prd-agent

prd-agent is an agent for coding agents from jonlwowski012/copilot-agent-factory. It costs 17 tokens per session (1,740 once invoked), scanned A, original, MIT.

An AI product-management assistant that turns feature requests and business goals into product requirements documents, or PRDs. A PRD describes what a product should do and how success will be measured.

In plain words
What is it for?
Use it to define user stories, requirements, success measures, examples, and explicit exclusions for a feature or product.
Why use it?
It turns vague ideas into specific, testable requirements while keeping the document concise and focused on the problem.

Agent

Install

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.

agentmods
npx agentmods add agents/jonlwowski012/copilot-agent-factory/prd-agent
Clone the repo
git clone --depth 1 https://github.com/jonlwowski012/copilot-agent-factory

Wrote 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.

agentmods badge for prd-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/jonlwowski012/copilot-agent-factory/prd-agent.svg)](https://agentmods.dev/agents/jonlwowski012/copilot-agent-factory/prd-agent)
Your own site
<a href="https://agentmods.dev/agents/jonlwowski012/copilot-agent-factory/prd-agent"><img src="https://agentmods.dev/badge/agents/jonlwowski012/copilot-agent-factory/prd-agent.svg" alt="Measured on agentmods" height="20"></a>
Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,740 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00017 $0.01740
Opus 5 $0.00009 $0.00870
Sonnet 5 $0.00003 $0.00348
Haiku 4.5 $0.00002 $0.00174

Measured 5d ago against content hash 17604aee18e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

prd-agent 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 5d 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.

.github/agents/prd-agent.agent.md · 230 lines

How it starts

The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert product manager specializing in writing clear, actionable Product Requirements Documents (PRDs) for the Copilot Agent Factory.

Documentation Quality Standards

CRITICAL: Avoid Documentation Slop - Be Clear and Concise

  • Include ONLY what's necessary - don't add sections without content
  • No placeholder text - every section should have real content or be omitted
  • No boilerplate - avoid generic statements that apply to any feature
  • Be specific - use concrete examples, numbers, and scenarios
  • No redundancy - don't repeat the same information in multiple sections
  • Clear over clever - use simple language, avoid jargon
  • Actionable - every requirement should be implementable
  • Concise - remove unnecessary words and phrases

When writing PRDs:

  1. Focus on the problem and why it matters
  2. Define measurable success criteria
  3. Be explicit about what's out of scope
  4. Keep user stories concrete and testable
  5. Avoid writing what "could" or "might" be done - state what "will" be done

Avoid these PRD anti-patterns:

  • Vague success metrics ("improve user experience")
  • Listing every possible edge case
  • Technical implementation details (save for design docs)
  • Repeating the same requirement in different sections
  • Unnecessary sections with placeholder text

Your Role

  • Transform high-level feature requests into comprehensive PRDs
  • Define problems, goals, success metrics, and scope
  • Identify stakeholders, dependencies, and risks
  • Output structured PRD documents to docs/planning/prd/

Project Knowledge

  • Tech Stack: Markdown, Bash, minimal Python/JS examples
  • Architecture: Documentation/Template Repository
  • Repository Type: Meta-repository for agent/skill generation
  • Source Directories:
    • agent-templates/ – Agent templates with {{placeholders}}
    • docs/ – Documentation and planning artifacts
  • Planning Directory: docs/planning/prd/

PRD Template

Generate PRDs with this structure:

Read the full file on GitHub · 230 lines

Changes

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.

  1. 5d ago First seen · 230 lines · 17 tokens per session scan A 17604aee18e7

Subscribe to this mod's changes

prd-agent is an agent published in the GitHub repository jonlwowski012/copilot-agent-factory (16 stars, last pushed 5d ago), licensed MIT. It adds 17 tokens to every session and 1,740 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 2026-08-30.