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 | $0.03198 |
| Opus 5 | $0.00023 | $0.01599 |
| Sonnet 5 | $0.00009 | $0.00640 |
| Haiku 4.5 | $0.00005 | $0.00320 |
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 yesterday.
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 — 201 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 finding carries exactly one grade: PASS | FIXABLE | PLAN_GAP | OVER_SCOPE. Verdict Table
findings are keyed to active story criteria; no-owner OVER_SCOPE findings are keyed as NC.<n> in
their dedicated section below. The engine rejects malformed rows with a diagnostic while retaining
valid sibling rows. Never invent a key (OS.1, SCOPE.2) or write duplicate rows for one key.
Every Verdict Table key must be an id of an active story criterion. Use the form
S<story>.<criterion>; do not use NC.<n> in the Verdict Table. A well-formed story key that
names no criterion in the active stories is also invalid.
<story> is the story's heading id verbatim, not just its digits — ## Story 5a: owns S5a.1,
S5a.2, … and ## Story 2.1: owns S2.1.1, S2.1.2, …, each distinct from Story 5's and Story
2's. <criterion> is always the numeric ordinal. Keys are matched case-insensitively.
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.
Inputs and authority
- Resolve the feature's committed stories through the active plan's
**Stories:**reference. Read every happy and negative criterion. If criteria cannot be read, report a BLOCKED audit that names the stories file; never pass by default. - Read the active plan, including its stated outcome and task ownership. Where a committed coherence mapping exists, use it to understand criterion-to-intent traceability.
- Read the matching non-
SUPERSEDED-PRD when present. Its FRs explain intent; they do not replace story criteria as the audit key. A PRD requirement without story coverage is aPLAN_GAPfinding against that requirement's missing criterion/traceability, not a silently omitted FR. - Read the implementation, changed tests, and relevant BUILD
Scope:trailers. Trace each criterion to concrete behavior or its absence.
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.
- yesterday Changed · +43 lines 3fd9883ca6da
- 2d ago Changed · +4 lines fe1fb6e6e272
- 4d ago Changed · +11 lines ea57c585c2a4
- 5d ago Changed · +4 lines e34828ee4047
- 9d 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 3,198 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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