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 adrielp/ai-engineering-harness --skill write_a_prdgit clone --depth 1 https://github.com/adrielp/ai-engineering-harnessWrote 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/adrielp/ai-engineering-harness/write_a_prd)<a href="https://agentmods.dev/skills/adrielp/ai-engineering-harness/write_a_prd"><img src="https://agentmods.dev/badge/skills/adrielp/ai-engineering-harness/write_a_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/adrielp/ai-engineering-harness/write_a_prd"><img src="https://agentmods.dev/badge/skills/adrielp/ai-engineering-harness/write_a_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 | $0.00060 | $0.00652 |
| Opus 5.5 | $0.00024 | $0.00261 |
| Sonnet 5.5 | $0.00012 | $0.00130 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
write_a_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.
This is a copy
86% identical to write-a-prd — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This skill will be invoked when the user wants to create a PRD. You may skip steps if you don't consider them necessary.
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Ask the user for a long, detailed description of the problem they want to solve and any potential ideas for solutions.
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Explore the repo to verify their assertions and understand the current state of the codebase.
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Interview the user relentlessly about every aspect of this plan until you reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one.
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Sketch out the major modules you will need to build or modify to complete the implementation. Actively look for opportunities to extract deep modules that can be tested in isolation.
A deep module (as opposed to a shallow module) is one which encapsulates a lot of functionality in a simple, testable interface which rarely changes.
Check with the user that these modules match their expectations. Check with the user which modules they want tests written for.
- Once you have a complete understanding of the problem and solution, use the template below to write the PRD. The PRD should be written as a local markdown file at
issues/prd.md. Create theissues/directory if it doesn't exist. Do NOT submit a GitHub issue or call any external service.
Problem Statement
The problem that the user is facing, from the user's perspective.
Solution
The solution to the problem, from the user's perspective.
User Stories
A LONG, numbered list of user stories. Each user story should be in the format of:
- As an , I want a , so that
This list of user stories should be extremely extensive and cover all aspects of the feature.
Implementation Decisions
A list of implementation decisions that were made. This can include:
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 · 76 lines · 60 tokens per session scan A 3d9aab6ade53
write_a_prd is a skill published in the GitHub repository adrielp/ai-engineering-harness (22 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 60 tokens to every session and 652 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to write-a-prd, differing in 7 lines, and is treated as a copy.
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