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 Orkas-AI/Orkas-Awesome-AgentSkills --skill product-prdgit clone --depth 1 https://github.com/Orkas-AI/Orkas-Awesome-AgentSkillsWrote 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/orkas-ai/orkas-awesome-agentskills/product-prd)<a href="https://agentmods.dev/skills/orkas-ai/orkas-awesome-agentskills/product-prd"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/product-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/orkas-ai/orkas-awesome-agentskills/product-prd"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/product-prd.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00081 | $0.00952 |
| Opus 5 | $0.00041 | $0.00476 |
| Sonnet 5 | $0.00016 | $0.00190 |
| Haiku 4.5 | $0.00008 | $0.00095 |
Grade A, and why
product-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 9d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product PRD
Use this skill to turn product ideas, research, and solution context into an engineering-readable PRD. A good PRD explains what to build and why, defines success, sets scope boundaries, and gives downstream teams enough context without over-defining implementation.
Do not use this skill for early opportunity validation, detailed Given/When/Then acceptance criteria, design briefs, engineering task breakdowns, code plans, or implementation. Hand those to adjacent skills.
When To Use
- Problem and solution direction are already roughly aligned.
- A feature, epic, or product initiative needs stakeholder review.
- Engineering, design, QA, or leadership need a shared PRD.
- Scope, goals, metrics, risks, and open questions need to be made explicit before build work.
If the user is still asking whether the product direction is worth pursuing, stay at the product analysis stage instead of writing a PRD.
Instructions
- Capture inputs and assumptions: list source materials, missing context, and assumptions before writing requirements.
- Summarize the problem: explain the user/business problem and why now.
- Define goals and success metrics: connect each metric to the problem being solved.
- Outline the solution: focus on user-facing behavior and key capabilities.
- Write testable requirements: group functional requirements and include non-functional needs when relevant.
- Define scope boundaries: explicitly state in scope, out of scope, and future considerations.
- Surface technical considerations: constraints, integrations, data, privacy, performance, reliability, or migration concerns; do not design the system.
- Identify dependencies and risks: include owners, impact, and mitigation where known.
- End with handoff: point to the next stage and state what is still missing.
Output Format
Use references/prd-template.md as the default structure. Keep the PRD concise enough to read in about 15 minutes unless the user asks for a deeper PRD.
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.
- 9d ago First seen · 67 lines · 81 tokens per session scan A 3785a26496fe
product-prd is a skill published in the GitHub repository Orkas-AI/Orkas-Awesome-AgentSkills (13 stars, last pushed 2mo ago), licensed MIT. It adds 81 tokens to every session and 952 once invoked, about $0.0004 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 2026-09-03.
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