product-capability
affaan-m/everything-claude-code
Translate PRD intent into implementation-ready capability plans with explicit constraints and unresolved decisions.
What is product-capability?
This skill converts product requirements, roadmap items, or design discussions into durable capability contracts that expose constraints, invariants, interfaces, and open questions before multi-service implementation begins. Use it when product intent is clear but engineering constraints remain implicit or scattered across team memory.
- Compress product asks into precise capability statements with clear user outcomes
- Extract hidden business rules, scope boundaries, invariants, and trust boundaries
- Define implementation-facing contracts with actors, surfaces, states, and transitions
- Separate user-visible promises from architecture preferences and unresolved decisions
- Create reusable artifacts that survive across sessions and harnesses
- Identify blockers and clarify what needs architecture or product review before coding
How to install product-capability
npx skills add https://github.com/affaan-m/everything-claude-code --skill product-capabilityHow to use product-capability
- 1.Gather the product intent (issue, PRD, roadmap note, or discussion)
- 2.Review current architecture and existing capability context in the repo
- 3.Restate the capability as a single precise statement of who, what, and outcome change
- 4.Extract fixed rules, scope boundaries, invariants, and lifecycle transitions
- 5.Define the implementation contract with actors, surfaces, states, and interfaces
- 6.List explicit non-goals and open questions blocking implementation
- 7.Determine handoff readiness and which ECC lane should take it next
- 8.Store the result in a durable location like PRODUCT.md or docs/product/
Use cases
- A PRD exists but implementation constraints are still implicit across the team
- A feature crosses multiple services and needs a capability contract before coding starts
- Senior engineers keep restating the same hidden assumptions during code review
- You need a durable product-context artifact to reference across Claude Code, Cursor, and other harnesses
- Product intent is clear but data model, lifecycle, or policy implications are fuzzy
- Senior engineers planning multi-service features
- Product managers translating requirements into engineering constraints
- Tech leads preparing handoffs to implementation teams
- Teams working across multiple repos or services
product-capability FAQ
Use this when a feature crosses multiple services, when product intent is clear but constraints are implicit, or when you need a reusable artifact that survives across sessions. If the implementation is straightforward and single-service, direct coding may be faster.
Mark unresolved questions explicitly. Do not invent product truth. Call out conflicts with existing repo constraints clearly instead of smoothing them over. This skill surfaces ambiguity rather than hiding it.
If the repo has a durable product-context file like PRODUCT.md or docs/product/, update it there. Otherwise, create one using the template at docs/examples/product-capability-template.md. The goal is one reusable artifact, not scattered ad hoc notes.
The handoff section tells you what's next. Common next lanes are project-flow-ops for execution planning, workspace-surface-audit for UI/UX contracts, api-connector-builder for integrations, or tdd-workflow for test-driven implementation.
Yes. The output is designed to be reusable across Claude Code, Codex, Cursor, OpenCode, and ECC 2.0 planning surfaces. Store it in version control as a durable reference.
Full instructions (SKILL.md)
Source of truth, from affaan-m/everything-claude-code.
name: product-capability description: Translate PRD intent, roadmap asks, or product discussions into an implementation-ready capability plan that exposes constraints, invariants, interfaces, and unresolved decisions before multi-service work starts. Use when the user needs an ECC-native PRD-to-SRS lane instead of vague planning prose. metadata: origin: ECC
Product Capability
This skill turns product intent into explicit engineering constraints.
Use it when the gap is not "what should we build?" but "what exactly must be true before implementation starts?"
When to Use
- A PRD, roadmap item, discussion, or founder note exists, but the implementation constraints are still implicit
- A feature crosses multiple services, repos, or teams and needs a capability contract before coding
- Product intent is clear, but architecture, data, lifecycle, or policy implications are still fuzzy
- Senior engineers keep restating the same hidden assumptions during review
- You need a reusable artifact that can survive across harnesses and sessions
Canonical Artifact
If the repo has a durable product-context file such as PRODUCT.md, docs/product/, or a program-spec directory, update it there.
If no capability manifest exists yet, create one using the template at:
docs/examples/product-capability-template.md
The goal is not to create another planning stack. The goal is to make hidden capability constraints durable and reusable.
Non-Negotiable Rules
- Do not invent product truth. Mark unresolved questions explicitly.
- Separate user-visible promises from implementation details.
- Call out what is fixed policy, what is architecture preference, and what is still open.
- If the request conflicts with existing repo constraints, say so clearly instead of smoothing it over.
- Prefer one reusable capability artifact over scattered ad hoc notes.
Inputs
Read only what is needed:
- Product intent
- issue, discussion, PRD, roadmap note, founder message
- Current architecture
- relevant repo docs, contracts, schemas, routes, existing workflows
- Existing capability context
PRODUCT.md, design docs, RFCs, migration notes, operating-model docs
- Delivery constraints
- auth, billing, compliance, rollout, backwards compatibility, performance, review policy
Core Workflow
1. Restate the capability
Compress the ask into one precise statement:
- who the user or operator is
- what new capability exists after this ships
- what outcome changes because of it
If this statement is weak, the implementation will drift.
2. Resolve capability constraints
Extract the constraints that must hold before implementation:
- business rules
- scope boundaries
- invariants
- trust boundaries
- data ownership
- lifecycle transitions
- rollout / migration requirements
- failure and recovery expectations
These are the things that often live only in senior-engineer memory.
3. Define the implementation-facing contract
Produce an SRS-style capability plan with:
- capability summary
- explicit non-goals
- actors and surfaces
- required states and transitions
- interfaces / inputs / outputs
- data model implications
- security / billing / policy constraints
- observability and operator requirements
- open questions blocking implementation
4. Translate into execution
End with the exact handoff:
- ready for direct implementation
- needs architecture review first
- needs product clarification first
If useful, point to the next ECC-native lane:
project-flow-opsworkspace-surface-auditapi-connector-builderdashboard-buildertdd-workflowverification-loop
Output Format
Return the result in this order:
CAPABILITY
- one-paragraph restatement
CONSTRAINTS
- fixed rules, invariants, and boundaries
IMPLEMENTATION CONTRACT
- actors
- surfaces
- states and transitions
- interface/data implications
NON-GOALS
- what this lane explicitly does not own
OPEN QUESTIONS
- blockers or product decisions still required
HANDOFF
- what should happen next and which ECC lane should take it
Good Outcomes
- Product intent is now concrete enough to implement without rediscovering hidden constraints mid-PR.
- Engineering review has a durable artifact instead of relying on memory or Slack context.
- The resulting plan is reusable across Claude Code, Codex, Cursor, OpenCode, and ECC 2.0 planning surfaces.
Related skills
More from affaan-m/everything-claude-code and the wider catalog.

security-review
Security checklist and patterns for authentication, input validation, secrets, and sensitive features.

golang-patterns
Idiomatic Go patterns, best practices, and conventions for building robust, efficient, and maintainable applications.

coding-standards
Baseline coding conventions for naming, readability, immutability, and quality across projects.

frontend-patterns
React and Next.js patterns for components, state management, performance, and modern frontend practices.

backend-patterns
REST/GraphQL API design, database optimization, and server-side patterns for Node.js, Express, and Next.js.

golang-testing
Go testing patterns: table-driven tests, subtests, benchmarks, fuzzing, and TDD methodology.