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 smallnest/pigo --skill prdgit clone --depth 1 https://github.com/smallnest/pigoWrote 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/smallnest/pigo/prd)<a href="https://agentmods.dev/skills/smallnest/pigo/prd"><img src="https://agentmods.dev/badge/skills/smallnest/pigo/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/smallnest/pigo/prd"><img src="https://agentmods.dev/badge/skills/smallnest/pigo/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 | $0.00106 | $0.02479 |
| Opus 5.5 | $0.00042 | $0.00992 |
| Sonnet 5.5 | $0.00021 | $0.00496 |
| Haiku 4.5 | $0.00011 | $0.00248 |
Grade A, and why
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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- prd — 86% identical, 25 lines differ
How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PRD Generator
Create detailed Product Requirements Documents that are clear, actionable, and suitable for implementation. After PRD is confirmed, use /to-issues to decompose it into Issues, and optionally /prd-to-spec for technical design before that.
The Job
- Receive a feature description from the user
- Ask clarifying questions to cover key ambiguities — scale the count to complexity, not a fixed number (see Step 1)
- Generate a structured PRD based on answers
- Present PRD to user for review — ask "Please review the PRD. Let me know if any adjustments are needed, or reply OK to confirm."
- Apply any adjustments, then save to
tasks/prd-[feature-name].md - Suggest next steps (see Step 3)
Important: Do NOT start implementing. Just create the PRD.
Step 1: Clarifying Questions
Ask only critical questions where the initial prompt is ambiguous. Scale the number of questions to the feature's complexity — the goal is covering key ambiguities, not hitting a fixed count:
- Simple, well-scoped feature: 2-3 questions
- Typical feature: 3-5 questions
- Complex feature (multiple user roles, cross-system integration, significant ambiguity): 6-8 questions
If a dimension is already unambiguous from the user's input, skip it — don't ask filler questions just to reach a number. Focus on:
- Problem/Goal: What problem does this solve?
- Core Functionality: What are the key actions?
- Scope/Boundaries: What should it NOT do?
- Success Criteria: How do we know it's done?
Format Questions Like This:
1. What is the primary goal of this feature?
A. Improve user onboarding experience
B. Increase user retention
C. Reduce support burden
D. Other: [please specify]
2. Who is the target user?
A. New users only
B. Existing users only
C. All users
D. Admin users only
3. What is the scope?
A. Minimal viable version
B. Full-featured implementation
C. Just the backend/API
D. Just the UI
What ships with it
3 files 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.
- 1mo ago First seen · 279 lines · 106 tokens per session scan A b028343a2db3
prd is a skill published in the GitHub repository smallnest/pigo (483 stars, last pushed 1mo ago), licensed MIT. It adds 106 tokens to every session and 2,479 once invoked, about $0.0004 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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