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 skills/pantani/ableton-mind/command-surface-auditnpx skills add Pantani/ableton-mind --skill command-surface-auditgit clone --depth 1 https://github.com/Pantani/ableton-mindWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pantani/ableton-mind/command-surface-audit)<a href="https://agentmods.dev/skills/pantani/ableton-mind/command-surface-audit"><img src="https://agentmods.dev/badge/skills/pantani/ableton-mind/command-surface-audit.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00049 | $0.00314 |
| Opus 5 | $0.00024 | $0.00157 |
| Sonnet 5 | $0.00010 | $0.00063 |
| Haiku 4.5 | $0.00005 | $0.00031 |
Grade A, and why
command-surface-audit scanned grade A with 0 findings 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 4d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Command Surface Audit
Use this skill to build an evidence-backed command matrix from the current checkout.
Workflow
- Inventory commands from package.json scripts, bin entries, .github/workflows, docs snippets and scripts/.
- Classify each command as safe read/check, local mutating, external read, publish/write or hardware/live.
- Run safe commands. Use dry-run or check mode for packaging and release paths.
- Do not run publish/write commands without explicit user confirmation.
- Record exact failures with the command, output signature, source file and likely owner.
- Flag commands that exist in docs but not package.json, or package scripts that no workflow/docs can reach.
Report Format
Write _workspace/quality-audit/command-surface-{N}.md:
| Command | Source | Class | Status | Evidence | Notes |
|---|
End with:
- Broken commands.
- Stale or undocumented commands.
- Commands blocked by missing Live, hardware, credentials or external services.
- Suggested tests or docs changes.
Local Execution
When running locally from Codex, use rtk proxy <command> for raw commands. Keep raw command names in the report so CI/users can copy them.
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.
- 4d ago First seen · 35 lines · 49 tokens per session scan A 6050ccae74b4
command-surface-audit is a skill published in the GitHub repository Pantani/ableton-mind (5 stars, last pushed 2mo ago), licensed MIT. It adds 49 tokens to every session and 314 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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