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 skills add jstoup111/ai-conductor --skill prd-auditgit clone --depth 1 https://github.com/jstoup111/ai-conductorWrote 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/jstoup111/ai-conductor/prd-audit)<a href="https://agentmods.dev/skills/jstoup111/ai-conductor/prd-audit"><img src="https://agentmods.dev/badge/skills/jstoup111/ai-conductor/prd-audit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jstoup111/ai-conductor/prd-audit"><img src="https://agentmods.dev/badge/skills/jstoup111/ai-conductor/prd-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 9 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 5.1 | $0.00045 | $0.02020 |
| Opus 5.5 | $0.00018 | $0.00808 |
| Sonnet 5.5 | $0.00009 | $0.00404 |
| Haiku 4.5 | $0.00005 | $0.00202 |
Grade A, and why
prd-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 19d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
At SHIP, judge whether the implementation was built as the feature stories specify. The stories' acceptance criteria are the authority. PRD functional requirements are intent context when a PRD exists; the plan's stated outcome is also intent context. This is a finding-authority: report grounded judgement and do not implement, amend DECIDE artifacts, append remediation tasks, or choose the gate route. The engine owns those mechanical outcomes.
Each criterion judgment carries exactly one grade: PASS | FIXABLE | PLAN_GAP | OVER_SCOPE.
Judgments must concern supplied active story criteria. An actual unowned OVER_SCOPE finding belongs
in a no-owner observation, not under an unrelated criterion. The engine validates references,
deduplicates findings, and rejects malformed results while retaining valid sibling judgments.
Per the /verify-claims protocol, cite concrete file:line evidence and give a confidence when
evidence is ambiguous. Do not turn uncertainty into a PASS.
Run at SHIP alongside the other SHIP validators. The configured step decides whether it is enabled; this skill does not infer a skip from feature tier, track, or the absence of a PRD.
Managed review
When the engine dispatches this skill, it supplies the bounded, versioned evidence projection and the terminal native structured-result shape. Treat those as the complete machine contract. Judge the supplied criteria against the supplied intent, change, task, and history evidence, then return one terminal structured judgment that conforms to the supplied shape.
Do not recreate engine input collection, infer routing authority, or substitute a Markdown report
for the terminal judgment. Do not write .pipeline/prd-audit.json, .pipeline/prd-audit.md,
accepted-widening state, operator decisions, or any other verdict artifact. The engine validates,
persists, renders, and routes the returned judgment.
For every supplied criterion, return grounded evidence and rationale with exactly one allowed grade. A FIXABLE judgment names exactly one supplied owner. An OVER_SCOPE judgment supplies its closed intent relation. Use a no-owner observation only for an actual unowned OVER_SCOPE finding. Never self-accept or refuse a finding.
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.
- 19d ago Changed · +2 lines 08c58a58f7ed
- 23d ago Changed · -68 lines 87ea3709339f
- 26d ago Changed · +5 lines 92877399f38c
- 1mo ago Changed 55417991d529
- 1mo ago Changed · -3 lines ecc1d713d2fb
- 1mo ago Changed · +43 lines 3fd9883ca6da
- 1mo ago Changed · +4 lines fe1fb6e6e272
- 1mo ago Changed · +11 lines ea57c585c2a4
- 1mo ago Changed · +4 lines e34828ee4047
- 2mo ago First seen · 139 lines · 45 tokens per session scan A 0e1e2a906075
prd-audit is a skill published in the GitHub repository jstoup111/ai-conductor (7 stars, last pushed today), licensed Apache-2.0. It adds 45 tokens to every session and 2,020 once invoked, about $0.0002 per session on Opus 5.5. 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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