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/corridortech/posecap/ad-auditnpx skills add CorridorTech/PoseCap --skill ad-auditgit clone --depth 1 https://github.com/CorridorTech/PoseCapWhat 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 | $0.00241 | $0.02463 |
| Opus 5 | $0.00120 | $0.01231 |
| Sonnet 5 | $0.00048 | $0.00493 |
| Haiku 4.5 | $0.00024 | $0.00246 |
Grade A, and why
ad-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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mechanical shape:
THIS SESSION:
1. Target + tree (what is under audit, and on which tree/SHA?).
2. Resolve the rule-set: repo binding docs (always) + curated store at
$AGENTIC_RULES_DIR or ~/.agentic/rules/ (optional) + project rules at
.agentic/rules/ (optional). The rule-set defines the groups and any
CRITICAL tag — never hardcode them.
3. Enumerate every group. For each: review it, or record explicit N/A + reason.
4. Write the assembled context to .agentic/reviews/<ISO>-audit-<scope>.md (audit trail).
5. Review each dispatched group in this session, as a checklist. Output one
section per group; give EVERY rule an explicit verdict.
6. Coverage matrix + verdict (never "approve") + rule-gap handoff to /ad-level-up.
The per-group checklist is the rigor: every rule gets a verdict, so a silent gap cannot masquerade as "all clear". A single-session reviewer with everything loaded can still rationalize — so for CRITICAL groups the skill recommends the user-initiated subagent escalation (Step 6), which restores true isolation and adds the cross-model pass.
<background_information>
The maximum quality gate. Where ad-review runs a light two-axis pass over a diff, ad-audit walks the project's whole rule-set as a checklist against a target bound for the team — proving every rule was checked, grounding every finding, and hardening critical rules with a second model. On Claude Code this is parallel Task subagents (one per group) plus a cross-model second pass; on Codex it is a single-session per-group checklist with a user-initiated subagent escalation for isolation and the cross-model pass. The rule-set location convention is ADR-0035; the mechanism is ADR-0036. It writes nothing to the rule-set — it audits, then hands genuine gaps to /ad-level-up.
</background_information>
Running ad-audit (Codex single-pass, per-group checklist). I will resolve the rule-set (repo binding docs + optional ~/.agentic/rules/ + optional .agentic/rules/ project layer), enumerate every group, write an audit trail to .agentic/reviews/, then give every rule an explicit verdict grouped by rule-group, with a coverage matrix. I never emit "approve".
NOTE on fidelity: a single session with everything loaded can rationalize across groups. For any group the rule-set marks CRITICAL, I will recommend the user-initiated subagent escalation at Step 6 — true isolation plus a cross-model pass against the persisted trail. The escalation TOML schema is at the bottom of this skill.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 94 lines · 241 tokens per session scan A 6e0527d0fd0a
ad-audit is a skill published in the GitHub repository CorridorTech/PoseCap (190 stars, last pushed 10d ago), licensed Apache-2.0. It adds 241 tokens to every session and 2,463 once invoked, about $0.0012 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 2026-08-30.
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