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
Wave 1 / Step 2 of v5.1.0 plain-language UX humanizer.
scanners/lib/humanizer-data.mjs exports TRANSLATIONS keyed by
scanner prefix (CML, SET, HKV, RUL, MCP, IMP, CNF, GAP, TOK, CPS,
DIS, COL, PLH). Each scanner has:
- static: exact-title -> {title, description, recommendation}
- patterns: array of {regex, translation} for template-literal titles
- _default: graceful fallback for unknown findings
Architectural change vs. plan: keys translations by exact scanner
title (not finding ID). Reason: finding IDs are sequence-based
(global counter in lib/output.mjs:34), not stable per finding-type
— two runs can produce different IDs for the same logical issue.
Title strings ARE stable (defined as string literals or template
patterns in the scanner source).
Translations follow research/03 SR-1..SR-17:
- active voice, second person, present tense
- sentences <= 25 words
- tier1 absolute prohibitions and tier3 domain jargon are kept out
of prose
- tier1/tier3 terms are permitted inside `backtick spans` (code
references like filenames and field names) — established
technical-doc convention
Test (12 cases): all 13 scanners covered; every static and pattern
entry has the 3 required fields; tier1 and tier3 forbidden-word
checks pass (with backtick-span exclusion); reference-stable
imports. All pass.
Regression: 657/657 tests (645 + 12 new).
Project: .claude/projects/2026-05-01-config-audit-ux-redesign/
