agentleFS
smallnestsmallnest/goal-workflow/skills/prd/SKILL.md

prd

Skill283 starsChanged 4 months agoMITView on GitHub

Generate a Product Requirements Document (PRD) for a new feature. Use when planning a feature, starting a new project, or when asked to create a PRD. After PRD is confirmed, use /prd-to-spec (optional) for technical design, then /to-issues to create implementable tickets. Triggers on: create a prd, write prd for, plan this feature, requirements for, spec out, 写PRD, 需求文档, 需求分析, 规格说明.

125 other projects use a version of this, 31 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use context-optimize, usecase and 6 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • ibahgatSkill

    context-optimize

    Improve context efficiency and cache stability for long or complex sessions.

    Also in 3 projects that use this

  • gabriellstSkill

    usecase

    Create an application use case. Use when implementing business operations like CreateOrder, ProcessPayment, CancelBooking. Use this skill for any command/mutation that orchestrates domain logic, whether simple CRUD or complex multi-step transactions with sagas. Dispatch hub — routes to typescript/go variants by file extension.

    Also in 3 projects that use this

  • ulises-jeremiasSkill

    trd

    WHAT — Draft and review a Technical Requirements Document (TRD) using the template, typically

    Also in 3 projects that use this

  • snarktankSkill

    ralph

    Convert PRDs to prd.json format for the Ralph autonomous agent system. Use when you have an existing PRD and need to convert it to Ralph's JSON format. Triggers on: convert this prd, turn this into ralph format, create prd.json from this, ralph json.

    Also in 16 projects that use this

  • JokerRunSkill

    compound-engineering

    Compound Engineering workflow for AI-assisted development. Use when planning features, executing work, reviewing code, or codifying learnings. Follows the Plan → Work → Review → Compound loop where each unit of engineering makes subsequent work easier. Triggers on: plan this feature, implement this, review this code, compound learnings, create implementation plan, systematic development.

    Also in 3 projects that use this

  • chusiminSkill

    brd

    评估具体产品或业务方向是否值得投入,交付商业判断或 BRD。基于用户问题、替代方案、商业机制、成本和证据提出建议;按请求决定简短分析或完整文档。

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 7 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 102 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Create detailed Product Requirements Documents that are clear, actionable, and suitable for implementation.

    line 9
  2. Distinctive:

    Ask clarifying questions to cover key ambiguities — scale the count to complexity, not a fixed number (see Step 1)

    line 16
  3. Distinctive:

    Important: Do NOT start implementing.

    line 22
  4. Distinctive:

    Ask only critical questions where the initial prompt is ambiguous.

    line 28
  5. Distinctive:

    If a dimension is already unambiguous from the user's input, skip it — don't ask filler questions just to reach a number.

    line 34
  6. Very specific:

    For any story with UI changes: Always include "Verify in a browser" as acceptance criteria (e.g., via the run skill).

    line 134
  7. Distinctive:

    After the PRD is saved, suggest the user:

    line 176
  8. Distinctive:

    If the user wants to proceed, invoke the corresponding skill.

    line 189
  9. Distinctive:

    Before saving the PRD:

    line 294

“Common” is measured: kept by at least 6 in 10 of the 102 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

PRD Generator

Create detailed Product Requirements Documents that are clear, actionable, and suitable for implementation. After PRD is confirmed, use /to-issues to decompose it into Issues, and optionally /prd-to-spec for technical design before that.


The Job

  1. Receive a feature description from the user
  2. Ask clarifying questions to cover key ambiguities — scale the count to complexity, not a fixed number (see Step 1)
  3. Generate a structured PRD based on answers
  4. Present PRD to user for review — ask "Please review the PRD. Let me know if any adjustments are needed, or reply OK to confirm."
  5. Apply any adjustments, then save to tasks/prd-[feature-name].md
  6. Suggest next steps (see Step 3)

Important: Do NOT start implementing. Just create the PRD.


Step 1: Clarifying Questions

Ask only critical questions where the initial prompt is ambiguous. Scale the number of questions to the feature's complexity — the goal is covering key ambiguities, not hitting a fixed count:

  • Simple, well-scoped feature: 2-3 questions
  • Typical feature: 3-5 questions
  • Complex feature (multiple user roles, cross-system integration, significant ambiguity): 6-8 questions

If a dimension is already unambiguous from the user's input, skip it — don't ask filler questions just to reach a number. Focus on:

  • Problem/Goal: What problem does this solve?
  • Core Functionality: What are the key actions?
  • Scope/Boundaries: What should it NOT do?
  • Success Criteria: How do we know it's done?

Format Questions Like This:

1. What is the primary goal of this feature?
   A. Improve user onboarding experience
   B. Increase user retention
   C. Reduce support burden
   D. Other: [please specify]

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 scope?
   A. Minimal viable version
   B. Full-featured implementation
   C. Just the backend/API
   D. Just the UI

This lets users respond with "1A, 2C, 3B" for quick iteration. Remember to indent the options.


Edge Cases & Fallback

ScenarioHandling
User skips clarifying questions (e.g., replies "whatever", "just write it")Fill with reasonable defaults, mark with [Assumption] in PRD, prompt user to confirm during review
User input is too vague (e.g., "add a feature")Ask once for specifics; if still vague, infer from project context and mark assumptions
tasks/ directory does not existAuto-create tasks/ directory
feature-name is hard to extract from inputAsk the user directly: "Suggested PRD filename is prd-XXX.md, please confirm or modify"
User requests PRD changes after reviewApply changes and re-save without re-running the clarification flow
PRD content exceeds 500 linesSuggest the user consider splitting into multiple sub-feature PRDs
User declines to proceedJust save the PRD, user can run /to-issues later
Issue creation needed laterSuggest running /to-issues with the saved PRD file

Step 2: PRD Structure

Generate the PRD with these sections:

1. Introduction/Overview

Brief description of the feature and the problem it solves. Use plain language — avoid jargon or explain it. Assume the reader may be a junior developer or AI agent.

2. Goals

Specific, measurable objectives (bullet list).

3. User Stories

Each story needs:

  • Title: Short descriptive name
  • Description: "As a [user], I want [feature] so that [benefit]"
  • Acceptance Criteria: Verifiable checklist of what "done" means

Numbering rule: US-001, US-002, US-003... (three digits, starting from 001). Each US should be independently implementable and small enough to complete within one focused agent session.

Mandatory E2E test story: Every PRD MUST include one end-to-end (E2E) test user story as the last user story. It validates the complete feature flow across the whole stack — from user action through UI, API, and data layer — not an isolated unit. Its acceptance criteria describe the full happy-path journey a real user takes to accomplish the feature's core goal, plus at least one critical edge/failure path, all asserted through an automated E2E test (e.g., Playwright/Cypress for UI, or an API-level integration test for backend-only features). This story depends on all others and confirms the feature works as a whole.

Acceptance criteria self-check template: Each criterion must satisfy at least one of the following, otherwise it is considered "vague" and must be rewritten:

  • Observable: describes a specific UI state or API response (e.g., "button shows confirmation dialog")
  • Testable: has clear input/output pairs (e.g., "entering an empty email shows a red warning")
  • Verifiable: can be checked by tools (e.g., "Typecheck/lint passes")
  • ❌ Bad example: "works correctly", "good user experience", "excellent performance" → these are unverifiable

Format:

### US-001: [Title]
**Description:** As a [user], I want [feature] so that [benefit].

**Acceptance Criteria:**
- [ ] Specific verifiable criterion
- [ ] Another criterion
- [ ] Typecheck/lint passes
- [ ] **[UI stories only]** Verify in a browser (e.g., via the `run` skill)

E2E story format:

### US-NNN: End-to-end test of [feature] flow
**Description:** As a QA engineer, I want an automated end-to-end test covering the full [feature] journey so that we catch regressions across the entire stack.

**Acceptance Criteria:**
- [ ] Automated E2E test simulates the full happy path (user action → UI → API → data → visible result)
- [ ] Covers at least one critical edge/failure path (e.g., invalid input, empty state, permission denied)
- [ ] Test runs in CI and passes
- [ ] Test is independent and repeatable (sets up and tears down its own data)

Important:

  • Acceptance criteria must be verifiable, not vague. "Works correctly" is bad. "Button shows confirmation dialog before deleting" is good.
  • For any story with UI changes: Always include "Verify in a browser" as acceptance criteria (e.g., via the run skill). This ensures visual verification of frontend work.

4. Functional Requirements

Numbered list of specific functionalities:

  • "FR-1: The system must allow users to..."
  • "FR-2: When a user clicks X, the system must..."

FR specification: Each FR starts with FR-N: (N increments from 1), uses "system must / system shall" phrasing, and describes one specific behavior. Avoid combining multiple "and"-linked behaviors in a single FR.

5. Non-Goals (Out of Scope)

What this feature will NOT include. Critical for managing scope.

6. Design Considerations (Optional)

  • UI/UX requirements
  • Link to mockups if available
  • Relevant existing components to reuse

7. Technical Considerations (Optional)

  • Known constraints or dependencies
  • Integration points with existing systems
  • Performance requirements

8. Success Metrics

How will success be measured?

  • "Reduce time to complete X by 50%"
  • "Increase conversion rate by 10%"

9. Open Questions

Remaining questions or areas needing clarification.


Output

  • Format: Markdown (.md)
  • Location: tasks/
  • Filename: prd-[feature-name].md (kebab-case)

Step 3: Next Steps

After the PRD is saved, suggest the user:

✅ PRD saved to tasks/prd-[feature-name].md

Next steps:
  /prd-to-spec  →  Generate technical SPEC (optional — for complex features)
  /to-issues    →  Decompose into Issues and create tickets

Or go straight to implementation:
  /to-issues    →  Create Issues, then /goal to implement

If the user wants to proceed, invoke the corresponding skill.


Example PRD

# PRD: Task Priority System

## Introduction

Add priority levels to tasks so users can focus on what matters most. Tasks can be marked as high, medium, or low priority, with visual indicators and filtering to help users manage their workload effectively.

## Goals

- Allow assigning priority (high/medium/low) to any task
- Provide clear visual differentiation between priority levels
- Enable filtering and sorting by priority
- Default new tasks to medium priority

## User Stories

### US-001: Add priority field to database
**Description:** As a developer, I need to store task priority so it persists across sessions.

**Acceptance Criteria:**
- [ ] Add priority column to tasks table: 'high' | 'medium' | 'low' (default 'medium')
- [ ] Generate and run migration successfully
- [ ] Typecheck passes

### US-002: Display priority indicator on task cards
**Description:** As a user, I want to see task priority at a glance so I know what needs attention first.

**Acceptance Criteria:**
- [ ] Each task card shows colored priority badge (red=high, yellow=medium, gray=low)
- [ ] Priority visible without hovering or clicking
- [ ] Typecheck passes
- [ ] Verify in a browser (e.g., via the `run` skill)

### US-003: Add priority selector to task edit
**Description:** As a user, I want to change a task's priority when editing it.

**Acceptance Criteria:**
- [ ] Priority dropdown in task edit modal
- [ ] Shows current priority as selected
- [ ] Saves immediately on selection change
- [ ] Typecheck passes
- [ ] Verify in a browser (e.g., via the `run` skill)

### US-004: Filter tasks by priority
**Description:** As a user, I want to filter the task list to see only high-priority items when I'm focused.

**Acceptance Criteria:**
- [ ] Filter dropdown with options: All | High | Medium | Low
- [ ] Filter persists in URL params
- [ ] Empty state message when no tasks match filter
- [ ] Typecheck passes
- [ ] Verify in a browser (e.g., via the `run` skill)

### US-005: End-to-end test of task priority flow
**Description:** As a QA engineer, I want an automated end-to-end test covering the full priority journey so that we catch regressions across the entire stack.

**Acceptance Criteria:**
- [ ] E2E test creates a task, sets its priority via the edit modal, and asserts the badge color updates on the card
- [ ] Test applies a priority filter and asserts only matching tasks remain visible
- [ ] Covers edge case: filtering to a priority with no tasks shows the empty state message
- [ ] Test runs in CI and passes
- [ ] Test sets up and tears down its own task data

## Functional Requirements

- FR-1: Add `priority` field to tasks table ('high' | 'medium' | 'low', default 'medium')
- FR-2: Display colored priority badge on each task card
- FR-3: Include priority selector in task edit modal
- FR-4: Add priority filter dropdown to task list header
- FR-5: Sort by priority within each status column (high to medium to low)

## Non-Goals

- No priority-based notifications or reminders
- No automatic priority assignment based on due date
- No priority inheritance for subtasks

## Technical Considerations

- Reuse existing badge component with color variants
- Filter state managed via URL search params
- Priority stored in database, not computed

## Success Metrics

- Users can change priority in under 2 clicks
- High-priority tasks immediately visible at top of lists
- No regression in task list performance

## Open Questions

- Should priority affect task ordering within a column?
- Should we add keyboard shortcuts for priority changes?

Checklist

Before saving the PRD:

  • Asked clarifying questions with lettered options
  • Incorporated user's answers
  • User stories are small and specific
  • Included a mandatory end-to-end (E2E) test story as the last user story
  • Functional requirements are numbered and unambiguous
  • Non-goals section defines clear boundaries
  • Saved to tasks/prd-[feature-name].md
  • Suggested next steps: /prd-to-spec (optional) and /to-issues

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.