Agent skill
feature-design
Feature design workflow — transform raw feature inputs (ideas, research, stakeholder requests, competitive analysis) into a structured PRD or feature brief. Applies product-manager role. Produces PRD, user stories, acceptance criteria, success metrics, and updates FEATURES.md. First step in the planning chain, precedes /architecture and /feature-plan.
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npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/feature-design-avav25-ai-assets-3
SKILL.md
Feature Design
Transform raw feature inputs into structured product documentation. This is the product design phase — no code, architecture, or engineering decisions are made here. Output feeds into /architecture for technical design and /feature-plan for implementation planning.
Apply Agent(product-manager) role for all steps below.
1. Receive Feature Inputs
Gather all available resources describing the feature:
- Accepted inputs: idea brief, user research, customer feedback, support tickets, competitive analysis, stakeholder request, verbal description, market data, analytics report
- Read every provided document thoroughly
- If the user provides a verbal description only — proceed to Step 2 to structure it through discovery
Extract Raw Signals
From the provided inputs, extract and organize:
| Signal | Source | Notes |
|---|---|---|
| Problem | [what pain exists, for whom] | [evidence or assumption] |
| Opportunity | [what business value] | [data points] |
| User segments | [who needs this] | [ICP/persona indicators] |
| Competitive context | [how others solve it] | [differentiation angle] |
| Constraints | [timeline, budget, technical, regulatory] | [hard vs soft] |
| Existing assets | [related features, prior art, dependencies] | [links/refs] |
If critical signals are missing (no clear problem statement, no target user) — ask before proceeding. Do not invent user needs.
2. Discovery and Framing
2a. Problem Validation
Define the problem with precision:
- Problem statement: One paragraph — who has the problem, what the problem is, why it matters now
- Evidence: Data points supporting the problem (usage metrics, support volume, churn correlation, user quotes, competitive pressure)
- Impact of inaction: What happens if we do nothing
If evidence is weak — flag this as a risk. Do not fabricate data.
2b. Target Users
Apply JTBD and ICP frameworks from Agent(product-manager):
- Job-to-be-Done: When [situation], I want to [motivation], so I can [outcome]
- ICP segments: Which customer profiles benefit most. Include triggers, buying signals, objections
- Personas (if useful): Name, role, goal, frustration. Keep lightweight — max 2 personas
2c. Scope Decision
Based on complexity, decide the deliverable type:
| Complexity | Signals | Deliverable |
|---|---|---|
| Small | Single service, < 1 week effort, clear solution | Feature Brief (abbreviated PRD) |
| Medium | Multi-component, 1–4 weeks, some unknowns | Full PRD |
| Large | Multi-service, 4+ weeks, significant unknowns, new capabilities | Full PRD + Spike/Discovery tasks |
| AI/Agent | LLM-powered, autonomous behavior, trust/safety concerns | Full PRD + Agent Contract + Eval Strategy |
Present the scope decision to the user for confirmation before proceeding.
3. Requirements Definition
3a. Functional Requirements
List requirements prioritized using MoSCoW:
- Must have: Core functionality — feature is useless without these
- Should have: Important but not blocking launch
- Could have: Nice-to-have, defer if constrained
- Won't have (this iteration): Explicitly excluded — prevents scope creep
Each requirement: one sentence, testable, outcome-focused. Never specify implementation — describe what, not how.
3b. Non-Functional Requirements
Identify relevant NFRs:
| Category | Requirement | Target |
|---|---|---|
| Performance | [e.g., response time] | [e.g., < 200ms p95] |
| Security | [e.g., auth, data protection] | [e.g., RBAC, PII encrypted] |
| Scalability | [e.g., concurrent users] | [e.g., 10K concurrent] |
| Accessibility | [e.g., WCAG level] | [e.g., WCAG 2.2 AA] |
| Compliance | [e.g., GDPR, SOC2] | [specific requirements] |
Only include categories relevant to this feature.
3c. Acceptance Criteria
Write acceptance criteria for every Must-have and Should-have requirement:
- Use Given/When/Then format for behavioral criteria
- Include happy path, edge cases, error states
- Include operational criteria: "no new errors in logs", "latency < Xms p95"
- Include security criteria: "unauthorized users receive 403", "PII not logged"
- Each criterion is independently testable
4. Success Metrics
Define how to measure feature success:
4a. Metric Framework
| Metric Type | Metric | Target | Measurement Method |
|---|---|---|---|
| Primary (North Star) | [e.g., activation rate] | [target value] | [how to measure] |
| Leading | [e.g., feature adoption D7] | [target value] | [how to measure] |
| Guardrail | [e.g., error rate, latency] | [must not exceed] | [how to measure] |
4b. Instrumentation Plan
- Events to track (name, properties, trigger)
- Dashboards to create or update
- Alerts to configure (guardrail breaches)
5. Risk Assessment
| Risk | Type | Impact | Likelihood | Mitigation |
|---|---|---|---|---|
| [description] | Technical / Business / Security / Compliance | High/Med/Low | High/Med/Low | [strategy] |
Mandatory risk categories to evaluate:
- Security threats (apply OWASP Top 10; add LLM Top 10 for AI features)
- Data handling risks (PII, secrets, retention)
- Backward compatibility and migration
- Dependency on external systems or teams
- User abuse scenarios
6. AI/Agent Addendum
Include this section only for AI-powered or agent features. Skip for standard features.
<agent_contract>
- Autonomy level: Assist (human decides) → Semi-auto (agent proposes, human approves) → Auto (agent acts independently)
- Allowed tools and permissions: Least privilege. List every tool/API the agent can access
- Confirmation gates: Which actions require human approval
- Failure modes: What happens when the agent fails, hallucinates, or exceeds scope
- Cost budget: Token/compute/API limits per operation
- Context pipeline: Consult
context-engineeringskill for context stack design, RAG pipeline, memory architecture, agent harness patterns, and production checklists - Eval strategy: Offline eval set (fixtures, synthetic + real cases), online monitoring (drift, failure rates) </agent_contract>
7. Compile Deliverable
Full PRD
Compile all sections into a structured PRD:
# PRD: [Feature Name]
## Problem Statement
[From Step 2a]
## Target Users
[From Step 2b — JTBD, ICP, personas]
## Scope and Non-Goals
[From Step 2c — what's in, what's explicitly out]
## Requirements
[From Step 3a — MoSCoW prioritized]
## Non-Functional Requirements
[From Step 3b]
## Acceptance Criteria
[From Step 3c]
## Success Metrics
[From Step 4]
## Risks and Mitigations
[From Step 5]
## Agent Contract
[From Step 6 — only for AI features]
## Rollout Strategy
- Phase 1: Internal / dogfood
- Phase 2: Beta (limited users, feature flag)
- Phase 3: GA (all users)
- Backward compatibility notes
- Feature flag name and config
Feature Brief (for small scope)
Abbreviated format — single document:
# Feature Brief: [Feature Name]
**Problem**: [1–2 sentences]
**Users**: [target segment]
**JTBD**: When [situation], I want to [motivation], so I can [outcome]
## Requirements
[Must-have list only — max 5 items]
## Acceptance Criteria
[Given/When/Then for each requirement]
## Success Metric
[Single primary metric + target]
## Risks
[Top 1–3 risks with mitigations]
Present the compiled deliverable to the user for review. Iterate until approved.
8. Update FEATURES.md
After the PRD/brief is approved:
- If
FEATURES.mddoes not exist — create it at the project root - Add or update the feature entry:
- Name, one-line description
- Status:
planned - Link to PRD/brief in
features/directory
- Save the PRD/brief to
features/[feature-name].md(kebab-case)
9. Handoff
Guide the next step based on feature complexity:
| Complexity | Next Step |
|---|---|
| Small (brief) | Run /feature-plan directly — architecture is implicit |
| Medium (PRD) | Run /architecture for technical design, then /feature-plan |
| Large (PRD + spikes) | Execute spikes first, then /architecture → /feature-plan |
| AI/Agent (PRD + contract) | Run /architecture with agent contract as input → /feature-plan |
Integration
- Input: Raw feature resources (ideas, research, feedback, stakeholder requests)
- Followed by:
/architecture(technical design),/feature-plan(work decomposition) - Roles:
Agent(product-manager)(primary — owns PRD),Agent(solution-architect)(consulted for feasibility) - Skills:
context-engineeringskill (context pipeline design, RAG, memory, agent harness — for AI/Agent features, Step 6) - Updates:
FEATURES.md,features/directory - Enables: Full planning chain:
/feature-design→/architecture→/feature-plan→/feature-dev
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