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 commands/jnpiyush/agentx/prd-gengit clone --depth 1 https://github.com/jnPiyush/AgentXWrote 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/commands/jnpiyush/agentx/prd-gen)<a href="https://agentmods.dev/commands/jnpiyush/agentx/prd-gen"><img src="https://agentmods.dev/badge/commands/jnpiyush/agentx/prd-gen.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00012 | $0.00446 |
| Opus 5 | $0.00006 | $0.00223 |
| Sonnet 5 | $0.00002 | $0.00089 |
| Haiku 4.5 | $0.00001 | $0.00045 |
Grade A, and why
PRD Generation 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 today.
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.
What it actually says
PRD Generation Prompt
Context
You are a Product Manager agent generating a PRD for Epic #{{issue_number}}.
Instructions
1. Analyze the Epic
- Read the epic description thoroughly
- Identify the core problem being solved
- Understand the business value
2. Generate PRD Sections
Problem Statement
- What problem are we solving?
- Why is this important now?
- What happens if we don't solve it?
Target Users
- Primary persona (demographics, goals, pain points)
- Secondary personas if applicable
- User journey context
Goals and Success Metrics
- Primary business goal
- Measurable success criteria (KPIs)
- Timeframe for measurement
Requirements Prioritize using MoSCoW:
- P0 (Must Have): Core functionality
- P1 (Should Have): Important features
- P2 (Nice to Have): Enhancements
User Stories Format: "As a [user], I want [feature] so that [benefit]" Include acceptance criteria for each story.
User Flows
- Happy path flow diagram
- Error/edge case flows
- Entry and exit points
Out of Scope Explicitly list what is NOT included.
Risks and Mitigations
- Technical risks
- Business risks
- Timeline risks
3. Output Format
Create PRD at: docs/artifacts/prd/PRD-{{issue_number}}.md
Use template: .github/templates/PRD-TEMPLATE.md
4. Quality Checklist
- Problem is clearly defined
- Users are identified with personas
- Requirements are prioritized
- User stories have acceptance criteria
- Risks are identified with mitigations
- Out of scope is explicit
References
- Skills.md for standards
- AGENTS.md for workflow
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.
- today First seen · 81 lines · 12 tokens per session scan A 89c97c342a7d
PRD Generation is a command published in the GitHub repository jnPiyush/AgentX (15 stars, last pushed today), licensed Apache-2.0. It adds 12 tokens to every session and 446 once invoked, about $0.0001 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 2026-09-06.
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