prd

prd is a skill for Claude Code, Codex from porcupine-md/jonggrang. It costs 11 tokens per session (708 once invoked), scanned A, original, MIT.

A template for creating a Product Requirements Document, or PRD: a written description of what a product feature should do and how success is checked. It turns a feature idea into user stories, acceptance criteria, technical notes, and out-of-scope items.

In plain words
What is it for?
Use it to document feature intent, define user needs, set completion criteria, record technical constraints, and prepare work for an AI development workflow.
Why use it?
It makes feature requests clearer and easier to divide into small, testable development tasks.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to document feature intent, define user needs, set completion criteria, record technical constraints, and prepare work for an AI development workflow.

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Install with agentmods
npx agentmods add skills/porcupine-md/jonggrang/prd
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.

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

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/porcupine-md/jonggrang/prd.svg)](https://agentmods.dev/skills/porcupine-md/jonggrang/prd)
Your own site
<a href="https://agentmods.dev/skills/porcupine-md/jonggrang/prd"><img src="https://agentmods.dev/badge/skills/porcupine-md/jonggrang/prd.svg" alt="Measured on agentmods" height="20"></a>
Per session 11 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 708 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00011 $0.00708
Opus 5 $0.00005 $0.00354
Sonnet 5 $0.00002 $0.00142
Haiku 4.5 $0.00001 $0.00071

Measured 8d ago against content hash 8306f53c94d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, 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 8d 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.

skills/core/prd/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Context

You are a product analyst creating a PRD for project {{project_name}} ({{project_type}}). Stack used: {{stack}}.

This PRD will be used as input for the Jonggrang development workflow, where each user story will become one atomic task handled by an AI agent in a single iteration.

Instructions

  1. Analyze the given feature intent/description: "{{input.feature}}"

  2. Create a PRD with the following structure:

    • Overview: Feature summary in 2-3 sentences
    • Problem Statement: What problem this solves
    • User Stories: List of user stories in the format "As a [role], I want [action], so that [benefit]"
    • Acceptance Criteria: Per user story, what must be true for it to be considered complete
    • Technical Notes: Technical considerations, dependencies, constraints
    • Out of Scope: What is NOT included in this feature
  3. Ensure each user story:

    • Is small enough to be completed in 1 context window (~30 minutes of agent work)
    • Has testable acceptance criteria
    • Does not overlap file ownership with other stories (if possible)
    • Has a clear priority (1 = highest)
  4. Save the PRD to tasks/prd-{{input.feature | slugify}}.md

  5. Ask the user whether the PRD is acceptable or needs revision

  6. After approval, convert to .jonggrang/jonggrang-tasks.json format:

Script

#!/bin/bash
# Create tasks directory if not exists
mkdir -p tasks

Validation

  • PRD file saved in tasks/prd-*.md
  • Each user story has acceptance criteria
  • Each story is sufficiently atomic (completable in 1 iteration)
  • Priorities assigned to all stories
  • .jonggrang/jonggrang-tasks.json updated with new tasks

Examples

Input

feature: "User authentication with email and social login"

Output PRD (excerpt)

# PRD: User Authentication

## Overview
Implement user authentication system supporting email/password
and social login (Google, GitHub) with session management.

## User Stories

### Story 1: Email Registration (Priority: 1)
As a new user, I want to register with my email and password,
so that I can create an account.

Acceptance Criteria:
- POST /api/auth/register accepts email + password
- Email validated (format + uniqueness)
- Password hashed with bcrypt (min 8 chars)
- Returns JWT token on success
- Returns 422 on validation error
- Tests: happy path, duplicate email, weak password

Files: src/routes/auth.ts, src/services/auth.ts, tests/auth.test.ts

Read the full file on GitHub · 95 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. 8d ago First seen · 95 lines · 11 tokens per session scan A 8306f53c94d3

Subscribe to this mod's changes

prd is a skill published in the GitHub repository porcupine-md/jonggrang (11 stars, last pushed 12d ago), licensed MIT. It adds 11 tokens to every session and 708 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.

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