agentleFS
kimgeakimgea/agent-kit/skills/tool-audit/SKILL.md

tool-audit

Skill0 starsChanged 31 days agoMITView on GitHub

Audit CLI tooling on this machine and how Codex or Claude Code agents use tools across sessions. Use when asked what CLI tools are installed, which tools or subcommands agents use and how often, whether agents use tools efficiently, how commands split into read/write/destructive classes, which installed tools are unused, which MCP or tool calls fail, how usage changes over time, or which read-only commands might be safe permission candidates.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Before interpreting a result, read only the matching section of report-guide.md: inventory, snapshots and trends, permission configuration, …

    line 47
  2. Distinctive:

    Treat permission suggestions as narrow candidates for human review, never as proof that a prefix is safe.

    line 68
  3. Very specific:

    Keep ambiguous command classifications mixed.

    line 73

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

tool-audit

Answer tooling questions from real local data with the fixed profiles exposed by scripts/audit.py. Use direct helpers only when custom filters are required.

Bootstrap permissions safely

On first use or after relocating the skill, run python <skill-dir>/scripts/setup_permissions.py --agent <current-agent> without --install and show its proposal. Install only after explicit user approval by rerunning with --install --yes. The bootstrap approves only audit.py plus one enumerated, argument-free profile. Setup, arbitrary Python, direct helpers, version probes, catalog writes, and custom paths remain gated. More restrictive project or managed policies still win.

Restart Codex after installing Codex rules. Use an approved --remove --yes to remove only entries recorded by setup.

Select a fixed profile

QuestionProfile
What CLI tools are installed here?inventory or inventory-json
Include uncategorized toolsinventory-uncategorized or inventory-uncategorized-json
How are tools used across sessions?usage
Are agents using tools efficiently?usage-efficiency
Which way are usage trends moving?usage-trends
How is MCP used?usage-mcp
Which tool calls fail?usage-errors
Where do sessions, approvals, or autonomous loops create friction?usage-friction
Which tools have we forgotten?usage-forgotten
What should we allowlist next?config-suggest
Is permission config safe or consistent?config-lint
Audit config and suggest togetherconfig
Record, view, or compare tooling statesnapshot, snapshot-history, or snapshot-changes

Fixed profiles deliberately accept no passthrough arguments. For custom scope, invoke usage.py directly with --agent, --project, --since, or --until, or invoke config_audit.py with explicit custom arguments; those calls remain approval-gated.

Before interpreting a result, read only the matching section of report-guide.md: inventory, snapshots and trends, permission configuration, or session usage and failures.

Run the selected profile

Resolve <skill-dir> from the current skill location and invoke scripts by absolute path without changing directory. Use python3, python, or Windows py -3, whichever names Python 3 on the machine.

python <skill-dir>/scripts/audit.py usage-efficiency
python <skill-dir>/scripts/audit.py inventory
python <skill-dir>/scripts/audit.py config-lint
python <skill-dir>/scripts/audit.py snapshot

Preserve the safety boundary

  • Inventory profiles walk PATH without executing discovered programs. Run the approval-gated inventory_versions.py only when versions are actually needed.
  • Treat permission suggestions as narrow candidates for human review, never as proof that a prefix is safe. The reports propose rules but do not edit agent configuration.
  • Report transcript findings in aggregate. Never print or retain raw prompt samples, credentials, authorization values, or secret-bearing arguments.
  • Keep ambiguous command classifications mixed; do not broaden them merely to avoid permission prompts.
  • State report limitations instead of assigning wrapped or ambiguous events to the wrong command.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.