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.

Stars 163
Forks 31

Install this agent skill to your Project

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:

  1. Problem statement: One paragraph — who has the problem, what the problem is, why it matters now
  2. Evidence: Data points supporting the problem (usage metrics, support volume, churn correlation, user quotes, competitive pressure)
  3. 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-engineering skill 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:

markdown
# 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:

markdown
# 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:

  1. If FEATURES.md does not exist — create it at the project root
  2. Add or update the feature entry:
    • Name, one-line description
    • Status: planned
    • Link to PRD/brief in features/ directory
  3. 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-engineering skill (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

Expand your agent's capabilities with these related and highly-rated skills.

Didn't find tool you were looking for?

Be as detailed as possible for better results