product-capability

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.

16 stars

Best use case

product-capability is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using product-capability should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/product-capability/SKILL.md --create-dirs "https://raw.githubusercontent.com/Jamkris/everything-gemini-code/main/skills/product-capability/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/product-capability/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How product-capability Compares

Feature / Agentproduct-capabilityStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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:

1. Product intent
   - issue, discussion, PRD, roadmap note, founder message
2. Current architecture
   - relevant repo docs, contracts, schemas, routes, existing workflows
3. Existing capability context
   - `PRODUCT.md`, design docs, RFCs, migration notes, operating-model docs
4. 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-ops`
- `workspace-surface-audit`
- `api-connector-builder`
- `dashboard-builder`
- `tdd-workflow`
- `verification-loop`

## Output Format

Return the result in this order:

```text
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 Gemini CLI, Codex, Cursor, OpenCode, and ECC 2.0 planning surfaces.

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