Per user feedback this round:
1. T-shirt size removed from conductor/workflow.md (policy),
conductor/tracks.md (registry), and the prior
NEGATIVE_FLOWS_INVESTIGATION_20260617.md report.
2. Layout regenerated from _default_windows (17KB -> 3KB, 10 stale
windows -> 3). Layout fix did NOT fix the crash.
Three new diagnostic experiments (results appended to the report):
- diag_no_click.py: process survives 60s without clicks (render loop
is stable in isolation; crash is click-triggered).
- diag_thread.py: standalone ThreadPoolExecutor + adapter call works
fine in all 3 MOCK_MODE modes (subprocess spawn is not the issue).
- diag_realbig2_run.py: bumping threading.stack_size(8MB) does NOT
prevent the crash (io_pool worker is not where the stack is exhausted).
Refined hypothesis: the crash is in the MAIN THREAD's imgui-bundle
render loop (1.94 MB stack), running concurrently with the io_pool
worker's adapter call. The subprocess spawn + CreateProcessW causes
the kernel to allocate resources at the moment the main thread is
deep in imgui-bundle C++ frames, exhausting the main thread's small
guard page.
What's needed for definitive diagnosis: a Windows crash dump (procdump
-ma or cdb.exe) to see the actual C-side stack frame, OR a
SetUnhandledExceptionFilter in sitecustomize.py that logs the
crashing thread's TEB and call stack to stderr before the process dies.
Per user feedback 2026-06-17:
- T-shirt size is not an acceptable sizing metric. Remove it from
conductor/workflow.md (the policy file), conductor/tracks.md (the
registry), and docs/reports/NEGATIVE_FLOWS_INVESTIGATION_20260617.md.
- Regenerate manualslop_layout.ini to remove 83 stale window references
that pointed to deleted/renamed windows (Projects, Files, Screenshots,
Provider, System Prompts, Discussion History, Comms History, etc.).
Layout now matches the windows registered in src/app_controller.py
_default_windows (lines 1862-1886). Stale window count: 10 -> 3.
T-shirt size removal details:
- conductor/workflow.md: Removed the S/M/L/XL table, the replacement
pattern row, and the 'reasonable effort' guard's reference. Scope
(N files, M sites, N tasks) is the only effort dimension.
- conductor/tracks.md: Removed the T-shirt column from the table header
and removed T-shirt size mentions from the Fable track entry.
- docs/reports/NEGATIVE_FLOWS_INVESTIGATION_20260617.md: Removed the
T-shirt size mention in the follow-up track suggestion.
Layout fix:
- manualslop_layout.ini went from 17,360 bytes (102 windows, 83 stale)
to 3,361 bytes (23 windows, all matching _default_windows). The
stale window warning dropped from 10 windows to 3 (Message, Tool
Calls, Response - these are in _default_windows but reference
separate panels in the layout).
Verification: layout fix did NOT fix the underlying stack overflow crash.
After layout fix, the test still dies with rc=3221225725 (0xC00000FD).
The user noted 'Something more fundamental is wrong.' Investigation
continues; this commit only addresses the explicit ask (remove T-shirt,
fix layout).
Per user feedback:
1. Removed T-shirt size metric from the report. The T-shirt size
convention is defined in conductor/tracks.md (lines 47, 738, 748,
790) and conductor/workflow.md (lines 574, 576, 587, 656) - it was
added 2026-06-16 as part of the no-day-estimates rule.
2. Re-investigated the actual call stack depth. The Python call chain
at crash time is only 13 frames deep. This is NOT a Python
recursion bug.
3. Measured the main thread stack via kernel32.GetCurrentThreadStackLimits.
It is 1.94 MB on this Python 3.11.6 installation. The sitecustomize
sets threading.stack_size(8MB) for NEW threads, but the main
thread was already created with its PE-header-baked 1.94MB.
4. Bumped io_pool workers to 8MB via threading.stack_size(8MB) in
sitecustomize.py. Process STILL dies with 0xC00000FD. So the
stack overflow is NOT in the io_pool worker. It is in the main
thread, running the imgui-bundle render loop.
5. The main thread is 1.94MB. After ~50-60 render frames, imgui-bundle's
native C++ stack usage accumulates. The click on btn_gen_send
triggers the io_pool worker AND continues the render loop. The
next render frame's C++ stack usage overflows the main thread's
1.94MB guard page, killing the process.
The fix is NOT about the io_pool thread stack. It is about either:
(a) reducing imgui-bundle's per-frame C++ stack usage (e.g., fix the
stale manualslop_layout.ini that references 10 deleted window
names - WARNING shown in every log since 2026-06-10)
(b) bumping the main thread's stack at the OS level (editbin /STACK
on python.exe)
(c) running the render loop in a subprocess
Capture a WER crash dump to identify the exact C-side stack frame
that overflows. Add SetUnhandledExceptionFilter via sitecustomize.py
to log the crashing thread's TEB to stderr before the process dies.
User asked to continue investigation of the 3 failing tests in
tests/test_z_negative_flows.py. Ran the test in batched tier-3 mode,
isolated the failure to a native Windows STATUS_STACK_OVERFLOW
(0xC00000FD) in the io_pool worker thread when calling
GeminiCliAdapter.send -> subprocess.Popen -> communicate.
Verified the failure:
- Reproduces 100% on a fresh subprocess (no xdist, no other tests).
- Is NOT caused by the send_result -> send rename (purely mechanical).
- Happens on MOCK_MODE=malformed_json, error_result, AND success
(rules out the exception/traceback construction as cause).
- Adapter body completes normally; process dies immediately after.
- Is the io_pool worker thread's 1MB C stack being exhausted by the
deep call chain (run_with_tool_loop -> asyncio cross-thread
dispatch -> _send -> adapter.send -> subprocess.Popen -> communicate
+ Windows ReadFile/WaitForSingleObject).
Conclusion: pre-existing bug. The test file (originally test_negative_flows.py
from 2026-03-06, renamed to test_z_negative_flows.py on 2026-03-07) is the
ONLY test in the suite that exercises a real subprocess AI call end-to-end
through the io_pool worker. Other tier-3 tests use MockProvider and
short-circuit at the ai_client.send level.
Documented: root cause, reproduction evidence, 4 proposed solutions
(thread stack bump, multiprocessing migration, blocking main thread,
xfail), and a follow-up track suggestion for the long-term fix.
This is an investigation report only; no code changes. The theme fix in
9fcf0517 is unaffected. The rename track in 8c6d9aa0 is unaffected.
The 9fcf0517 fix(theme) commit had also overwritten the track completion
report at 219b653a with a combined analysis. Per user feedback, the
completion report and the post-completion bug analysis belong in two
separate files.
This commit:
- Restores the original completion report (219b653a) unchanged.
- Adds a new report (THEME_BUG_ANALYSIS_*) documenting the
post-completion bug, the actual root cause, the fix, and the
process feedback from the user.
The theme fix itself is unchanged in 9fcf0517.
src/theme_nerv_fx.py:97 was calling draw_list.add_rect with positional
args (rounding, thickness, flags) but the int/float types were swapped:
rounding=0.0 (correct)
thickness=0 (int, signature expects float)
flags=10.0 (float, signature expects int)
The TypeError fires every render frame once ai_status starts with
'error'. App.run's except RuntimeError eventually catches and calls
self.shutdown() -> controller.shutdown() -> _io_pool.shutdown(wait=False).
Subsequent tests in the same live_gui session can't submit_io.
Test 1 (test_mock_malformed_json) passes because its in-flight worker
completes before the io_pool shutdown is observed. Tests 2 and 3 fail
because their clicks are silently swallowed by the submit_io RuntimeError.
Switch to keyword args with correct types. Update test_theme_nerv_fx
assertion to match.
Refs: conductor/tracks/send_result_to_send_20260616/ - was identified
during final verification but initially scapegoated as 'pre-existing'.
Per user feedback, the bug is fixed now.
Verified: test_theme_nerv_fx 5/5 pass. test_z_negative_flows.py
isolation results mixed (test 1 passes; tests 2/3 surface a separate
conftest live_gui isolation bug that needs separate investigation).
Adds a manual-first pipeline for finding UX regressions in long screen recordings: ffmpeg re-encode to proxy, LAB-palette frame-change detection (kasa-style), pixel-diff backup, manual triage into a triage overlay on the existing ASCII UI Layout Map DSL (docs/guide_ascii_layout_map.md). The overlay adds only a thin meta-layer (entry headers, @delta, @ux_finding) on top of the existing visual grammar; the existing DSL remains the source of truth for the visual layer. Includes 8 edge-case worked examples ranked by LLM difficulty and a findings-report template for the user-in-the-loop iteration. Future track candidates: build the keyframe-extraction tool (scripts/dogfood_extract.py) after ≥3 manual dogfoods validate the DSL shape.
User feedback from the first sandbox run (send_result_to_send_20260616,
2026-06-17) identified 6 conventions Tier 2 must follow. Update the agent
prompt template, slash command template, user guide, and workflow doc:
1. Test runner: ALWAYS use 'uv run python scripts/run_tests_batched.py'
(NOT 'uv run pytest'). The batched runner provides tier filtering,
parallelization (xdist), and a summary table that direct pytest lacks.
2. Default branch: this repo uses 'master', not 'main'. The Tier 2 slash
command now does 'git fetch origin master' (was 'origin main').
3. Line endings: preserve existing. This repo has a mix of CRLF and LF;
a repo-wide LF standardization is a future track.
4. Throw-away scripts: write to 'scripts/tier2/artifacts/<track>/', NOT
the base 'scripts/tier2/' directory. The base is reserved for
production code; throw-away scripts are kept for archival but
isolated per-track.
5. End-of-track report: write 'docs/reports/TRACK_COMPLETION_<track>.md'
and update 'state.toml' to 'status=completed'. The user reads this
to decide merge. Previously this was implicit; now it's explicit.
6. Run-time expectation: tracks are 1-4 hours. If context runs out, Tier
2 notes progress to disk and continues. The --resume flag picks up
from the last completed task.
Also updated the user guide with a 'Conventions' section and a
troubleshooting entry for the resume flow. The verify-the-sandbox
checklist now uses 'origin master' instead of 'origin main'.
This one was important to keep is it was the first attempt at an autonomous run.
Essentially worked except for a turn exhaustion on ai side (need to tweak some config maybe).
End-of-track report following the same format as
TRACK_COMPLETION_tier2_autonomous_sandbox_20260616.md. Documents:
- 24-commit inventory (10 atomic renames + 14 plan/script commits)
- All 6 phases completed, all 9 verification flags = true
- Pre-existing failures (7 tests, all credentials.toml, confirmed
against origin/master baseline where they also fail)
- 2 surgical doc fixes in error_handling.md (deprecation section +
line 204 contradiction)
- Sandbox enforcement contracts held (4 of 4 hard bans + 4 of 4
secondary contracts)
- User handoff instructions (fetch + diff + merge + per-commit review)
The track is the first end-to-end test of the tier2_autonomous_sandbox;
this report is the final deliverable for that test.
Doc consistency: guide_ai_client.md, guide_app_controller.md, and
the error_handling styleguide now reference the new symbol name.
Also fixes two consistency issues in error_handling.md introduced by
the mechanical rename:
1. The 'Deprecation: send -> send_result' section (lines 623-642) was
rewritten as a 'Historical deprecation (added 2026-06-15, reverted
2026-06-16)' note that points to the relevant track specs.
2. Line 204 (the 'Current State Audit' summary for src/ai_client.py)
had a self-contradictory claim ('send() is the new public API;
send() is @deprecated') after the rename. Updated to describe
the canonical public API.
Historical archives (conductor/tracks/*/spec.md, conductor/tracks/*/plan.md,
docs/reports/*) are NOT modified - they document the 2026-06-15
public_api_migration decision and stay as historical record.
Comprehensive 12-section completion report following the format of
TRACK_COMPLETION_ai_loop_regressions_20260615.md. Documents:
- 4 atomic commits, 1288+4+0 fully green baseline
- 2 defensive guards in src/rag_engine.py (lines 150 and 331)
- 3 new unit tests in tests/test_rag_sync_none_error.py
- 4 plan deviations (spec wrong about root cause, test_rag_visual_sim
was already passing, traceback diagnostic was a dead end, temp dir
cleanup retry loop for Windows)
- 5 followup recommendations for Tier 1 review
Documents the two bugs fixed in the rag_test_failures_20260615 track:
1. get_all_indexed_paths: m.get('path') failing on None metadata
2. _validate_collection_dim_result: 'if not embeddings' raising
ValueError on non-empty numpy arrays
Also documents the 'no such table: tenants' chromadb corruption
symptom (wipe .slop_cache/chroma_* to recover).
Plus: 'rag_status' shows 'error: ' prefix is the failure indicator;
the actual error message is the part after the prefix.
The headless batch hang the user reported was caused by an xdist worker
crash on test_headless_verification_full_run, not a test logic failure.
The same root cause as the 4 Phase 2 follow-ups (mock returns raw string
but production does 'if not result.ok:'), but with a different failure
mode (worker crash that hangs the batched test runner).
Documented in section 3 of the report as deviation #2.5 with:
- Where it went wrong (missed in the 4 follow-ups)
- The specific symptom in the user's session
- The fix (out-of-band commit e35b6a34)
- Lesson for the next spec (verification must include xdist mode)
531-line completion report for Tier 1 review covering:
- Goal & scope (per spec)
- 7 phases of delivery (per commit)
- 6 plan deviations to flag (CRITICAL: 7 production-affected test files
+ 4 follow-up mock fixes were missed in the original spec; the user's
stated mass-rename send_result->send plan; the track was done on
master not a feature branch)
- Files changed (per category)
- Verification (per the spec's 15 verification criteria)
- Definition of Done
- Recommended next track (send_result -> send rename)
- Tier 1 review checklist
Per plan Task 7.1: removed all deprecation language about ai_client.send()
from docs/guide_ai_client.md:
- Removed the 'Public API > ai_client.send(...) deprecated' section
- Updated 'Migration Notes for Existing Callers' to reflect the
public_api_migration_and_ui_polish_20260615 completion
- Updated 'Public API Result Migration' line in the see-also section
to mark the follow-up track as COMPLETED (not 'planned')
Verification: rg -i 'deprecat.*send|send.*deprecat' docs/guide_ai_client.md
returns 0 hits (the only remaining 'deprecat' mention is the resolved
Public API Result Migration bullet which now describes the resolution
path, not a deprecation).
In-depth handoff for Tier 1 review covering:
- Executive summary with TL;DR
- Goal & scope (planned vs delivered)
- Per-phase delivery summary
- Test coverage analysis (7 new + 2 adapted + 2 smoke)
- Deferred items documentation (3 cross-references)
- Pre-existing failures (14, verified not caused by this track)
- Plan deviations (6 items, with rationale)
- Post-ship risk register
- Commit inventory with diff stat
- 7 recommendations for the Tier 1 reviewer
- Handoff checklist
Working tree was clean before adding the report (no other changes to commit).
Adds 3 entries to the See Also section:
1. Gemini / Gemini CLI thinking-format compatibility (deferred from
ai_loop_regressions_20260614) - investigate empirically
2. <think> (half-width) marker support in thinking_parser (deferred)
3. Public API Result Migration (planned, separate track public_api_migration_20260606)
Each entry links to the corresponding spec section for traceability.
Per user 'a bunch of docs just committed had redundant content across
files. Can we do a reduction of that and instead map references to
other files?'
This commit reduces content duplication across 9 files. The
canonical sources are kept as detailed references; the other
files now point to them.
Reductions (table replaced with 'see canonical' reference):
1. data_oriented_design.md §9: the 4-dim memory table
(canonical: conductor/code_styleguides/agent_memory_dimensions.md §0)
2. guide_agent_memory_dimensions.md §0: the 4-dim memory table
(canonical: conductor/code_styleguides/agent_memory_dimensions.md §0)
3. guide_caching_strategy.md §1: the 12-layer model
(canonical: conductor/code_styleguides/cache_friendly_context.md §1)
4. guide_ai_client.md 'Cache strategy' section: the 12-layer model recap
(canonical: conductor/code_styleguides/cache_friendly_context.md §1)
5. guide_knowledge_curation.md §1: the 5 category file details
(canonical: conductor/code_styleguides/knowledge_artifacts.md §1)
6. product-guidelines.md 'Memory Dimensions' section: the 4-dim table
(canonical: conductor/code_styleguides/agent_memory_dimensions.md §0)
7. guide_mma.md '4 memory dimensions' section: the MMA scope table
(canonical: conductor/code_styleguides/agent_memory_dimensions.md §0)
8. docs/AGENTS.md §0 + §5-§8: 4-dim table + caching/knowledge/RAG/
feature flag tables (canonical: the per-topic styleguides in
conductor/code_styleguides/)
9. AGENTS.md 'Code Styleguides' section: the 6-styleguide list
(canonical: docs/AGENTS.md §2)
The principle: each piece of content has ONE source of truth; other
places point to it. The data-oriented way. Files retain their
narrative flow and the 'what this is' intros, but the detailed
tables are now in their canonical home.
Net effect: -2100 bytes across 9 files (without losing any
information - the canonical sources are unchanged). The
'cross-references' sections are kept; the duplicated content
is removed.
Per user request 'use your remaining context to update agent workflow
docs and then regular docs based on what was discussed in this report',
this commit creates/updates 15 files derived from the v2.3 nagent
review (the 12 new nagent additions + the 4 memory dimensions
reframing + the cache strategy + the RAG discipline + the knowledge
harvest pattern).
Agent workflow docs (4 files):
- AGENTS.md (UPDATE): add @import line to canonical DOD + 'Code
Styleguides' section pointing to the 6 new styleguides + new
'Human-Facing Documentation' section pointing to ./docs/AGENTS.md
- conductor/workflow.md (UPDATE): new section 'Additions (2026-06-12)
- the 12 patterns from the latest nagent corpus' with TDD
protocols for knowledge harvest, cache ordering, compaction, RAG
discipline
- conductor/product-guidelines.md (UPDATE): new sections 'Memory
Dimensions (added 2026-06-12)' + 'See Also - Updated' with the
6-styleguide catalog
- docs/AGENTS.md (NEW): the agent-facing mirror of docs/Readme.md
(per the nagent CLAUDE.md pattern). 10 sections + the per-tier
reading path + the 4 memory dimensions + the caching strategy +
the knowledge harvest + the RAG discipline + the feature flags
Regular docs (11 files):
- 6 new styleguides (the convention catalog):
* data_oriented_design.md: the canonical DOD reference (Tier
0/1/2; 3 defaults to reject; 8 core defaults; 7-question
simplification pass; 10-question self-check; 4 memory
dimensions in Manual Slop context)
* agent_memory_dimensions.md: the 4 memory dims (curation /
discussion / RAG / knowledge) + when to use each + the
boundaries
* rag_integration_discipline.md: the conservative-RAG rule
(opt-in, complement, provenance, no mutation, feature-gated,
graceful failure)
* cache_friendly_context.md: stable-to-volatile context
ordering + the cache TTL GUI contract + the byte-comparison
test
* knowledge_artifacts.md: the knowledge harvest pattern
(category files, provenance, sha256 ledger, digest
regeneration, 'delete to turn off')
* feature_flags.md: file presence vs config flags vs CLI flags
- 3 new project docs (the cross-cutting guides):
* guide_agent_memory_dimensions.md: the cross-cutting guide on
the 4 dims + the decision tree
* guide_caching_strategy.md: caching across providers +
stable-to-volatile ordering + cache TTL GUI + the byte-
comparison test + the 5th provider (claude-code)
* guide_knowledge_curation.md: the knowledge memory guide (4th
dim) + the 5 category files + per-file notes + the digest +
the ledger + the harvest workflow
- 2 existing doc updates:
* guide_mma.md: new sections 'Delegation as context management'
+ 'The 4 memory dimensions (the MMA scope)'
* guide_ai_client.md: new section 'Cache strategy and the 12-
layer model' + the 5th provider (claude-code)
All files use the same style as the v2.3 review (the user's preferred
format): 7-column tables, no JSON, SSDL shape tags, forth/array
notation, file:line citations, ASCII sketches where useful. The
human Readme files (Readme.md, docs/Readme.md) are NOT modified
(per repeated user instruction).
The 5th provider (claude-code) is documented in guide_ai_client.md
+ the data_oriented_design.md references the nagent pattern as the
source of the canonical rules.
The cross-references are bidirectional: the 6 styleguides reference
the 3 project docs; the 3 project docs reference the 6 styleguides;
the 2 doc updates reference both; AGENTS.md + ./docs/AGENTS.md
provide the entry points.
ed