skill-stocktake
Use when auditing skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.
Best use case
skill-stocktake is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when auditing skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.
Teams using skill-stocktake should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/skill-stocktake/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How skill-stocktake Compares
| Feature / Agent | skill-stocktake | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when auditing skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 |
|------|-------------|
| `~/.copilot/skills/` | Global skills (all projects) |
| `{cwd}/.copilot/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 `.copilot/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:** `~/.copilot/skills/skill-stocktake/results.json`
## Quick Scan Flow
Re-evaluate only skills that have changed since the last run (5–10 min).
1. Read `~/.copilot/skills/skill-stocktake/results.json`
2. Run: `bash ~/.copilot/skills/skill-stocktake/scripts/quick-diff.sh \
~/.copilot/skills/skill-stocktake/results.json`
(Project dir is auto-detected from `$PWD/.copilot/skills`; pass it explicitly only if needed)
3. If output is `[]`: report "No changes since last run." and stop
4. Re-evaluate only those changed files using the same Phase 2 criteria
5. Carry forward unchanged skills from previous results
6. Output only the diff
7. Run: `bash ~/.copilot/skills/skill-stocktake/scripts/save-results.sh \
~/.copilot/skills/skill-stocktake/results.json <<< "$EVAL_RESULTS"`
## Full Stocktake Flow
### Phase 1 — Inventory
Run: `bash ~/.copilot/skills/skill-stocktake/scripts/scan.sh`
The script enumerates skill files, extracts frontmatter, and collects UTC mtimes.
Project dir is auto-detected from `$PWD/.copilot/skills`; pass it explicitly only if needed.
Present the scan summary and inventory table from the script output:
```
Scanning:
✓ ~/.copilot/skills/ (17 files)
✗ {cwd}/.copilot/skills/ (not found — global skills only)
```
| Skill | 7d use | 30d use | Description |
|-------|--------|---------|-------------|
### Phase 2 — Quality Evaluation
Launch a Task tool subagent (**Explore agent, model: opus**) with the full inventory and checklist.
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
1. **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)
2. **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
3. **Update**: present updated content with sources checked
4. Check MEMORY.md line count; propose compression if >100 lines
## Results File Schema
`~/.copilot/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": "~/.copilot/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 originRelated Skills
wpds
Use when building UIs leveraging the WordPress Design System (WPDS) and its components, tokens, patterns, etc.
wp-wpcli-and-ops
Use when working with WP-CLI (wp) for WordPress operations: safe search-replace, db export/import, plugin/theme/user/content management, cron, cache flushing, multisite, and scripting/automation with wp-cli.yml.
wp-rest-api
Use when building, extending, or debugging WordPress REST API endpoints/routes: register_rest_route, WP_REST_Controller/controller classes, schema/argument validation, permission_callback/authentication, response shaping, register_rest_field/register_meta, or exposing CPTs/taxonomies via show_in_rest.
wp-project-triage
Use when you need a deterministic inspection of a WordPress repository (plugin/theme/block theme/WP core/Gutenberg/full site) including tooling/tests/version hints, and a structured JSON report to guide workflows and guardrails.
wp-plugin-development
Use when developing WordPress plugins: architecture and hooks, activation/deactivation/uninstall, admin UI and Settings API, data storage, cron/tasks, security (nonces/capabilities/sanitization/escaping), and release packaging.
wp-playground
Use for WordPress Playground workflows: fast disposable WP instances in the browser or locally via @wp-playground/cli (server, run-blueprint, build-snapshot), auto-mounting plugins/themes, switching WP/PHP versions, blueprints, and debugging (Xdebug).
wp-phpstan
Use when configuring, running, or fixing PHPStan static analysis in WordPress projects (plugins/themes/sites): phpstan.neon setup, baselines, WordPress-specific typing, and handling third-party plugin classes.
wp-performance
Use when investigating or improving WordPress performance (backend-only agent): profiling and measurement (WP-CLI profile/doctor, Server-Timing, Query Monitor via REST headers), database/query optimization, autoloaded options, object caching, cron, HTTP API calls, and safe verification.
wp-interactivity-api
Use when building or debugging WordPress Interactivity API features (data-wp-* directives, @wordpress/interactivity store/state/actions, block viewScriptModule integration, wp_interactivity_*()) including performance, hydration, and directive behavior.
wp-block-themes
Use when developing WordPress block themes: theme.json (global settings/styles), templates and template parts, patterns, style variations, and Site Editor troubleshooting (style hierarchy, overrides, caching).
wp-block-development
Use when developing WordPress (Gutenberg) blocks: block.json metadata, register_block_type(_from_metadata), attributes/serialization, supports, dynamic rendering (render.php/render_callback), deprecations/migrations, viewScript vs viewScriptModule, and @wordpress/scripts/@wordpress/create-block build and test workflows.
wp-abilities-api
Use when working with the WordPress Abilities API (wp_register_ability, wp_register_ability_category, /wp-json/wp-abilities/v1/*, @wordpress/abilities) including defining abilities, categories, meta, REST exposure, and permissions checks for clients.