scripts/librarian_promote.py is the first Stage 2 piece: a
vendor-agnostic LLM dispatcher that drafts a docs/research/ note
from a given docs/archive/ entry. It assembles the prompt by
stitching scripts/librarian-prompt.md (system) onto the archive
body with a "draft a research note per the rules above" task
instruction, then shells out to the CLI selected by LIBRARIAN_LLM
({claude|codex|gemini}; default claude). The LLM's stdout is
captured to runs/tmp/librarian-promote-<timestamp>-draft.md for
human review — the script never writes into docs/research/ itself.
Refusal cases:
- path not under docs/archive/
- target docs/research/<stem>.md already exists (after stripping any
-YYYY-MM-DD suffix)
- archive missing
If the LLM judges the archive non-promotable, it is instructed to
return a single SKIP: <reason> line instead of fabricating a draft.
--show-prompt prints the assembled prompt without invoking the LLM,
useful for inspecting what would be sent.
Plan updated: Stage 2 v1 marked complete; remaining Stage 2 work
(MEMORY drift fixup, duplicate-merge, survey mode) catalogued.
Next concrete step is a smoke test against one real archive entry.
Adds one ignore-list entry for docs/research/option-a-bench-result.md
which appears in the plan as a hypothetical accept target.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
docs/performance.md grew to 914 lines because dated experiments and
design analyses kept getting appended instead of routed to
docs/archive/ and docs/research/ as AGENTS.md prescribes. The
oversize check from librarian Stage 1 surfaced the file; this commit
acts on that finding by extracting the parts that belong elsewhere
and trimming the source to a focused current-state reference.
Extracts (verbatim from the original prose, with cross-link headers
and a brief routing note added at top):
- docs/archive/deep-cfr-performance-experiments-2026-05-07.md
bundles torch.compile (regression), AMP (regression), GPU forward
profiling (decision support), and Option B interleaved traversal
(pass) — same date, same theme.
- docs/research/batched-traversal-inference-decision.md captures the
durable A vs B vs C rationale with a closing "Outcome" pointer to
the post-bench archive doc.
- docs/archive/post-a-optimization-calculus-2026-05-07.md preserves
the forward-looking sequencing recorded pre-bench.
- docs/archive/option-a-bench-result-2026-05-07.md preserves the
regression diagnosis and re-enable criteria.
docs/performance.md is now 345 lines, holds sections 1–9 (current
runtime / bottleneck / device / AMP status / batching / eval /
TensorRT / priorities), and ends with a "See Also" linking the four
extracts.
Also reworded the AGENTS.md soft-cap rule from a bare "~500-line
soft cap" to clarify the intent: the cap is a *routing trigger* (is
content piling up that should live in archive/research?), not a
split mandate. Reduces the risk of future agents shredding a useful
doc just to satisfy a number.
scripts/librarian.sh now exits 0 against the working tree.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds the last two deterministic Stage 1 checks and wires them into
scripts/librarian.sh:
- librarian_check_stale_plans.py: per docs/plans/*.md, uses
`git log -1 --format=%cs` to get the last commit date and flags
plans untouched in 60+ days. Plans should be either active or
archived; long silence is drift.
- librarian_check_memory_drift.py: validates the user-memory dir
(~/.claude/projects/<slug>/memory). Each MEMORY.md index line
must point at a real file with frontmatter (name, description,
type ∈ {user, feedback, project, reference}); no orphaned memory
files. Memory dir is derived from repo root for portability.
Both run clean against current state.
Stage 1 declared complete. Promotable-archive and duplicate-prose
detection are moved to Stage 2 in the plan because both need LLM
judgment to avoid false positives — not pattern matching.
Next concrete step is the open Stage 1 finding from yesterday:
docs/performance.md at 914 lines, due for a split into sub-topic
notes.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Third Stage 1 piece: scripts/librarian_check_oversize.py walks
non-archive markdown files and flags any over the 500-line soft cap
declared in AGENTS.md. Wired into scripts/librarian.sh.
Caught one real finding on first run: docs/performance.md at 914
lines. Splitting it into sub-topic notes is a separate cleanup task
— surfaced for the user, not auto-applied.
Updates docs/plans/librarian.md Progress + sets the next concrete
step to a stale-plan checker.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Single entry point that runs every Stage 1 check in order and
aggregates exit codes — both checks always run so users see all
findings in one pass. Two checks wired up today (lychee link
integrity, file:line citations), more land incrementally as Stage 1
grows.
Removes scripts/librarian.sh from the ignore list now that the file
exists. Updates docs/plans/librarian.md Progress + Next Step.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
scripts/librarian_check_citations.py extracts file:line references from
inline-code spans across docs/**/*.md and verifies each path exists
(and, if cited with a line number, is within range). Skips
docs/archive/ and docs/plans/archive/ which are read-only by policy.
Caught one real drift in docs/research/optimization_sequencing.md: the
note pointed at docs/plans/amp_trainer.md, which had moved into
docs/plans/archive/.
scripts/librarian-ignore.txt holds fnmatch globs for citations that are
intentionally future-tense (planned files described in the plan docs
themselves). Used sparingly so the checker stays useful as a drift
signal.
Updates docs/plans/librarian.md Progress + Next Step. Next concrete
step is a thin scripts/librarian.sh orchestrator over both checkers.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Captures the full librarian design (two-layer architecture, three-stage
pipeline, vendor-agnostic via LIBRARIAN_LLM env, propose-only / no
auto-apply) in docs/plans/librarian.md. Lands the first concrete Stage 1
piece: scripts/librarian_check_links.py, a lychee --offline wrapper
ported from ~/dev/coolrl/src/coolrl/dev/check_doc_links.py.
Also moves the librarian prompt from .claude/agents/ (Claude Code only)
to scripts/librarian-prompt.md so any CLI can load it as a system
prompt later. Fixes one stale README link the new checker caught:
docs/classic-port-notes.md → docs/archive/classic-port-notes.md.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Add an experiment-only explicit-continuation traversal prototype that batches policy requests, records CPU/CUDA parity results, and updates the Option B plan with Phase 0/1 evidence.
Co-Authored-By: Codex <codex@openai.com>
Archive implemented AMP, Option A inference-server, and Cython heuristic plans. Add the active Option B interleaved traversal plan and update model-size/torch.compile plans to reflect the current traversal scheduling conclusion.
Co-Authored-By: Codex <codex@openai.com>
The experiment finds a model size where (a) learning-curve gains
justify compute, and (b) forward time is large enough to amortize
AMP/compile/TensorRT overhead. Outcome gates re-enabling those four
deferred optimizations and Option A.
Tested grid: hidden={512,768,1024,1536} × layers={3,4,6,8} subset.
200 iterations per config on home (RTX 3090), single seed initially,
second seed for boundary configs. Eval cadence held at default.
Decision tree included for: success → recommend new default and
trigger downstream plans; null → document and stay; expensive-but-
better → defer until AMP/compile/TRT land.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
performance.md additions:
- Batched Traversal Inference design decision (A vs B vs C with
rationale).
- Option A bench result and structural ceiling (realized batch ~7.2,
IPC overhead exceeds GPU gain at small model size).
- Post-A optimization calculus: why compile/TensorRT remain
iter-neutral today and become meaningful only after model growth
and/or denser eval. Sequencing matters; do not retest these on the
current small model.
- Free-threaded Python (3.13t/3.14t) note: cleanest endpoint in
principle, but PyTorch maturity + Cython nogil audit cost block
near-term adoption.
docs/plans/ (4 plan documents for Codex execution):
- batched_traversal_inference_server.md (executed; deferred).
- amp_trainer.md.
- torch_compile.md.
- cython_safe_heuristic_bots.md (executed; first-pass landed).
docs/reports/ (3 cost reports):
- cost_pytorch_free_threaded_2026-05-07.md: WAIT 3-6 months;
PyTorch wheels exist but our Cython is the gating cost.
- cost_cython_nogil_audit_2026-05-07.md: medium effort, traversal.pyx
carries 90% of blockers; Steps 1-3 (cfr_math/encoding nogil
keywords, TraversalStats cdef class) are safe and cheap, Steps
4-6 wait for triggers.
- cost_pytorch_cuda_multithread_2026-05-07.md: risky;
optimizer.step / load_state_dict race silently with concurrent
forward; per-thread default streams unset means naive threading
serializes on default stream anyway.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
coolguyandClaude Opus 4.7