Session A audit (read/plan only). Reconciled docs/cc-2.1.x-gap-matrix.md (the
v5.2.0 plan) against HEAD: the entire HIGH-priority false-positive cluster is
already CLOSED in v5.2.0 (settings keys + xhigh, 28 hook events, MCP POSIX/trust,
claude-md HIGH->MEDIUM reframe, DIS/CNF param-aware). The 8 unreleased commits add
incrementally; no active bug or false positive remains unshipped.
Operator GO 2026-06-19: "Release-only, ship-list tom" -> Session B SKIPPED. All
still-open gaps are M-effort enhancements -> defer to v5.4. v5.3.0 = docs +
knowledge + release of the 8 commits already on main.
Output: scope-decision block appended to docs/v5.3.0-release-plan.md (empty
ship-list + verbatim GO + full draft CHANGELOG bullets mapping all 8 commits +
What's New draft + 3 knowledge-backing entries for Session C); reconciliation
block prepended to docs/cc-2.1.x-gap-matrix.md. Version confirmed 5.3.0 (minor,
non-breaking). 9 commits 1576909..HEAD = 8 mapped + 1 excluded (the plan commit).
Syklus 2 of Fase 4 Items 2+3. Flags when the sum of active skill
descriptions exceeds the listing budget (~2% of context, CC 2.1.32).
Design (operator-confirmed "fact-first, 200k anchor"):
- low severity (estimate) vs medium for the verified 1,536-char cap
- each description counted up to the 1,536 cap (what actually loads in
the listing) — avoids double-counting the tail CA-SKL-001 flags
- fires when sum > 2% x 200k = 4000 tok; evidence leads with the measured
sum + a calibration note that the budget scales 5x on 1M-context models
- aggregate emitted after the per-skill loop so the common case reads
001=cap, 002=aggregate (finding IDs are a sequential counter, not stable
semantic IDs — tests match on title, never NNN)
Also:
- tailored humanizer static entry for the aggregate title
- fix latent HOME leak in posture-grade-stability.test.mjs: it spawned
posture.mjs without hermeticEnv(), so a real ~/.claude leaked HOME-scoped
SKL/COL findings into the baseline grade (Token Efficiency A->B). Now
isolated like the 8 other CLI-spawning tests.
- docs sync: test count 868->875, scanner-internals, gap-matrix, plan status
Suite 875/875, no snapshot drift, self-audit clean.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ter3E2JSi1Khgmuf2kady8
Fase 4 Items 2+3 (CC 2.1.114→181 gap-review). New orchestrated scanner
`skill-listing-scanner.mjs` (prefix SKL) flags every active skill whose
description exceeds the verified 1,536-char listing cap (CC 2.1.105, changelog
L1502). Past the cap, Claude Code silently truncates the description the model
reads to route skill invocation — dropping the trigger phrases at the tail.
HOME-scoped over all user + plugin skills via enumerateSkills (COL is the model).
- CA-SKL-001 (medium): description > 1,536 chars. Remediation folds in Item
2(b) — recommends disableBundledSkills + skillOverrides + trimming
(designvalg A: no standalone GAP-check, which would fire for nearly everyone).
- Designvalg B: v1 ships the verified cap ONLY. The aggregate 2%-of-context
listing budget is deferred — it needs a context-window assumption that would
turn a verified fact into a guess (would carry a CALIBRATION_NOTE if added).
- Choice C: recognize the skillOverrides settings key (CC 2.1.129) in
KNOWN_KEYS. Left OUT of TYPE_CHECKS — the value is a per-skill object
(off/user-invocable-only/name-only), not a string; a 'string' check (as the
plan sketched) would create a NEW false positive. Verify-first deviation.
Registration: scan-orchestrator (13th scanner), humanizer (SKL → 'Wasted
tokens' + static/_default translations), scoring SCANNER_AREA_MAP (→ Token
Efficiency; no 11th area), README badge 12→13, CLAUDE.md (finding-id +
test-count), docs/scanner-internals.md, gap-matrix + plan status notes.
Snapshots reseeded hermetically (SEED_SNAPSHOT/UPDATE_SNAPSHOT): SKL entry with
0 findings in empty HOME, scanners_ok 11→12, claudeMdEstimatedTokens bump from
the CLAUDE.md edits flowing through the cascade. Contamination grep clean.
Suite 868/868 (856 baseline + 11 SKL + 1 skillOverrides). RED→GREEN logged
per cycle.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ter3E2JSi1Khgmuf2kady8
Plans the skill-listing token-management work (gap-matrix rows 167+169) for a fresh session. All version facts re-verified against the changelog cache before writing: disableBundledSkills v2.1.169; skill-listing budget = 2% of context (v2.1.32) + 1,536-char per-description cap (v2.1.105); skillOverrides v2.1.129.
Key findings from code investigation:
- Item 2(a) (disableBundledSkills unknown-key false-positive) is ALREADY fixed (Batch 1: KNOWN_KEYS + TYPE_CHECKS); matrix row 166 marked DONE.
- Item 2(b): a standalone binary GAP check would be noise; recommend folding the disableBundledSkills recommendation into Item 3 SKL scanner remediation (designvalg A).
- Item 3: new SKL scanner; lead with the verified 1,536-char truncation cap (high confidence); aggregate 2%-budget is an estimate needing a context-window assumption (designvalg B) — calibration-noted.
- Reuse enumerateSkills() + parseFrontmatter; document the boundary vs TOK pattern F.
- Matrix row 170 keys (skillListingBudgetFraction/maxSkillDescriptionChars) do NOT exist (verified).
Plan doc carries exact file:line anchors, scanner-registration touchpoints, failing-test-first cycle specs, and 2 open design decisions to confirm before coding. STATE.md updated to resume here after /clear.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ter3E2JSi1Khgmuf2kady8
Fase 4 token-opt, Item 1 of gap-review NEXT STEP #2. The prompt-cache pattern corpus + TOK scanner were frozen at an "Opus 4.7" framing after CC shipped Opus 4.8 (default, 2.1.154) and Fable 5 (2.1.170). Model-era facts re-verified against the official changelog cache before editing.
The patterns are properties of prompt-caching, not of any model, so mechanic text is now model-neutral with a single "current default: Opus 4.8" anchor — preventing a re-freeze at the next model bump.
- rename knowledge/opus-4.7-patterns.md -> prompt-cache-patterns.md (git mv, history preserved); 6 reference sites updated
- TOK scanner: line-318 finding text (human-facing) made model-neutral; header + cache-prefix-scanner + CLI comments refreshed
- configuration-best-practices.md body + footnote 4.7 -> 4.8
- human-facing docs: commands/{tokens,help,manifest}.md, project CLAUDE.md, README, docs/scanner-internals.md
- gap-matrix row marked DONE; future Items 2/3 retargeted to new filename
Failing-test-first (Iron Law): +2 knowledge staleness guards (era-anchor + no-refreeze) +1 scanner assertion (no stale model anchor in finding text). Suite 853 -> 856 green; zero snapshot drift; self-audit A(97) PASS. CHANGELOG / v5 plan / ratified gap-plan keep historical opus-4.7-patterns refs (correct record of past state).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ter3E2JSi1Khgmuf2kady8
`.mcp.json` has no per-server `trust` key — verified 2026-06-18 against
code.claude.com/docs/en/mcp + /settings. MCP server approval is
dialog/settings-based (enableAllProjectMcpServers / enabledMcpjsonServers /
disabledMcpjsonServers), never a JSON field. The scanner's "Missing trust
level" (CA-MCP-001, medium) and "Invalid trust level" (high) were false
positives flagging a field that does not exist.
- scanner: delete both trust checks + VALID_TRUST_LEVELS; drop `trust` from
VALID_SERVER_FIELDS so a stray `trust` is now flagged as an unknown field
- humanizer: remove the two trust-level entries
- knowledge (5 files): point to the real approval mechanism, not a trust field
- fixtures: scrub `trust` (incl. the invalid "local" in optimal-setup)
- tests: flip assertions (no trust-level finding; stray trust -> unknown
field) + add knowledge-staleness re-freeze guards
- snapshots: reseed (marketplace-medium .mcp.json -8 tokens, hermetic)
- gap-matrix: mark the trust verify-first item DONE
Suite: 853/853 green.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ter3E2JSi1Khgmuf2kady8
