Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/evol-ai/skillcompass/setupgit clone --depth 1 https://github.com/Evol-ai/SkillCompassWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.03775 |
| Opus 5 | $0.00000 | $0.01887 |
| Sonnet 5 | $0.00000 | $0.00755 |
| Haiku 4.5 | $0.00000 | $0.00378 |
Grade B, and why
setup scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
After smart guidance, check if `~/.claude/settings.json` already has a `statusLine` configured. How it starts
The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/setup - Skill Inventory & Health Check
This command gives users a quick local inventory of installed skills and surfaces only high-signal issues. It supports two modes:
- Manual mode: the user explicitly runs
/setupor/skill-compass setup - Auto-trigger mode: first-run helper shown before another command
In auto-trigger mode, setup must never replace or derail the user's original request. Its job is to help briefly, save state, and return control to the dispatcher.
Step 1: Determine Mode and Load State
- Detect whether setup was invoked manually or as a first-run auto-trigger.
- If auto-triggered, preserve the original command name and arguments as
resume_commandandresume_args. - Use
.skill-compass/setup-state.jsonas the primary persisted state file. - For backward compatibility, if
.skill-compass/setup-state.jsonis missing but.skill-compass/.setup-doneexists, read the legacy marker and migrate the minimal fields intosetup-state.json. - Load the standard OpenClaw config file
~/.openclaw/openclaw.jsonif it exists. If present, read optional extra skill roots fromskills.load.extraDirs. - If setup was auto-triggered and a current setup state already exists, return control to the dispatcher immediately so it can continue the original command.
Step 2: Confirm Auto-Trigger (auto-trigger mode only)
When auto-triggered, ask the user first:
Quick skill inventory (~5 sec) before continuing
{resume_command}? [OK / Skip]
- If the user says
Skip:- Write
.skill-compass/setup-state.jsonwith{"version": 1, "skipped": true, "timestamp": "{ISO}"} - Also write
.skill-compass/.setup-donefor compatibility - Return control to the dispatcher immediately so it can continue the original command
- Write
- If the user agrees:
- Continue with setup
Manual /setup does not need this confirmation.
Step 3: Discover Skills
Build the scan root list in this priority order:
.claude/skills/(project-level Claude Code).openclaw/skills/(project-level OpenClaw, if present)- Each path listed in
skills.load.extraDirsfrom~/.openclaw/openclaw.json ~/.claude/skills/(user-level Claude Code)~/.openclaw/skills/(user-level OpenClaw, if present)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 361 lines · 0 tokens per session scan B 2b4f10e91c10
setup is a command published in the GitHub repository Evol-ai/SkillCompass (216 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,775 tokens. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
story-long-scan
长篇网文扫榜。分析起点、番茄、晋江等平台排行数据，提炼市场趋势。.
audit_docs
Audit all project metadata files for stale counts, version mismatches, broken references, and missing entries. Reports discrepancies without auto-fixing.
merge_session
Merge session branch(es) into main via rebase + fast-forward push. Use from inside a session worktree pane to land your work, or with --all to batch merge all sessions from the main repo.
cherry_pick_pr
Cherry-pick one or more commits onto a new branch from main and open a PR. Useful when a commit landed on the wrong branch or you want to split a multi-commit branch into separate PRs.
cti-report
Render case deliverables — relationship graph (PNG/SVG/Mermaid) and a polished PDF/DOCX assessment. Usage: /cti-report [--graph|--pdf].
reskin
Extract a measured design signature (type ramp, accent + its budget, grid unit, radius, layout) from a reference image or site, write it to signature.json, and drive the build to match it — "steal this vibe" as a spec, not pixels.