Borrowing it
Nothing to install: this file belongs to CorridorTech/PoseCap. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/CorridorTech/PoseCap/main/.agents/skills/ad-prd/SKILL.mdgit clone --depth 1 https://github.com/CorridorTech/PoseCapWrote 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/corridortech/posecap/ad-prd)<a href="https://agentmods.dev/skills/corridortech/posecap/ad-prd"><img src="https://agentmods.dev/badge/skills/corridortech/posecap/ad-prd/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/corridortech/posecap/ad-prd"><img src="https://agentmods.dev/badge/skills/corridortech/posecap/ad-prd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00184 | $0.02041 |
| Opus 5.5 | $0.00074 | $0.00816 |
| Sonnet 5.5 | $0.00037 | $0.00408 |
| Haiku 4.5 | $0.00018 | $0.00204 |
Grade A, and why
ad-prd 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 2mo 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<background_information>
Layer 3 of the artifact stack. Lazy lifecycle owner of the PRD (Product Requirements Document). One product = one PRD; multi-product repos use a PRODUCT-MAP.md index plus per-product <slug>.md files.
PRD is product-level scope, not feature-level scope. A feature spec (ad-spec, Layer 4) implements part of a PRD; a PRD is never implemented by a single task. If the user's ask is single-feature, route to ad-spec instead.
Codex auto-trigger on description keywords is less mature than Claude Code's. If auto-invocation does not fire when the user mentions PRD, product requirements, target user, product roadmap, or product success metrics, invoke this skill manually. </background_information>
Route elsewhere when:
- Scope is one feature →
ad-spec(Layer 4). - Scope is a vocabulary question →
ad-domain(Layer 2). - Scope is an architectural decision →
ad-adr. - Scope is fuzzy and needs interview-before-research →
ad-grill-me, which can route back here once the product framing is sharp.
A spike or PoC does not need a PRD — the skill is excluded from the poc profile. If the user is on poc profile and invokes ad-prd, ask explicitly whether the project has graduated to solo or team before writing.
Step 1 — codebase-first scan. Before asking a single question, look. The repo often answers half the fields.
- Check
doc/product/— does a PRD already exist? - Read
AGENTS.md## Project Overview— pulls product name, one-line description, deployment target. - Read
README.mdhead — pulls product framing for users who land via the public README. - Read
CONTEXT.mdif it exists — anchors the canonical nouns the PRD must use. - Read
doc/specs/index — existing feature specs surface the implicit product scope. - Read
package.jsonname/description/keywordsfor product framing signal.
Only after the scan produces no answer does the skill ask the user. Asking the user about something the repo already states wastes their attention.
Step 2 — determine slug and target file. Single product (default): doc/product/PRD.md. Multi-product: ask whether this is a multi-product repo; if yes, file path is doc/product/<product-slug>.md and a doc/product/PRODUCT-MAP.md index lists each product. Slug: kebab-case, ≤4 words, derived from the product name.
Status starts at draft. Created: today, ISO format. Updated: today, ISO format. Owner: ask once — defaults to the repo's primary committer (from git config user.name) if unset.
Step 3 — interview to fill. Ask one question at a time, in this order. Skip questions whose answers are already obvious from the Step 1 scan; surface what the scan found and ask only for confirmation.
If the product framing is vague ("improve efficiency", "build a dashboard", "use AI", "make it easier"), run a short sharpening pass before filling the PRD fields. Keep these as facilitation notes, not PRD sections:
- Today statement. "Today,
<target user>must<painful workflow>when<trigger>. They need a way to<unmet need>." - How Might We. Reframe the problem broad enough to allow multiple solutions, narrow enough to exclude generic improvement.
- North Star. "Deploy
<what>to change<metric 1>and<metric 2>so that<ultimate outcome>." Require baseline, target, and measurement source when available.
If the user starts with a solution, validate it against the Today statement and North Star before accepting it into Roadmap. If it serves a different user, fails to move the named metrics, or prescribes implementation before the problem is clear, route back to ad-grill-me.
- Product. Name and one-sentence positioning. "X is a Y that does Z for W."
- Target User. Specific role / persona, not "developers" or "users". Cite the primary success-bearing user; secondary users go under Personas if they affect the product shape.
- Problem. What the target user can't do today, or does badly today. The cost of the status quo. "What breaks if this product does not exist?"
- Goals. 3–5 measurable outcomes the product is for. State each as a plain bullet (no checkbox — PRD is definition, not tracking). Pass/fail must be observable; tracking of whether each goal is met lives in per-feature tasks.
- Non-goals. Explicit out-of-scope items readers might assume are in scope. Prevents scope creep without an audit trail.
- Success Metrics. Product-level KPIs — measurable and durable, not procedural. "Weekly active users above N at 90 days" — yes. "Users love it" — no. Each metric carries the measurement source.
- Roadmap. Multi-feature scope. Each line names a feature, the user value it carries, and the (rough) sequence. Concrete enough to drive
ad-speclater; not a binding commitment. MarkMVP,Next,Later; no dates. - Constraints. What binds across the entire product — regulatory, business, technical. Skip if none; do not invent.
- Personas (optional). If the product has secondary users whose needs reshape it. Skip when one persona drives everything.
- Open Questions. Deferred decisions. Each line becomes a future ADR, a spec-time decision, or an explicit punt with rationale.
- Related. ADRs touched, feature specs implementing parts of it, other PRDs this one supersedes. Filled lazily.
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.
- 2mo ago First seen · 90 lines · 184 tokens per session scan A 1690b5d57f66
ad-prd is a skill published in the GitHub repository CorridorTech/PoseCap (265 stars, last pushed 3d ago), licensed Apache-2.0. It adds 184 tokens to every session and 2,041 once invoked, about $0.0007 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 2026-08-30.
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