Agent skill

Prd

PRD(Product Requirements Document) 작성 스킬. An agent skill from autopus-ai/autopus-adk.

MITAuto-check passedProduct & Project Management

Install Prd

skills CLI

$ npx skills add autopus-ai/autopus-adk --skill prd -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install autopus-ai/autopus-adk prd --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.omp/skills/prd .claude/skills/prd && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "prd" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/prd into .claude/skills/prd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prd", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/prd

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add autopus-ai/autopus-adk --skill prd -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install autopus-ai/autopus-adk prd --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.omp/skills/prd .agents/skills/prd && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "prd" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/prd into .agents/skills/prd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prd", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add autopus-ai/autopus-adk --skill prd -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install autopus-ai/autopus-adk prd --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.omp/skills/prd .cursor/skills/prd && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "prd" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/prd into .cursor/skills/prd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prd", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/autopus-ai/autopus-adk.git --path .omp/skills/prd

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add autopus-ai/autopus-adk --skill prd -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install autopus-ai/autopus-adk prd --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.omp/skills/prd .gemini/skills/prd && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "prd" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/prd into .gemini/skills/prd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prd", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install autopus-ai/autopus-adk prd

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add autopus-ai/autopus-adk --skill prd -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .github/skills && cp -r skills-src/.omp/skills/prd .github/skills/prd && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "prd" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/prd into .github/skills/prd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prd", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add autopus-ai/autopus-adk --skill prd -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install autopus-ai/autopus-adk prd --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.omp/skills/prd .opencode/skills/prd && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "prd" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/prd into .opencode/skills/prd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "prd", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: prd
GitHub stars: 111
Token cost: ~1.7k tokens
SKILL.md length: 645 words
Files: 1
Skills in repo: 11
Repo updated: Oct 4, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

PRD(Product Requirements Document) 작성 스킬. An agent skill from autopus-ai/autopus-adk.

Works in 6 steps: Request Analysis → 5: Discovery Q&A → Codebase Context Collection → …
Tasks that involve PRD writing
SKILL.md covers PRD Writing Process, Relationship to Other Skills and Output Example
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Prd is an agent skill from autopus-ai/autopus-adk. PRD(Product Requirements Document) 작성 스킬

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: omp

It sits in Product & Project Management, covering PRD writing. The repository describes itself as: Autopus-ADK is of the agents, by the agents. for the agents. Multi-model orchestration (consensus/pipeline/debate/fastest). Architecture-as-Code, Lore decision tracking… The licence is MIT.

When your agent uses it

Tasks that involve PRD writing

Example prompts

“/prd”

Requirements

Compatibility (from SKILL.md): omp

Workflow steps

6 steps, taken from the step headings in SKILL.md.

Request Analysis
5: Discovery Q&A
Codebase Context Collection
PRD Section Authoring
Quality Validation
File Save

What it can do on your machine

Read from SKILL.md and the folder at commit 3f15677. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and bash).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compatibility
omp
From compatibility in the SKILL.md frontmatter.

Context cost

Prd loads about 1.7k tokens when it runs. Until then it costs about 11 tokens; SKILL.md has 645 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~11
When it runs · the whole SKILL.md, loaded when a task matches: ~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from autopus-ai/autopus-adk at commit 3f15677, republished under its MIT licence (© autopus-ai). 645 words, ~1,730 tokens.

Download SKILL.mdSave it as .claude/skills/prd/SKILL.md (or your agent's skills folder).

name: prd
description: PRD(Product Requirements Document) 작성 스킬
compatibility: omp

PRD Skill

Skill for creating Product Requirements Documents (PRD) that provide top-level context for the Planning → SPEC pipeline.

PRD Writing Process

Step 1: Request Analysis

Identify the four core dimensions from the user's request:

What: What product or feature are we building?
Why: What problem does it solve? What is the business motivation?
Who: Who are the primary users or stakeholders?
When: What is the target release or deadline?

Clarify any missing dimensions before proceeding.

Step 1.5: Discovery Q&A

PRD 작성 전에 6개 핵심 질문으로 컨텍스트를 수집합니다. auto idea의 Clarification Ledger 또는 auto plan의 inline intent ledger가 이미 답한 항목은 재질문하지 않고 PRD evidence로 재사용합니다. 사용자 입력이 불충분하면 현재 플랫폼의 question transport로 highest expected-gain 미해결 항목 1개만 확인합니다:

Problem: 해결하려는 핵심 문제는 무엇인가? (증상이 아닌 근본 원인)
Target Users: 누가 이것을 사용하는가? (역할, 빈도, 기대)
Success Metrics: 성공을 어떻게 측정하는가? (정량적 지표 1개 이상)
Constraints: 기술적/비즈니스적 제약은? (기한, 호환성, 예산)
Prior Art: 이전에 시도된 접근이나 관련 기능이 있는가?
Scope Boundary: 이번에 명확히 제외할 것은? (스코프 크리프 방지)

Outcome Lock이나 Must acceptance를 막는 질문만 진행을 차단합니다. 그 밖의 불확실한 항목은 assumed 또는 deferred로 표시하고 PRD의 Open Questions 섹션에 기록합니다. --auto에서는 질문 없이 가장 보수적인 가정을 남기고 Step 2로 진행합니다.

Step 2: Codebase Context Collection

Gather relevant context to ground the PRD in the current state of the system:

Related files: Identify existing modules, packages, or services affected
Existing patterns: Review coding conventions, API patterns, data models
Prior SPECs: Check for related SPEC documents across top-level and submodules

ls .autopus/specs/ */.autopus/specs/ 2>/dev/null   # list existing SPECs (top-level + submodules)
cat .autopus/specs/SPEC-*/prd.md */.autopus/specs/SPEC-*/prd.md 2>/dev/null  # review related PRDs

Use this context to ensure the PRD aligns with existing architecture and avoids conflicts.

Step 3: PRD Section Authoring

Choose the appropriate mode based on scope:

Mode Selection

Mode	When to Use	Sections
Standard	New features, cross-team work, public APIs	10 sections
Minimal	Small changes, internal tools, hotfixes	5 sections

Standard Mode (11 sections)

Reference: templates/shared/prd-standard.md.tmpl

Problem & Context — Current situation, problem statement, business impact
Goals & Success Metrics — SMART goals with quantitative success criteria
Target Users — User groups, roles, usage frequency, key expectations
User Stories / Job Stories — Two formats supported:
- User Stories: As a [role] / I want [action] / so that [benefit] + INVEST criteria check
- Job Stories (JTBD): When [situation] / I want to [motivation] / so I can [outcome]
- Choose the format that best captures user intent. Job Stories work better when context matters more than role.
Functional Requirements — MoSCoW prioritized (P0=Must, P1=Should, P2=Could)
Non-Functional Requirements — Performance, security, scalability, compliance
Technical Constraints — Stack constraints, external dependencies, compatibility
Out of Scope — Explicit exclusions to prevent scope creep
Risks & Open Questions — Risk severity/mitigation + unresolved questions
Pre-mortem — "이 기능이 6개월 후 실패한다면 이유는?" 사전 분석
- 3-5개 실패 시나리오 도출
- 각 시나리오별 발생 확률 (High/Medium/Low)과 예방 조치
- Discovery Q&A에서 수집한 제약/위험과 연결
Practitioner Q&A — Key implementation questions with answers or TBD

Show full SKILL.md (178 more words)Show less

Minimal Mode (5 sections)

Reference: templates/shared/prd-minimal.md.tmpl

Problem — Core problem in 1-2 sentences
Requirements — P0 items only, EARS format
Technical Notes — Constraints, dependencies, impact on existing code
Out of Scope — At least one explicit exclusion
Key Q&A — 3-5 blocking questions with answers or TBD

Step 4: Quality Validation

Run the following checklist before finalizing the PRD:

markdown

## PRD Quality Checklist

### Structure (Standard mode)
- [ ] All 10 sections present and non-empty
- [ ] Overview is ≤ 3 sentences

### Structure (Minimal mode)
- [ ] All 5 sections present and non-empty

### Goals
- [ ] At least 1 measurable success metric defined
  - Good: "p99 latency < 200ms", "DAU increase by 10%"
  - Bad: "improve performance", "make users happy"

### Requirements
- [ ] At least 1 P0 (Must Have) requirement listed
- [ ] Requirements written in EARS format

### Scope
- [ ] At least 1 Out of Scope item explicitly listed

### Consistency
- [ ] No conflicts with existing SPECs (check both `.autopus/specs/` and `*/.autopus/specs/`)
- [ ] Terminology matches codebase conventions

Flag any checklist failures to the user before saving.

Step 5: File Save

Save the completed PRD to the target module's SPEC directory:

{target-module}/.autopus/specs/SPEC-{ID}/prd.md

Where {ID} is the next available SPEC identifier (e.g., SPEC-AUTH-001), unique across the entire project. The target module is determined by the spec-writer's module detection logic.

If the directory does not exist, create it:

bash

mkdir -p {target-module}/.autopus/specs/SPEC-{ID}

Relationship to Other Skills

PRD sits at the top of the planning pipeline:

PRD (this skill)
  └─> Planning (planning.md) — EARS requirements, MoSCoW prioritization
        └─> SPEC — Formal specification with implementation tasks

The Goals and Requirements sections of a PRD feed directly into planning.md's requirements analysis step.
EARS format and MoSCoW priorities defined in a PRD carry forward unchanged into the Planning and SPEC phases.
When creating a Planning document, reference the PRD for top-level context and constraints.

Output Example

markdown

# PRD: Async Job Queue

**SPEC-ID**: SPEC-QUEUE-001
**Mode**: Standard
**Date**: 2026-03-23

## 1. Problem & Context
API endpoints take 500ms+ due to slow background tasks running synchronously in the request path.
This causes timeouts and poor user experience under load.

## 2. Goals & Success Metrics
| Goal | Success Metric | Target |
|------|---------------|--------|
| Reduce latency | p99 API response time | < 200ms |
| Improve reliability | Job failure rate | < 0.1% |

## 8. Out of Scope
- Priority queues (deferred to SPEC-QUEUE-002)
- Cross-region job routing

## 5. Functional Requirements
### P0 — Must Have
| ID | Requirement |
|----|-------------|
| FR-01 | WHEN a job is enqueued, THE SYSTEM SHALL persist it durably before acknowledging |
| FR-02 | WHEN a job fails, THE SYSTEM SHALL retry up to 3 times with exponential backoff |

### P1 — Should Have
| ID | Requirement |
|----|-------------|
| FR-10 | WHILE a job is running, THE SYSTEM SHALL emit telemetry events |

Files

Just SKILL.md in .omp/skills/prd of autopus-ai/autopus-adk.

Open the folder on GitHubat commit 3f15677

Compare with similar skills

Prd next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Prd compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Prd this skillautopus-ai/autopus-adk	111	—	~1.7k	Automated safety check: Pass	MIT	4 days ago
CCPM Project Managementautomazeio/ccpm	8.4k	—	~1.1k	Automated safety check: Pass	MIT	6 mo ago
Ralph Tui Create Beadssubsy/ralph-tui	2.5k	1 repos	~2.6k	Automated safety check: Pass	MIT	1 mo ago
Trellis Brainstormanjiemo/SunnyBeach	178	7 repos	~4k	Automated safety check: Pass	Apache-2.0	27 days ago
Adversarial Speczscole/adversarial-spec	556	1 repos	~8.3k	Automated safety check: Notes	MIT	8 mo ago
Ralph Tui Create Beads Rustsubsy/ralph-tui	2.5k	1 repos	~2.8k	Automated safety check: Pass	MIT	1 mo ago

Similar skills

CCPM Project Management
automazeio/ccpm
Runs a spec-driven workflow from PRD to epic to GitHub issues to parallel agents, with status, standup and blocked-work reports from bundled scripts.
8.4k GitHub stars~1.1k tokensUpdated 6 mo ago
Product & Project ManagementAuto-check passed
Ralph Tui Create Beads
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Convert PRDs to beads for ralph-tui execution. An agent skill from subsy/ralph-tui.
2.5k GitHub starsUsed in 1 repo~2.6k tokens
Product & Project ManagementAuto-check passed
Trellis Brainstorm
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Guides collaborative requirements discovery before implementation.
178 GitHub starsUsed in 7 repos~4k tokens
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Adversarial Spec
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Iteratively refine a product spec by debating with multiple LLMs (GPT, Gemini, Grok, etc.) until all models agree.
556 GitHub starsUsed in 1 repo~8.3k tokens
Product & Project ManagementAuto-check: notes
Ralph Tui Create Beads Rust
subsy/ralph-tui
Convert PRDs to beads for ralph-tui execution using beads-rust (br CLI).
2.5k GitHub starsUsed in 1 repo~2.8k tokens
Product & Project ManagementAuto-check passed
Ouroboros PM Interview
Q00/ouroboros
Runs a guided product-manager interview that classifies each question automatically and produces a Product Requirements Document.
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Questions about Prd

What does Prd do?

PRD(Product Requirements Document) 작성 스킬. An agent skill from autopus-ai/autopus-adk. Prd is an agent skill from autopus-ai/autopus-adk.

When should I use Prd?

Prd fits situations like: tasks that involve PRD writing.

How do I install Prd in Claude Code?

Run `npx skills add autopus-ai/autopus-adk --skill prd -a claude-code`. Or copy the skill folder (.omp/skills/prd in autopus-ai/autopus-adk) into .claude/skills/prd in your project. Claude Code loads it when a task matches its description.

How do I install Prd in Codex?

Run `npx skills add autopus-ai/autopus-adk --skill prd -a codex`. Or copy the skill folder (.omp/skills/prd in autopus-ai/autopus-adk) into .agents/skills/prd in your project. Codex loads it when a task matches its description.

Can I use Prd in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add autopus-ai/autopus-adk --skill prd -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/prd, .gemini/skills/prd, .github/skills/prd and .opencode/skills/prd in your project.

What does Prd need to run?

SKILL.md names no scripts, command-line tools or credentials: Prd is instructions for the agent only. Compatibility (from SKILL.md): omp.

Does Prd access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Prd safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Prd use?

Prd is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Prd use?

About 1.7k tokens (SKILL.md is roughly 6.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Prd?

Skills that share tags, products or a category with Prd: CCPM Project Management (automazeio/ccpm, 8.4k stars), Ralph Tui Create Beads (subsy/ralph-tui, 2.5k stars), Trellis Brainstorm (anjiemo/SunnyBeach, 178 stars) and Adversarial Spec (zscole/adversarial-spec, 556 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Prd?

autopus-ai (a GitHub organization) maintains it in autopus-ai/autopus-adk, which has 111 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 4, 2026.

Source: autopus-ai/autopus-adk on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Prd

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Compatibility

Context cost

Safety

SKILL.md

PRD Skill

PRD Writing Process

Step 1: Request Analysis

Step 1.5: Discovery Q&A

Step 2: Codebase Context Collection

Step 3: PRD Section Authoring

Mode Selection

Standard Mode (11 sections)

Minimal Mode (5 sections)

Step 4: Quality Validation

Step 5: File Save

Relationship to Other Skills

Output Example

Files

Compare with similar skills

Similar skills

More from autopus-ai/autopus-adk

Related

Questions about Prd