prd

prd is a skill for Claude Code, Codex from ashtonian/llm-init. It costs 12 tokens per session (972 once invoked), scanned A, original, MIT.

An interactive process for creating a product requirements document, which describes what a product or feature should do, and then breaking it into sized task files. It asks structured questions about users, scope, technical choices, dependencies, and constraints.

In plain words
What is it for?
Use it to define an MVP or larger feature, document its requirements, and create tasks for agent-team execution.
Why use it?
It turns a feature idea into an implementation plan that a development team can execute. This makes the intended scope and work items clearer before coding starts.

Skill for Claude CodeCodex

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 skills/ashtonian/llm-init/prd
Any agent
npx skills add ashtonian/llm-init --skill prd
Clone the repo
git clone --depth 1 https://github.com/ashtonian/llm-init

Made for: Claude Code, Codex.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/ashtonian/llm-init/prd.svg)](https://agentmods.dev/skills/ashtonian/llm-init/prd)
Your own site
<a href="https://agentmods.dev/skills/ashtonian/llm-init/prd"><img src="https://agentmods.dev/badge/skills/ashtonian/llm-init/prd.svg" alt="Measured on agentmods" height="20"></a>
Per session 12 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 972 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 $0.00012 $0.00972
Opus 5 $0.00006 $0.00486
Sonnet 5 $0.00002 $0.00194
Haiku 4.5 $0.00001 $0.00097

Measured 3d ago against content hash c7a318b0d99b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 3d 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.

templates/.claude/skills/prd/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interactive PRD-to-tasks pipeline. Generate a Product Requirements Document from a feature description, then convert it into sized task files for agent team execution.

Instructions

Work through 3 phases. Present options with lettered choices (A, B, C, D) for quick user responses.

Phase 1: Interactive Discovery

Conduct a focused Q&A to understand the feature. Ask 2-3 questions per round, max 4 rounds.

Round 1 -- Scope & Users

  • Who is this for? (A) Internal team, B) End users, C) API consumers, D) All)
  • What problem does it solve? (open-ended, 1-2 sentences)
  • What's the MVP scope? (A) Minimal -- one happy path, B) Standard -- happy path + errors, C) Full -- complete feature)

Round 2 -- Technical Shape

  • Primary interaction pattern? (A) REST API, B) GraphQL, C) CLI, D) UI form, E) Background job)
  • Data storage needs? (A) New table/model, B) Extend existing model, C) No persistence, D) External service)
  • Auth requirements? (A) None/public, B) Authenticated only, C) Role-based, D) Custom)

Round 3 -- Dependencies & Constraints (if needed)

  • External dependencies? (APIs, services, libraries)
  • Performance constraints? (latency, throughput, data volume)
  • Any existing code to build on?

Round 4 -- Edge Cases (if needed)

  • Error handling strategy? (A) Return errors to caller, B) Retry + fallback, C) Queue for later, D) Depends on case)
  • Concurrency concerns? (A) Single-user, B) Multi-user but no conflicts, C) Needs locking/transactions)

Adapt questions based on previous answers. Skip rounds that aren't relevant.

Phase 2: Generate PRD

After the Q&A, generate a structured PRD document:

# PRD: {Feature Name}

## Summary
{2-3 sentence description}

## User Stories
- As a {role}, I want {action} so that {benefit}
- ...

## Acceptance Criteria
- [ ] {Criterion with specific, testable condition}
- ...

## Technical Approach
- {Architecture decisions from the Q&A}
- {Data model changes}
- {API contracts}

## Out of Scope
- {What this does NOT include}

## Priority Order
1. {Data layer / models}
2. {Business logic / services}
3. {API / UI layer}
4. {Integration / E2E tests}

Read the full file on GitHub · 108 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. 3d ago First seen · 108 lines · 12 tokens per session scan A c7a318b0d99b

Subscribe to this mod's changes

prd is a skill published in the GitHub repository ashtonian/llm-init (2 stars, last pushed 6mo ago), licensed MIT. It adds 12 tokens to every session and 972 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 2026-08-31.

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