prd

prd is a skill for Claude Code, Codex from adawalli/nexus. It costs 66 tokens per session (575 once invoked), scanned A, original, MIT.

A workflow for creating a Product Requirements Document, or PRD: a written description of a feature, its requirements, boundaries, and success measures.

In plain words
What is it for?
Asking key clarification questions, writing a Markdown PRD, and saving it under a named task file without implementing the feature.
Why use it?
It turns an early feature idea into clear instructions that developers can understand and implement.

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

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/adawalli/nexus/prd.svg)](https://agentmods.dev/skills/adawalli/nexus/prd)
Your own site
<a href="https://agentmods.dev/skills/adawalli/nexus/prd"><img src="https://agentmods.dev/badge/skills/adawalli/nexus/prd.svg" alt="Measured on agentmods" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 575 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 $0.00066 $0.00575
Opus 5 $0.00033 $0.00287
Sonnet 5 $0.00013 $0.00115
Haiku 4.5 $0.00007 $0.00057

Measured 4d ago against content hash 0790f235ae90, 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 4d 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.

.claude/skills/prd/SKILL.md · 75 lines

How it starts

The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PRD Generator

Create clear, actionable Product Requirements Documents suitable for junior developers to understand and implement.

Workflow

  1. Receive feature request - User describes a feature or functionality
  2. Ask clarifying questions - 3-5 essential questions with lettered options
  3. Generate PRD - Create structured document based on answers
  4. Save PRD - Write to /tasks/prd-[feature-name].md

Important: Do NOT implement the feature. Only create the PRD document.

Step 1: Clarifying Questions

Ask only critical questions where the initial prompt is ambiguous. Skip questions when answers are reasonably inferable.

Question areas:

  • Problem/Goal - "What problem does this solve?"
  • Core Functionality - "What key actions should users perform?"
  • Scope/Boundaries - "What should this NOT do?"
  • Success Criteria - "How will we know it's successful?"

Format requirements:

  • Number questions (1, 2, 3)
  • Letter options (A, B, C, D) for each question
  • Enable responses like "1A, 2C, 3B"

Example:

1. What is the primary goal of this feature?
   A. Improve user onboarding experience
   B. Increase user retention
   C. Reduce support burden
   D. Generate additional revenue

2. Who is the target user?
   A. New users only
   B. Existing users only
   C. All users
   D. Admin users only

3. What is the expected scope?
   A. MVP - minimal viable implementation
   B. Full feature - complete functionality
   C. Iteration - enhance existing feature

Step 2: Generate PRD

After receiving answers, generate the PRD using the structure in references/prd-template.md.

Writing guidelines:

  • Write for junior developers - explicit, unambiguous, avoid jargon
  • Focus on "what" and "why", not "how"
  • Number all functional requirements
  • Keep requirements specific and testable

Step 3: Save PRD

Save to /tasks/prd-[feature-name].md

Use kebab-case for feature name (e.g., prd-user-authentication.md, prd-export-dashboard.md).

Read the full file on GitHub · 75 lines

Files

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.

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. 4d ago First seen · 75 lines · 66 tokens per session scan A 0790f235ae90

Subscribe to this mod's changes

prd is a skill published in the GitHub repository adawalli/nexus (23 stars, last pushed 22d ago), licensed MIT. It adds 66 tokens to every session and 575 once invoked, about $0.0003 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.

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