skill-stocktake

Original：🇺🇸 English

Translated

3 scripts

Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.

2installs

Sourcesehoon787/my-codex

Added on2026-03-25

NPX Install

npx skill4agent add sehoon787/my-codex skill-stocktake

SKILL.md Content

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skill-stocktake

Slash command (

/skill-stocktake

) that audits all Claude skills and commands using a quality checklist + AI holistic judgment. Supports two modes: Quick Scan for recently changed skills, and Full Stocktake for a complete review.

Scope

The command targets the following paths relative to the directory where it is invoked:

Path	Description
`~/.claude/skills/`	Global skills (all projects)
`{cwd}/.claude/skills/`	Project-level skills (if the directory exists)

At the start of Phase 1, the command explicitly lists which paths were found and scanned.

Targeting a specific project

To include project-level skills, run from that project's root directory:

bash

cd ~/path/to/my-project
/skill-stocktake

If the project has no

.claude/skills/

directory, only global skills and commands are evaluated.

Modes

Mode	Trigger	Duration
Quick Scan	`results.json` exists (default)	5–10 min
Full Stocktake	`results.json` absent, or `/skill-stocktake full`	20–30 min

Results cache:

~/.claude/skills/skill-stocktake/results.json

Quick Scan Flow

Re-evaluate only skills that have changed since the last run (5–10 min).

Read

~/.claude/skills/skill-stocktake/results.json

Run:

bash ~/.claude/skills/skill-stocktake/scripts/quick-diff.sh \       ~/.claude/skills/skill-stocktake/results.json

(Project dir is auto-detected from

$PWD/.claude/skills

; pass it explicitly only if needed)

If output is
```
[]
```
: report "No changes since last run." and stop
Re-evaluate only those changed files using the same Phase 2 criteria
Carry forward unchanged skills from previous results
Output only the diff

Run:

bash ~/.claude/skills/skill-stocktake/scripts/save-results.sh \       ~/.claude/skills/skill-stocktake/results.json <<< "$EVAL_RESULTS"

Full Stocktake Flow

Phase 1 — Inventory

Run:

bash ~/.claude/skills/skill-stocktake/scripts/scan.sh

The script enumerates skill files, extracts frontmatter, and collects UTC mtimes. Project dir is auto-detected from

$PWD/.claude/skills

; pass it explicitly only if needed. Present the scan summary and inventory table from the script output:

Scanning:
  ✓ ~/.claude/skills/         (17 files)
  ✗ {cwd}/.claude/skills/    (not found — global skills only)

Skill	7d use	30d use	Description

Phase 2 — Quality Evaluation

Launch an Agent tool subagent (general-purpose agent) with the full inventory and checklist:

text

Agent(
  subagent_type="general-purpose",
  prompt="
Evaluate the following skill inventory against the checklist.

[INVENTORY]

[CHECKLIST]

Return JSON for each skill:
{ \"verdict\": \"Keep\"|\"Improve\"|\"Update\"|\"Retire\"|\"Merge into [X]\", \"reason\": \"...\" }
"
)

The subagent reads each skill, applies the checklist, and returns per-skill JSON:

{ "verdict": "Keep"|"Improve"|"Update"|"Retire"|"Merge into [X]", "reason": "..." }

Chunk guidance: Process ~20 skills per subagent invocation to keep context manageable. Save intermediate results to

results.json

(

status: "in_progress"

) after each chunk.

After all skills are evaluated: set

status: "completed"

, proceed to Phase 3.

Resume detection: If

status: "in_progress"

is found on startup, resume from the first unevaluated skill.

Each skill is evaluated against this checklist:

- [ ] Content overlap with other skills checked
- [ ] Overlap with MEMORY.md / CLAUDE.md checked
- [ ] Freshness of technical references verified (use WebSearch if tool names / CLI flags / APIs are present)
- [ ] Usage frequency considered

Verdict criteria:

Verdict	Meaning
Keep	Useful and current
Improve	Worth keeping, but specific improvements needed
Update	Referenced technology is outdated (verify with WebSearch)
Retire	Low quality, stale, or cost-asymmetric
Merge into [X]	Substantial overlap with another skill; name the merge target

Evaluation is holistic AI judgment — not a numeric rubric. Guiding dimensions:

Actionability: code examples, commands, or steps that let you act immediately
Scope fit: name, trigger, and content are aligned; not too broad or narrow
Uniqueness: value not replaceable by MEMORY.md / CLAUDE.md / another skill
Currency: technical references work in the current environment

Reason quality requirements — the

reason

field must be self-contained and decision-enabling:

Do NOT write "unchanged" alone — always restate the core evidence

For Retire: state (1) what specific defect was found, (2) what covers the same need instead

Bad:
```
"Superseded"
```

Good:

"disable-model-invocation: true already set; superseded by continuous-learning-v2 which covers all the same patterns plus confidence scoring. No unique content remains."

For Merge: name the target and describe what content to integrate

Bad:
```
"Overlaps with X"
```

Good:

"42-line thin content; Step 4 of chatlog-to-article already covers the same workflow. Integrate the 'article angle' tip as a note in that skill."

For Improve: describe the specific change needed (what section, what action, target size if relevant)

Bad:
```
"Too long"
```

Good:

"276 lines; Section 'Framework Comparison' (L80–140) duplicates ai-era-architecture-principles; delete it to reach ~150 lines."

For Keep (mtime-only change in Quick Scan): restate the original verdict rationale, do not write "unchanged"

Bad:
```
"Unchanged"
```

Good:

"mtime updated but content unchanged. Unique Python reference explicitly imported by rules/python/; no overlap found."

Phase 3 — Summary Table

Skill	7d use	Verdict	Reason

Phase 4 — Consolidation

Retire / Merge: present detailed justification per file before confirming with user:
- What specific problem was found (overlap, staleness, broken references, etc.)
- What alternative covers the same functionality (for Retire: which existing skill/rule; for Merge: the target file and what content to integrate)
- Impact of removal (any dependent skills, MEMORY.md references, or workflows affected)
Improve: present specific improvement suggestions with rationale:
- What to change and why (e.g., "trim 430→200 lines because sections X/Y duplicate python-patterns")
- User decides whether to act
Update: present updated content with sources checked
Check MEMORY.md line count; propose compression if >100 lines

Results File Schema

~/.claude/skills/skill-stocktake/results.json

evaluated_at
: Must be set to the actual UTC time of evaluation completion. Obtain via Bash:

date -u +%Y-%m-%dT%H:%M:%SZ

. Never use a date-only approximation like

T00:00:00Z

json

{
  "evaluated_at": "2026-02-21T10:00:00Z",
  "mode": "full",
  "batch_progress": {
    "total": 80,
    "evaluated": 80,
    "status": "completed"
  },
  "skills": {
    "skill-name": {
      "path": "~/.claude/skills/skill-name/SKILL.md",
      "verdict": "Keep",
      "reason": "Concrete, actionable, unique value for X workflow",
      "mtime": "2026-01-15T08:30:00Z"
    }
  }
}

Notes

Evaluation is blind: the same checklist applies to all skills regardless of origin (ECC, self-authored, auto-extracted)
Archive / delete operations always require explicit user confirmation
No verdict branching by skill origin

skill-stocktake

NPX Install

Tags

SKILL.md Content

skill-stocktake

Scope

Targeting a specific project

Modes

Quick Scan Flow

Full Stocktake Flow

Phase 1 — Inventory

Phase 2 — Quality Evaluation

Phase 3 — Summary Table

Phase 4 — Consolidation

Results File Schema

Notes