/prd
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.
$ npx -y skills add smallnest/goal-workflow --skill prd --agent claude-codeHow it fires
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- Slash command
/prd
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The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
prd.SKILL.mdname: prd
description: "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."
user-invocable: true
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
| Scenario | Handling | |----------|----------| | 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 exist | Auto-create `tasks/` directory | | feature-name is hard to extract from input | Ask the user directly: "Suggested PRD filename is prd-XXX.md, please confirm or modify" | | User requests PRD changes after review | Apply changes and re-save without re-running the clarification flow | | PRD content exceeds 500 lines | Suggest the user consider splitting into multiple sub-feature PRDs | | User declines to proceed | Just save the PRD, user can run `/to-issues` later | | Issue creation needed later | Suggest 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
Read more
name: prd description: "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." user-invocable: true
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
| Scenario | Handling | |----------|----------| | 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 exist | Auto-create `tasks/` directory | | feature-name is hard to extract from input | Ask the user directly: "Suggested PRD filename is prd-XXX.md, please confirm or modify" | | User requests PRD changes after review | Apply changes and re-save without re-running the clarification flow | | PRD content exceeds 500 lines | Suggest the user consider splitting into multiple sub-feature PRDs | | User declines to proceed | Just save the PRD, user can run `/to-issues` later | | Issue creation needed later | Suggest 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
An AI-driven development workflow — from PRD to shipped code, all within Claude Code.
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