Agent skill

Skill Stocktake

by affaan-m in affaan-m/ECC

Audits your installed Claude skills and commands for quality, with a quick mode for recently changed skills and a full mode that evaluates all of them through subagents.

MITAuto-check passedAgent Workflows

Install Skill Stocktake

skills CLI
$ npx skills add affaan-m/ECC --skill skill-stocktake -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC skill-stocktake --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skill-stocktake .claude/skills/skill-stocktake && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
skill-stocktake
GitHub stars
277k
Used in
5 other repos
Token cost
~3.1k tokens
SKILL.md length
1,206 words
Files
4 (incl. scripts)
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

Audits your installed Claude skills and commands for quality, with a quick mode for recently changed skills and a full mode that evaluates all of them through subagents.

  • Works in 4 steps: Inventory → Quality Evaluation → Summary Table → …
  • Reviewing the quality of every skill and command you have installed
  • SKILL.md covers Scope, Modes, Quick Scan Flow and Full Stocktake Flow, plus 2 more sections
  • Runs Shell scripts from its folder; calls bash and jq

What it does

This slash command, /skill-stocktake, reviews the skills in ~/.claude/skills/ and, when run from a project root, the project's .claude/skills/ folder as well. It combines a quality checklist with an AI judgment of each skill, and it starts by listing which paths it found and scanned.

Quick Scan is the default when a results.json cache exists: quick-diff.sh finds the skills changed since the last run, only those are re-evaluated, unchanged results carry forward and the output shows only the difference. Full Stocktake runs when the cache is missing or you pass full. There scan.sh lists the skill files, reads their frontmatter and collects modification times, and the evaluation runs in sequential subagent batches. save-results.sh writes the cache to ~/.claude/skills/skill-stocktake/results.json. A quick scan takes about 5 to 10 minutes and a full one 20 to 30.

When your agent uses it

  • Reviewing the quality of every skill and command you have installed
  • Re-checking only the skills that changed since the last audit
  • Running a periodic review of a project's .claude/skills folder

Example prompts

  • “Run /skill-stocktake full from this project's root so the project skills are included.”
  • “Run a quick stocktake and show only the skills that changed since the last run.”
  • “Audit my global Claude skills and give me the inventory table.”

Requirements

  • Bash, to run the bundled scan.sh, quick-diff.sh and save-results.sh scripts
  • Skills installed under ~/.claude/skills/

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Inventory
  2. Quality Evaluation
  3. Summary Table
  4. Consolidation

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • bash
    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Skill Stocktake loads about 3.1k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 1,206 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~46
When it runs · the whole SKILL.md, loaded when a task matches
~3.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 1,206 words, ~3,090 tokens.

Download SKILL.mdSave it as .claude/skills/skill-stocktake/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
skill-stocktake
description
Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.
metadata.origin
ECC

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:

PathDescription
~/.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.

Directories named .trash are excluded from both scan modes: archived skills are not part of the live inventory. If an older results.json contains .trash entries, start a new Full Stocktake using the cache initialization below before resuming Quick Scan. An ordinary save merges entries and does not remove archived records.

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

ModeTriggerDuration
Quick Scanresults.json exists (default)5–10 min
Full Stocktakeresults.json absent, or /skill-stocktake full20–30 min

The shell scripts require Bash, Node.js, and jq on PATH.

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).

  1. Read ~/.claude/skills/skill-stocktake/results.json
  2. Run: bash ~/.claude/skills/skill-stocktake/scripts/quick-diff.sh \ ~/.claude/skills/skill-stocktake/results.json (Project dir is auto-detected from $PWD/.claude/skills; pass it explicitly only if needed)
  3. If output is []: report "No changes since last run." and stop
  4. Re-evaluate only those changed files using the same Phase 2 criteria
  5. Carry forward unchanged skills from previous results
  6. Output only the diff
  7. Run: bash ~/.claude/skills/skill-stocktake/scripts/save-results.sh \ ~/.claude/skills/skill-stocktake/results.json <<< "$EVAL_RESULTS"

Full Stocktake Flow

Phase 1 — Inventory

Run this entire block in one Bash invocation. It prints the inventory for the agent and initializes a new full run only when there is no unfinished run to resume:

bash
(
  set -euo pipefail
  SCAN_JSON=$(bash ~/.claude/skills/skill-stocktake/scripts/scan.sh)
  printf '%s\n' "$SCAN_JSON"
  RESULTS_JSON=~/.claude/skills/skill-stocktake/results.json

  CACHE_STATUS=""
  if [[ -f "$RESULTS_JSON" ]]; then
    CACHE_STATUS=$(jq -r '.batch_progress.status // ""' "$RESULTS_JSON")
  fi
  if [[ "$CACHE_STATUS" == "in_progress" ]]; then
    RESUMED_RESULTS=$(jq --slurpfile saved "$RESULTS_JSON" '
      . as $inventory | $saved[0]
      | .skills = (.skills | to_entries
        | map(.key = (.value.path // .key))
        | map(select(. as $entry
          | $entry.value.mtime != null
            and any($inventory.skills[];
              .path == $entry.key and .mtime == $entry.value.mtime)))
        | from_entries)
      | .mode = "full"
      | .batch_progress = {
          total: ($inventory.skills | length),
          evaluated: (.skills | length), status: "in_progress"
        }
    ' <<< "$SCAN_JSON")
    bash ~/.claude/skills/skill-stocktake/scripts/save-results.sh \
      "$RESULTS_JSON" --replace <<< "$RESUMED_RESULTS"
  else
    INITIAL_RESULTS=$(printf '%s\n' "$SCAN_JSON" | jq '{
      mode: "full", skills: {},
      batch_progress: {total: (.skills | length), evaluated: 0, status: "in_progress"}
    }')
    bash ~/.claude/skills/skill-stocktake/scripts/save-results.sh \
      "$RESULTS_JSON" --replace <<< "$INITIAL_RESULTS"
  fi
)

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)
Skill7d use30d useDescription

Usage counts come from the optional ~/.claude/observations.jsonl file (overridable with SKILL_STOCKTAKE_OBSERVATIONS), which Claude Code does not create by default. When the file is absent, use_7d and use_30d are JSON null; display them as unmeasured in inventory and summary tables. A numeric 0 means the file exists but contains no matching Read observations in that window. Missing usage data is never evidence for retiring a skill.

--replace writes a complete cache snapshot. A new run starts with an empty evaluation; a resumed run instead keeps a saved evaluation only when its path is still live and its saved, non-null mtime matches the fresh inventory. Changed skills and entries without an mtime require re-evaluation. It removes archived/deleted entries and refreshes the progress counts even when no new batch remains. Existing name-keyed entries are normalized using their saved path. Never use the empty initialization payload for a resume. Later chunks, completion updates, and Quick Scans must omit --replace so they merge into the current run instead of losing earlier results.

Phase 2 — Quality Evaluation

Launch an Agent tool subagent (general-purpose agent) with the actual JSON emitted by Phase 1 and the checklist below. Copy the inventory values into the prompt itself; shell variables do not carry over into Agent calls. Include the full inventory for overlap checks and explicitly identify the paths in the current batch to evaluate. Do not send literal inventory or checklist placeholders.

The subagent reads each assigned skill, applies the checklist, and returns a JSON object with a skills map keyed by the inventory path. Each entry includes its path, scanned mtime, verdict, and self-contained reason. Use the same path keys across all batches so merging results cannot overwrite a different skill with the same name.

Chunk guidance: Process ~20 skills per subagent invocation to keep context manageable. After each chunk, wrap its returned skills map with mode: "full" and batch_progress: {total, evaluated, status: "in_progress"}. Set total to the inventory size and evaluated to the cumulative number of distinct evaluated paths, including saved batches. Assign this JSON to CHUNK_RESULTS and run the following command in the same Bash invocation as that assignment:

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

After all skills are evaluated, persist completion before proceeding to Phase 3:

bash
(
  set -euo pipefail
  RESULTS_JSON=~/.claude/skills/skill-stocktake/results.json
  COMPLETED_RESULTS=$(jq -e '
    if (.skills | length) == .batch_progress.total then
      {skills: {}, mode: "full", batch_progress: (.batch_progress + {
        evaluated: (.skills | length), status: "completed"
      })}
    else error("Inventory still has unevaluated skills") end
  ' "$RESULTS_JSON")
  bash ~/.claude/skills/skill-stocktake/scripts/save-results.sh \
    "$RESULTS_JSON" <<< "$COMPLETED_RESULTS"
)

Resume detection: If status: "in_progress" is found on startup, run Phase 1 to reconcile the saved results with the fresh inventory, then evaluate only paths absent from the reconciled skills map. If none remain, persist completion immediately. Completed evaluations are preserved only for surviving paths with matching, non-null mtimes; new or changed skills and entries without an mtime require evaluation.

Show full SKILL.md (437 more words)Show less

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 when measured; missing observations marked unmeasured, not treated as zero

Verdict criteria:

VerdictMeaning
KeepUseful and current
ImproveWorth keeping, but specific improvements needed
UpdateReferenced technology is outdated (verify with WebSearch)
RetireLow 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
Skill7d useVerdictReason
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

~/.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": {
    "~/.claude/skills/skill-name/SKILL.md": {
      "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

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in skills/skill-stocktake of affaan-m/ECC.

  • SKILL.md
  • scripts/quick-diff.sh
  • scripts/save-results.sh
  • scripts/scan.sh

Open the folder on GitHubat commit 2d515e4

Used in 5 other repositories

We found 10 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 5 other GitHub owners. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 9, 2026.

Compare with similar skills

Skill Stocktake next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Skill Stocktake compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Skill Stocktake this skillaffaan-m/ECC277k5 repos~3.1kAutomated safety check: PassMIT
Task Observerrebelytics/one-skill-to-rule-them-all3.2k1 repos~11kAutomated safety check: PassCC-BY-4.0
Kimi Code DelegationCherryHQ/cherry-studio53k—~504Automated safety check: PassAGPL-3.0
Dotagentsgetsentry/dotagents251—~1.8kAutomated safety check: PassMIT
Subagentethanhq/cc-fleet216—~4.3kAutomated safety check: PassApache-2.0
Teamethanhq/cc-fleet216—~3.4kAutomated safety check: PassApache-2.0

Similar skills

  • Task Observer

    rebelytics/one-skill-to-rule-them-all

    Monitors task execution for skill improvement opportunities.

    3.2k GitHub starsUsed in 1 repo~11k tokens
    Agent WorkflowsAuto-check passed
  • Kimi Code Delegation

    CherryHQ/cherry-studio

    Delegates one bounded repository task to Kimi Code in non-interactive prompt mode and reads back the final result from its JSON event stream.

    53k GitHub stars~504 tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Dotagents

    getsentry/dotagents

    Official

    Manage dotagents dependencies and runtime config. An agent skill from getsentry/dotagents.

    251 GitHub stars~1.8k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Subagent

    ethanhq/cc-fleet

    Run a one-shot or flat parallel batch of provider LLM subagents (headless cc-fleet subagent) that return a result.

    216 GitHub stars~4.3k tokensUpdated 12 days ago
    Agent WorkflowsAuto-check passed
  • Team

    ethanhq/cc-fleet

    Spawn long-lived provider LLM teammates in tmux panes that you message via the native agent-team tools — multi-turn, collaborative, watchable.

    216 GitHub stars~3.4k tokensUpdated 12 days ago
    Agent WorkflowsAuto-check passed
  • Workflow

    ethanhq/cc-fleet

    Orchestrate a MULTI-PHASE, dependent, or resumable run over many provider subagents from a JS script, off the main context (cc-fleet workflow).

    216 GitHub stars~5.3k tokensUpdated 12 days ago
    Agent WorkflowsAuto-check passed

More from affaan-m/ECC

All 682 skills in this repo
  • Ingests, indexes, searches, edits and monitors video, audio and live streams through the VideoDB Python SDK, returning stream links, clips and timestamps.

    277k GitHub starsUsed in 3 repos~3.5k tokens
    Auto-check: notes
  • Docs Governance

    affaan-m/ECC

    Route broad documentation-governance requests to existing ECC skills and run an opt-in, read-only audit of mapped documentation roles, links, ADR indexes, and evidence references.

    277k GitHub stars~1.1k tokensUpdated today
    Auto-check passed
  • Rules Distillation

    affaan-m/ECC

    Scans installed skills for principles that recur across them and proposes rule-file changes: append, revise, add a section, create a file or leave as covered.

    277k GitHub starsUsed in 2 repos~2.3k tokens
    Auto-check passed
  • Builds DRAFT counterparty agreements from one markdown template and a small JSON spec per party, with clauses picked by the party's role.

    277k GitHub stars~2.9k tokensUpdated today
    Auto-check passed
  • Set an ECC-specific frontend design direction for production UI work.

    277k GitHub starsUsed in 1 repo~2.2k tokens
    Auto-check passed
  • Measures whether agents actually follow a skill, rule or agent definition by generating scenarios at three strictness levels and scoring tool-call traces.

    277k GitHub starsUsed in 1 repo~623 tokens
    Auto-check passed

Works with

Categories

Questions about Skill Stocktake

What does Skill Stocktake do?

Audits your installed Claude skills and commands for quality, with a quick mode for recently changed skills and a full mode that evaluates all of them through subagents. claude/skills/ folder as well. It combines a quality checklist with an AI judgment of each skill, and it starts by listing which paths it found and scanned.

When should I use Skill Stocktake?

Skill Stocktake fits situations like: reviewing the quality of every skill and command you have installed; re-checking only the skills that changed since the last audit; running a periodic review of a project's .claude/skills folder.

How do I install Skill Stocktake in Claude Code?

Run `npx skills add affaan-m/ECC --skill skill-stocktake -a claude-code`. Or copy the skill folder (skills/skill-stocktake in affaan-m/ECC) into .claude/skills/skill-stocktake in your project. Claude Code loads it when a task matches its description.

How do I install Skill Stocktake in Codex?

Run `npx skills add affaan-m/ECC --skill skill-stocktake -a codex`. Or copy the skill folder (skills/skill-stocktake in affaan-m/ECC) into .agents/skills/skill-stocktake in your project. Codex loads it when a task matches its description.

Can I use Skill Stocktake in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill skill-stocktake -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-stocktake, .gemini/skills/skill-stocktake, .github/skills/skill-stocktake and .opencode/skills/skill-stocktake in your project.

What does Skill Stocktake need to run?

Going by SKILL.md and its folder, Skill Stocktake needs a shell for the scripts in its folder and the command-line tools its instructions call (bash and jq). Our summary lists: Bash, to run the bundled scan.sh, quick-diff.sh and save-results.sh scripts; Skills installed under ~/.claude/skills/.

Does Skill Stocktake access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Skill Stocktake safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Skill Stocktake use?

Skill Stocktake is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Skill Stocktake use?

About 3.1k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Skill Stocktake?

Skills that share tags, products or a category with Skill Stocktake: Task Observer (rebelytics/one-skill-to-rule-them-all, 3.2k stars), Kimi Code Delegation (CherryHQ/cherry-studio, 53k stars), Dotagents (getsentry/dotagents, 251 stars) and Subagent (ethanhq/cc-fleet, 216 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skill Stocktake?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.