map of what currently matters and how to think about it”

That could be as small as a single structured artifact with entries like:
- thread
- point


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
a list of a few active threads, not one file per chat subject

3. **Raw logs/transcript**
   - full history exists already
   - not the thing I should rely on directly for continuity

So yes, there are better existing patterns:
- **scratchpad / working memory**
- **active threads register**
- **task state**
- **episodic summary + semantic memory**
- **blackboard / notebook** style state

What’s missing here is basically an **active threads / orientation register**.

Not:
- “every topic gets a file”

More like:
- “the system keeps a compact, continuously updated map of what currently matters and how to think about it”

That could be as small as a single structured artifact with entries like:
- thread
- point
- current status
- risks / easy misreads
- stance to preserve
- why it matters

So yes, there is a better way, and it’s more like a **small rolling state model** than a pile of files.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 36.6s
Time: model 34.9s, overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 178.3k o 336 t 29 cache 6.7k/4% est $0.4513; p≈3.5ktok/14.2kch
Ctx: direct ACP session 181.7k; active 175.1k; cache 6.7k/4%; p≈3.3ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46


No, definitely not a file per conversation. That would be awful.

The better pattern is usually something like:

- **one stable prompt/instruction layer**
- **one durable memory layer**
- **one rolling handover/orientation layer**

So instead of “new file for every topic,” think:

1. **Durable facts/rules**
   - long-lived
   - only updated when something truly general or recurring is learned

2. **Rolling thread orientation**
   - a small structured record for the **currently important live threads**
   - overwritten/updated, not endlessly multiplied
   - maybe a list of a few active threads, not one file per chat subject

3. **Raw logs/transcript**
   - full history exists already
   - not the thing I should rely on directly for continuity

So yes, there are better existing patterns:
- **scratchpad / working memory**
- **active threads register**
- **task state**
- **episodic summary + semantic memory**
- **blackboard / notebook** style state

What’s missing here is basically an **active threads / orientation register**.

Not:
- “every topic gets a file”

More like:
- “the system keeps a compact, continuously updated map of what currently matters and how to think about it”

That could be as small as a single structured artifact with entries like:
- thread
- point
- current status
- risks / easy misreads
- stance to preserve
- why it matters

So yes, there is a better way, and it’s more like a **small rolling state model** than a pile of files.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 37.3s
Time: model 34.9s, overhead 2.4s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 178.3k o 336 t 29 cache 6.7k/4% est $0.4513; p≈3.5ktok/14.2kch
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.3%; usable 17.6%; observed turns 17; actual turns 46


Hmm let's try it. Where do we integrate it so it doesn't get overwritten by heartbeat?


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 46


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 46


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.6s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 46


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.1s
Time: overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.3ktok/13.0kch
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 46


* 🟡 Working
Stage: direct ACP load session start (1.3s)
Model: openai/gpt-5.4
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 46
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.4s)
Model: openai/gpt-5.4
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: direct ACP prompt started (4.4s)
Model: openai/gpt-5.4
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 6.5s
Time: model 5.1s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈3.3ktok/13.0kch
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


🟡 Working
Stage: direct ACP first session update (4.1s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47
Label: persistent-chat


* 🟡 Working
Stage: direct ACP first visible text (5.3s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47
Label: persistent-chat


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47
Label: persistent-chat


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


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 12.1s
Time: model 10.7s, overhead 1.1s
Label: persistent-chat
Turn: p≈3.3ktok/13.0kch
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Best place: **a new source artifact that heartbeat reads from, not something heartbeat generates**.

So not:
- `turn-packet.md`
- `session-packet.md`
- other derived files

Because those are exactly what heartbeat will rewrite.

Better options in current setup:

1. **New durable state file


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 18.3s
Time: model 16.8s, overhead 1.1s
Label: persistent-chat
Turn: p≈3.3ktok/13.0kch
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Best place: **a new source artifact that heartbeat reads from, not something heartbeat generates**.

So not:
- `turn-packet.md`
- `session-packet.md`
- other derived files

Because those are exactly what heartbeat will rewrite.

Better options in current setup:

1. **New durable state file under persistent-chat state**
   - something like:
     - `active-threads.json`
     - `orientation-register.json`
     - `thread-handover.json`
   - heartbeat can **read it and surface excerpts**
   - but should never own/regenerate it

2. **Treat


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Best place: **a new source artifact that heartbeat reads from, not something heartbeat generates**.

So not:
- `turn-packet.md`
- `session-packet.md`
- other derived files

Because those are exactly what heartbeat will rewrite.

Better options in current setup:

1. **New durable state file under persistent-chat state**
   - something like:
     - `active-threads.json`
     - `orientation-register.json`
     - `thread-handover.json`
   - heartbeat can **read it and surface excerpts**
   - but should never own/regenerate it

2. **Treat it like curated memory input, not output**
   - same pattern as:
     - raw state/source → heartbeat/curator reads it
     - packet/output files are derived views

3. **Keep writes append/update-based and structured**
   - probably JSON, not prose
   - easier to merge, trim, and reason about

So


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 24.3s
Time: model 22.9s, overhead 1.1s
Label: persistent-chat
Turn: p≈3.3ktok/13.0kch
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
ons in current setup:

1. **New durable state file under persistent-chat state**
   - something like:
     - `active-threads.json`
     - `orientation-register.json`
     - `thread-handover.json`
   - heartbeat can **read it and surface excerpts**
   - but should never own/regenerate it

2. **Treat it like curated memory input, not output**
   - same pattern as:
     - raw state/source → heartbeat/curator reads it
     - packet/output files are derived views

3. **Keep writes append/update-based and structured**
   - probably JSON, not prose
   - easier to merge, trim, and reason about

So the integration pattern should be:

- **agent/script writes** `orientation-register.json`
- **heartbeat reads** it
- **session/turn packets include compact excerpts from it**
- heartbeat must **not overwrite the source file itself**

That’s the safe shape.

If you want, next we can sketch the schema. I


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
    - `active-threads.json`
     - `orientation-register.json`
     - `thread-handover.json`
   - heartbeat can **read it and surface excerpts**
   - but should never own/regenerate it

2. **Treat it like curated memory input, not output**
   - same pattern as:
     - raw state/source → heartbeat/curator reads it
     - packet/output files are derived views

3. **Keep writes append/update-based and structured**
   - probably JSON, not prose
   - easier to merge, trim, and reason about

So the integration pattern should be:

- **agent/script writes** `orientation-register.json`
- **heartbeat reads** it
- **session/turn packets include compact excerpts from it**
- heartbeat must **not overwrite the source file itself**

That’s the safe shape.

If you want, next we can sketch the schema. I’d keep it very small, like:
- thread id
- status
- point
- risks / easy misreads
- stance
- updated_at


* 🟠 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 30.2s
Time: model 28.8s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 181.5k o 293 t 21 cache 6.7k/4% est $0.4586; p≈3.3ktok/13.0kch
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


* 🔴 Failed
Stage: model/tool run failed
Model: openai/gpt-5.4
Elapsed: 30.5s
Time: model 28.8s
Cause: direct ACP client produced a suspiciously truncated final message: possible_mid_sentence_cutoff
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


* 🔴 Failed
Stage: no final answer
Model: openai/gpt-5.4
Elapsed: 30.9s
Time: model 28.8s
Cause: direct ACP client produced a suspiciously truncated final message: possible_mid_sentence_cutoff
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 185.4k; active 178.7k; cache 6.7k/4%; p≈3.5ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


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


* 🔴 Failed
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 31.3s
Time: model 28.8s, overhead 2.6s
Cause: direct ACP client produced a suspiciously truncated final message: possible_mid_sentence_cutoff
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 181.5k o 293 t 21 cache 6.7k/4% est $0.4586; p≈3.3ktok/13.0kch
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


Suspiciously truncated?


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.8s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.2s
Time: overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.8kch
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47


* 🟡 Working
Stage: direct ACP load session start (1.3s)
Model: openai/gpt-5.4
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 47
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.1s)
Model: openai/gpt-5.4
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 48
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: direct ACP prompt started (4.1s)
Model: openai/gpt-5.4
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 48
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 6.6s
Time: model 5.0s, overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.8kch
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 48


* 🟡 Working
Stage: direct ACP first session update (4.5s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 48
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP first visible text (5.8s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 48
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 48
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 12.0s
Time: model 10.4s, overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.8kch
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 48


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


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

That warning usually means the model seemed to finish in a way that looked cut off rather than naturally ended — like a dangling fragment or abrupt stop. So the bridge treated it as suspicious instead of trusting it.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 15.6s
Time: model 14.1s, overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 184.0k o 51 t 30 cache 6.7k/3% est $0.4612; p≈2.4ktok/9.8kch
Ctx: direct ACP session 188.5k; active 181.9k; cache 6.7k/4%; p≈3.3ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 48


Yeah, probably.

That warning usually means the model seemed to finish in a way that looked cut off rather than naturally ended — like a dangling fragment or abrupt stop. So the bridge treated it as suspicious instead of trusting it.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 16.1s
Time: model 14.1s, overhead 2.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 184.0k o 51 t 30 cache 6.7k/3% est $0.4612; p≈2.4ktok/9.8kch
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 17.7%; usable 18.0%; observed turns 18; actual turns 48


I don't know, your draft looks fine to me. And then it even says no final answer. Looks like a bug in the daemon


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 48


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 48


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.6s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 48


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.1s
Time: overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.6ktok/10.3kch
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 48


* 🟡 Working
Stage: direct ACP load session start (1.3s)
Model: openai/gpt-5.4
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 48
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.4s)
Model: openai/gpt-5.4
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 6.4s
Time: model 5.0s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.6ktok/10.3kch
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49


* 🟡 Working
Stage: direct ACP prompt started (4.4s)
Model: openai/gpt-5.4
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP first session update (5.0s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 12.1s
Time: model 10.7s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.6ktok/10.3kch
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49


* 🟡 Working
Stage: direct ACP first visible text (7.0s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 17.5s
Time: model 16.0s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.6ktok/10.3kch
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yeah, that does sound more like a daemon/bridge bug than a real bad answer.

If the draft looked fine to you, and then the system still said:
- suspiciously truncated
- no final answer

then the failure is probably in **how the daemon judged or finalized the turn**, not in the actual content itself.


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
Yeah, that does sound more like a daemon/bridge bug than a real bad answer.

If the draft looked fine to you, and then the system still said:
- suspiciously truncated
- no final answer

then the failure is probably in **how the daemon judged or finalized the turn**, not in the actual content itself.

So more specifically, possibilities are:
- the truncation heuristic is too aggressive
- the final-answer extraction path is misclassifying valid output
- the daemon is losing the final commit step after already showing streamed draft text


* 🟠 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 20.9s
Time: model 19.5s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 192.9k o 134 t 54 est $0.4851; p≈2.6ktok/10.3kch
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49


* 🔴 Failed
Stage: model/tool run failed
Model: openai/gpt-5.4
Elapsed: 21.6s
Time: model 19.5s
Cause: direct ACP client produced a suspiciously truncated final message: possible_mid_sentence_cutoff
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49


* 🔴 Failed
Stage: no final answer
Model: openai/gpt-5.4
Elapsed: 21.8s
Time: model 19.5s
Cause: direct ACP client produced a suspiciously truncated final message: possible_mid_sentence_cutoff
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 190.7k; active 184.1k; cache 6.7k/3%; p≈2.4ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49


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


* 🔴 Failed
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 22.3s
Time: model 19.5s, overhead 2.8s
Cause: direct ACP client produced a suspiciously truncated final message: possible_mid_sentence_cutoff
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 192.9k o 134 t 54 est $0.4851; p≈2.6ktok/10.3kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.2%; usable 18.5%; observed turns 20; actual turns 49


I can still read your drafts but I get error message as normal output. Could you please investigate where the suspiciously truncated condition is coming from and if we need to fix it?


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 49


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 49


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.6s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 49


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.1s
Time: overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 49


* 🟡 Working
Stage: direct ACP load session start (1.2s)
Model: openai/gpt-5.4
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 49
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.2s)
Model: openai/gpt-5.4
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: direct ACP prompt started (4.2s)
Model: openai/gpt-5.4
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 6.6s
Time: model 5.0s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 🟡 Working
Stage: direct ACP first session update (4.5s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP first tool update (4.5s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (1):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 12.0s
Time: model 10.5s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 17.4s
Time: model 15.8s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (4):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (11):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 22.8s
Time: model 21.2s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (13):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 28.2s
Time: model 26.7s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (19):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 34.1s
Time: model 32.5s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 39.5s
Time: model 38.0s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (25):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 45.0s
Time: model 43.5s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 🟡 Working
Stage: direct ACP first visible text (40.5s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (27):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ
- todowrite / in_progress / call_sR8FjwkOBGav9vD1s5forQQ
- 0 todos / completed / call_sR8FjwkOBGav9vD1s5forQQ

Draft:
Yes


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 50.4s
Time: model 48.9s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (27):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ
- todowrite / in_progress / call_sR8FjwkOBGav9vD1s5forQQ
- 0 todos / completed / call_sR8FjwkOBGav9vD1s5forQQ

Draft:
Yes — I checked, and this does look like a daemon-side heuristic issue.

Where it comes from:
- `matrix_lite/daemon.py:5769direct_acp_text_looks_truncated(text, stop_reason)`
- It marks output as suspicious if:
  - it ends with


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (27):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ
- todowrite / in_progress / call_sR8FjwkOBGav9vD1s5forQQ
- 0 todos / completed / call_sR8FjwkOBGav9vD1s5forQQ

Draft:
Yes — I checked, and this does look like a daemon-side heuristic issue.

Where it comes from:
- `matrix_lite/daemon.py:5769direct_acp_text_looks_truncated(text, stop_reason)`
- It marks output as suspicious if:
  - it ends with `<` or `</` → `dangling_xml_tag_fragment`
  - it looks like an unterminated XML-ish tag
  - or, for long text, it ends mid-word / with no punctuation → `possible_mid_sentence_cutoff`

Why that turns into the scary error:
- `matrix_lite


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 56.4s
Time: model 54.9s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (27):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ
- todowrite / in_progress / call_sR8FjwkOBGav9vD1s5forQQ
- 0 todos / completed / call_sR8FjwkOBGav9vD1s5forQQ

Draft:
Yes — I checked, and this does look like a daemon-side heuristic issue.

Where it comes from:
- `matrix_lite/daemon.py:5769direct_acp_text_looks_truncated(text, stop_reason)`
- It marks output as suspicious if:
  - it ends with `<` or `</` → `dangling_xml_tag_fragment`
  - it looks like an unterminated XML-ish tag
  - or, for long text, it ends mid-word / with no punctuation → `possible_mid_sentence_cutoff`

Why that turns into the scary error:
- `matrix_lite/daemon.py:6608`
  - `ok = ... and not truncation_reason ...`
- So **any** truncation_reason forces the whole direct ACP turn to be treated as failed
- Then later at `matrix_lite/daemon.py:8148-8154`, direct


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 62.5s
Time: model 60.9s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (27):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ
- todowrite / in_progress / call_sR8FjwkOBGav9vD1s5forQQ
- 0 todos / completed / call_sR8FjwkOBGav9vD1s5forQQ

Draft:
ke a daemon-side heuristic issue.

Where it comes from:
- `matrix_lite/daemon.py:5769direct_acp_text_looks_truncated(text, stop_reason)`
- It marks output as suspicious if:
  - it ends with `<` or `</` → `dangling_xml_tag_fragment`
  - it looks like an unterminated XML-ish tag
  - or, for long text, it ends mid-word / with no punctuation → `possible_mid_sentence_cutoff`

Why that turns into the scary error:
- `matrix_lite/daemon.py:6608`
  - `ok = ... and not truncation_reason ...`
- So **any** truncation_reason forces the whole direct ACP turn to be treated as failed
- Then later at `matrix_lite/daemon.py:8148-8154`, direct ACP gets the generic user-facing message:
  - “did not receive a final answer... failed or was interrupted...”

So your read is basically right:
- the draft can be perfectly readable
- the daemon can still classify it as “not ok”
- and then emit the generic “no final


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (27):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ
- todowrite / in_progress / call_sR8FjwkOBGav9vD1s5forQQ
- 0 todos / completed / call_sR8FjwkOBGav9vD1s5forQQ

Draft:
g
  - or, for long text, it ends mid-word / with no punctuation → `possible_mid_sentence_cutoff`

Why that turns into the scary error:
- `matrix_lite/daemon.py:6608`
  - `ok = ... and not truncation_reason ...`
- So **any** truncation_reason forces the whole direct ACP turn to be treated as failed
- Then later at `matrix_lite/daemon.py:8148-8154`, direct ACP gets the generic user-facing message:
  - “did not receive a final answer... failed or was interrupted...”

So your read is basically right:
- the draft can be perfectly readable
- the daemon can still classify it as “not ok”
- and then emit the generic “no final answer” message

I do think it should be fixed, in at least two ways:

1. **Make the truncation heuristic less aggressive**
   - especially `possible_mid_sentence_cutoff`
   - that one is easy to false-positive on normal prose

2. **Surface the real reason**
   - if the only


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 68.5s
Time: model 67.0s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (27):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ
- todowrite / in_progress / call_sR8FjwkOBGav9vD1s5forQQ
- 0 todos / completed / call_sR8FjwkOBGav9vD1s5forQQ

Draft:
ated as failed
- Then later at `matrix_lite/daemon.py:8148-8154`, direct ACP gets the generic user-facing message:
  - “did not receive a final answer... failed or was interrupted...”

So your read is basically right:
- the draft can be perfectly readable
- the daemon can still classify it as “not ok”
- and then emit the generic “no final answer” message

I do think it should be fixed, in at least two ways:

1. **Make the truncation heuristic less aggressive**
   - especially `possible_mid_sentence_cutoff`
   - that one is easy to false-positive on normal prose

2. **Surface the real reason**
   - if the only problem is `truncation_reason`, the user-facing message should say that explicitly
   - not the broader “no final answer / failed or interrupted” wording

So the current bug is not just “truncation detection exists” — it’s also that:
- **heuristic suspicion == total turn failure**
-


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 74.5s
Time: model 72.9s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (27):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ
- todowrite / in_progress / call_sR8FjwkOBGav9vD1s5forQQ
- 0 todos / completed / call_sR8FjwkOBGav9vD1s5forQQ

Draft:
adable
- the daemon can still classify it as “not ok”
- and then emit the generic “no final answer” message

I do think it should be fixed, in at least two ways:

1. **Make the truncation heuristic less aggressive**
   - especially `possible_mid_sentence_cutoff`
   - that one is easy to false-positive on normal prose

2. **Surface the real reason**
   - if the only problem is `truncation_reason`, the user-facing message should say that explicitly
   - not the broader “no final answer / failed or interrupted” wording

So the current bug is not just “truncation detection exists” — it’s also that:
- **heuristic suspicion == total turn failure**
- and then it gets reported as a more severe failure than it really is

If you want, I can next patch it so:
- only the XML-tag cases are hard failures
- mid-sentence suspicion becomes softer / logged
- and the user-facing message distinguishes “susp


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Tools (27):
- todowrite / pending / call_IEJ96Tw1RTwdVhjOeW2X9NO
- todowrite / in_progress / call_IEJ96Tw1RTwdVhjOeW2X9NO
- 3 todos / completed / call_IEJ96Tw1RTwdVhjOeW2X9NO
- grep / pending / call_wBQFVtZmrbeX2crwqrxdS5z
- grep / in_progress / call_wBQFVtZmrbeX2crwqrxdS5z
- read / pending / call_1EfTQn4Jvmxsdrc8A30hnjT
- suspiciously truncated|truncation_reason|direct_acp_text_looks_truncated|danglin / completed / call_wBQFVtZmrbeX2crwqrxdS5z
- read / in_progress / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / pending / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_1EfTQn4Jvmxsdrc8A30hnjT
- read / in_progress / call_U0UP4Ip391gVRTc9vEAlz7l
- ../../app/matrix_lite/daemon.py / completed / call_U0UP4Ip391gVRTc9vEAlz7l
- read / pending / call_StKUAWtdmi7WH4U7XmnBe3L
- read / in_progress / call_StKUAWtdmi7WH4U7XmnBe3L
- ../../app/matrix_lite/daemon.py / completed / call_StKUAWtdmi7WH4U7XmnBe3L
- read / pending / call_2dUyv3YUcOx4cDly7h10vfo
- read / in_progress / call_2dUyv3YUcOx4cDly7h10vfo
- grep / pending / call_lt8cIm0TPNlrJGaBSsx17Wz
- grep / in_progress / call_lt8cIm0TPNlrJGaBSsx17Wz
- ../../app/tests/test_daemon_stability.py / completed / call_2dUyv3YUcOx4cDly7h10vfo
- suspiciously truncated final message|did not receive a final answer|send_normal_ / completed / call_lt8cIm0TPNlrJGaBSsx17Wz
- read / pending / call_4cqwgkS4d1boIVU4NzZf0dg
- read / in_progress / call_4cqwgkS4d1boIVU4NzZf0dg
- ../../app/matrix_lite/daemon.py / completed / call_4cqwgkS4d1boIVU4NzZf0dg
- todowrite / pending / call_sR8FjwkOBGav9vD1s5forQQ
- todowrite / in_progress / call_sR8FjwkOBGav9vD1s5forQQ
- 0 todos / completed / call_sR8FjwkOBGav9vD1s5forQQ

Draft:
s “not ok”
- and then emit the generic “no final answer” message

I do think it should be fixed, in at least two ways:

1. **Make the truncation heuristic less aggressive**
   - especially `possible_mid_sentence_cutoff`
   - that one is easy to false-positive on normal prose

2. **Surface the real reason**
   - if the only problem is `truncation_reason`, the user-facing message should say that explicitly
   - not the broader “no final answer / failed or interrupted” wording

So the current bug is not just “truncation detection exists” — it’s also that:
- **heuristic suspicion == total turn failure**
- and then it gets reported as a more severe failure than it really is

If you want, I can next patch it so:
- only the XML-tag cases are hard failures
- mid-sentence suspicion becomes softer / logged
- and the user-facing message distinguishes “suspiciously truncated” from “no final answer.”


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 76.8s
Time: model 75.3s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 488 o 444 cache 201.7k/100% est $0.0079; p≈2.4ktok/9.5kch
Ctx: direct ACP session 193.1k; active 193.1k; p≈2.6ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


Yes — I checked, and this does look like a daemon-side heuristic issue.

Where it comes from:
- `matrix_lite/daemon.py:5769direct_acp_text_looks_truncated(text, stop_reason)`
- It marks output as suspicious if:
  - it ends with `<` or `</` → `dangling_xml_tag_fragment`
  - it looks like an unterminated XML-ish tag
  - or, for long text, it ends mid-word / with no punctuation → `possible_mid_sentence_cutoff`

Why that turns into the scary error:
- `matrix_lite/daemon.py:6608`
  - `ok = ... and not truncation_reason ...`
- So **any** truncation_reason forces the whole direct ACP turn to be treated as failed
- Then later at `matrix_lite/daemon.py:8148-8154`, direct ACP gets the generic user-facing message:
  - “did not receive a final answer... failed or was interrupted...”

So your read is basically right:
- the draft can be perfectly readable
- the daemon can still classify it as “not ok”
- and then emit the generic “no final answer” message

I do think it should be fixed, in at least two ways:

1. **Make the truncation heuristic less aggressive**
   - especially `possible_mid_sentence_cutoff`
   - that one is easy to false-positive on normal prose

2. **Surface the real reason**
   - if the only problem is `truncation_reason`, the user-facing message should say that explicitly
   - not the broader “no final answer / failed or interrupted” wording

So the current bug is not just “truncation detection exists” — it’s also that:
- **heuristic suspicion == total turn failure**
- and then it gets reported as a more severe failure than it really is

If you want, I can next patch it so:
- only the XML-tag cases are hard failures
- mid-sentence suspicion becomes softer / logged
- and the user-facing message distinguishes “suspiciously truncated” from “no final answer.”


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 77.3s
Time: model 75.3s, overhead 2.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 488 o 444 cache 201.7k/100% est $0.0079; p≈2.4ktok/9.5kch
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 18.4%; usable 18.7%; observed turns 21; actual turns 50


Well I want to see any output even if truncated.


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 50


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 50


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.6s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 50


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.1s
Time: overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.6ktok/10.2kch
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 50


* 🟡 Working
Stage: direct ACP load session start (1.3s)
Model: openai/gpt-5.4
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 50
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.4s)
Model: openai/gpt-5.4
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: direct ACP prompt started (4.4s)
Model: openai/gpt-5.4
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 6.5s
Time: model 5.0s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.6ktok/10.2kch
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51


🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 11.7s
Time: model 10.2s, overhead 1.1s
Label: persistent-chat
Turn: p≈2.6ktok/10.2kch
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51


* 🟡 Working
Stage: direct ACP first session update (6.0s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51
Label: persistent-chat


* 🟡 Working
Stage: direct ACP first visible text (6.7s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51
Label: persistent-chat


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51
Label: persistent-chat


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


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

Then the rule should probably be:

- **always show the model output if there is any**
- separately mark it as:
  - complete
  - suspiciously truncated
  - definitely interrupted / no final answer

So truncation should affect:
- **confidence / labeling**

not:
- **whether you get to see


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 17.6s
Time: model 16.1s, overhead 1.1s
Label: persistent-chat
Turn: p≈2.6ktok/10.2kch
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51


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

Then the rule should probably be:

- **always show the model output if there is any**
- separately mark it as:
  - complete
  - suspiciously truncated
  - definitely interrupted / no final answer

So truncation should affect:
- **confidence / labeling**

not:
- **whether you get to see the output at all**

Right now the daemon is conflating:
- “output may be incomplete”
with
- “treat this as no usable final answer”

And that’s the wrong behavior for your preference.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 20.6s
Time: model 19.2s, overhead 1.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 198.2k o 118 t 30 cache 6.7k/3% est $0.4976; p≈2.6ktok/10.2kch
Ctx: direct ACP session 202.7k; active 932; cache 201.7k/100%; p≈2.4ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51


That makes sense.

Then the rule should probably be:

- **always show the model output if there is any**
- separately mark it as:
  - complete
  - suspiciously truncated
  - definitely interrupted / no final answer

So truncation should affect:
- **confidence / labeling**

not:
- **whether you get to see the output at all**

Right now the daemon is conflating:
- “output may be incomplete”
with
- “treat this as no usable final answer”

And that’s the wrong behavior for your preference.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 21.1s
Time: model 19.2s, overhead 2.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 198.2k o 118 t 30 cache 6.7k/3% est $0.4976; p≈2.6ktok/10.2kch
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51


I think this was a reaction to our earlier issues with '...' output


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.6s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.1s
Time: overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.6ktok/10.5kch
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51


* 🟡 Working
Stage: direct ACP load session start (1.3s)
Model: openai/gpt-5.4
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 51
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.7s)
Model: openai/gpt-5.4
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 52
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 6.4s
Time: model 5.0s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.6ktok/10.5kch
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 52


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


* 🟡 Working
Stage: direct ACP prompt started (4.7s)
Model: openai/gpt-5.4
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 52
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP first session update (3.7s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 52
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP first visible text (3.7s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 52
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.3%; usable 19.7%; observed turns 22; actual turns 52
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 12.4s
Time: model 10.9s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.6ktok/10.5kch
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 52


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 52
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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

The heuristic was probably added to catch genuinely broken endings after earlier bad outputs, but it overshot and now catches answers that are merely a bit suspicious-looking. So it solved one failure mode by creating another.


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 14.8s
Time: model 13.4s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 200.6k o 52 cache 6.7k/3% est $0.5023; p≈2.6ktok/10.5kch
Ctx: direct ACP session 205.0k; active 198.3k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 52


Yeah, that would make sense.

The heuristic was probably added to catch genuinely broken endings after earlier bad outputs, but it overshot and now catches answers that are merely a bit suspicious-looking. So it solved one failure mode by creating another.


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 15.3s
Time: model 13.4s, overhead 1.9s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 200.6k o 52 cache 6.7k/3% est $0.5023; p≈2.6ktok/10.5kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 52


How do we fix this?


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 52


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 52


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.6s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 52


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.1s
Time: overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 52


* 🟡 Working
Stage: direct ACP load session start (1.4s)
Model: openai/gpt-5.4
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 52
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.5s)
Model: openai/gpt-5.4
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 6.5s
Time: model 5.0s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


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


* 🟡 Working
Stage: direct ACP prompt started (4.5s)
Model: openai/gpt-5.4
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 12.3s
Time: model 10.8s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 17.7s
Time: model 16.2s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 23.3s
Time: model 21.8s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 28.7s
Time: model 27.2s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 34.2s
Time: model 32.7s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 39.8s
Time: model 38.3s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


* 🟡 Working
Stage: direct ACP first session update (34.0s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP first visible text (34.8s after prompt)
Model: openai/gpt-5.4
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: streaming direct ACP progress
Model: openai/gpt-5.4
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


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


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 45.6s
Time: model 44.1s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
I’d fix it in three steps:

1. **Decouple “show output” from “trust output”**
   - if there is assistant text, show it
   - add a label if needed:
     - complete
     - possibly truncated
     - interrupted / no final answer

2. **N


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
I’d fix it in three steps:

1. **Decouple “show output” from “trust output”**
   - if there is assistant text, show it
   - add a label if needed:
     - complete
     - possibly truncated
     - interrupted / no final answer

2. **Narrow the hard-failure heuristic**
   - keep hard failure for strong signals like:
     - trailing `<` or `</`
     - obvious unterminated tag junk
   - make `possible_mid_sentence_cutoff` a **soft warning**, not an automatic failure

3.


* 📝 Live progress
This is streamed draft/tool progress, not hidden reasoning.
Draft:
I’d fix it in three steps:

1. **Decouple “show output” from “trust output”**
   - if there is assistant text, show it
   - add a label if needed:
     - complete
     - possibly truncated
     - interrupted / no final answer

2. **Narrow the hard-failure heuristic**
   - keep hard failure for strong signals like:
     - trailing `<` or `</`
     - obvious unterminated tag junk
   - make `possible_mid_sentence_cutoff` a **soft warning**, not an automatic failure

3. **Improve the fallback message**
   - don’t say “did not receive a


* 🟡 Processing result
Stage: model returned
Model: openai/gpt-5.4
Elapsed: 51.3s
Time: model 49.8s, overhead 1.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 202.8k o 235 t 26 cache 6.7k/3% est $0.5109; p≈2.4ktok/9.6kch
Ctx: direct ACP session 207.3k; active 200.7k; cache 6.7k/3%; p≈2.6ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


I’d fix it in three steps:

1. **Decouple “show output” from “trust output”**
   - if there is assistant text, show it
   - add a label if needed:
     - complete
     - possibly truncated
     - interrupted / no final answer

2. **Narrow the hard-failure heuristic**
   - keep hard failure for strong signals like:
     - trailing `<` or `</`
     - obvious unterminated tag junk
   - make `possible_mid_sentence_cutoff` a **soft warning**, not an automatic failure

3. **Improve the fallback message**
   - don’t say “did not receive a


* 🟢 Done
Stage: final reply sent
Model: openai/gpt-5.4
Elapsed: 51.8s
Time: model 49.8s, overhead 2.0s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: i 202.8k o 235 t 26 cache 6.7k/3% est $0.5109; p≈2.4ktok/9.6kch
Ctx: direct ACP session 209.7k; active 203.0k; cache 6.7k/3%; p≈2.4ktok; ctx 19.5%; usable 19.9%; observed turns 23; actual turns 53


Now even your draft was truncated


⚪ Received
Stage: queued for agent
Model: openai/gpt-5.4
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 209.7k; active 203.0k; cache 6.7k/3%; p≈2.4ktok; ctx 20.0%; usable 20.4%; observed turns 25; actual turns 53


* ⚪ Queued
Stage: waiting for conversation turn
Model: openai/gpt-5.4
Elapsed: 0.1s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 209.7k; active 203.0k; cache 6.7k/3%; p≈2.4ktok; ctx 20.0%; usable 20.4%; observed turns 25; actual turns 53


* 🟡 Working
Stage: building prompt
Model: openai/gpt-5.4
Elapsed: 0.8s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Ctx: direct ACP session 209.7k; active 203.0k; cache 6.7k/3%; p≈2.4ktok; ctx 20.0%; usable 20.4%; observed turns 25; actual turns 53


* 🟡 Working
Stage: model running
Model: openai/gpt-5.4
Elapsed: 1.2s
Time: overhead 1.2s
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX
Turn: p≈2.7ktok/10.9kch
Ctx: direct ACP session 209.7k; active 203.0k; cache 6.7k/3%; p≈2.4ktok; ctx 20.0%; usable 20.4%; observed turns 25; actual turns 53


* 🟡 Working
Stage: direct ACP load session start (1.3s)
Model: openai/gpt-5.4
Ctx: direct ACP session 209.7k; active 203.0k; cache 6.7k/3%; p≈2.4ktok; ctx 20.0%; usable 20.4%; observed turns 25; actual turns 53
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX


* 🟡 Working
Stage: direct ACP replay drain done (4.6s)
Model: openai/gpt-5.4
Ctx: direct ACP session 209.7k; active 203.0k; cache 6.7k/3%; p≈2.4ktok; ctx 20.0%; usable 20.4%; observed turns 25; actual turns 54
Backend: ses_1a4838151ffe2RE9g5hXeQ8xwX