Product capability
Skill onfire7777/universal-ai-skills-library/skills/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.From its SKILL.md
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SKILL.md
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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.
What ships with it: 1 file
280 B alongside SKILL.md
agents/
- openai.yaml280 B
Gives 0 of the 12 instructions most plan spec skills give in 839 tokens
Counted across 1,360 of the 2,617 authors here whose files we hold, read 2026-09-06
- Ask one question at a timein 73 of 1360
- Write the spec using the templatein 22 of 1360
- Ask clarifying questions if neededin 19 of 1360, across 18 files
- Wait for user confirmation before proceedingin 19 of 1360
- Save plans to the plans directoryin 17 of 1360, across 13 files
- Check for product marketing context firstin 16 of 1360, across 5 files
- Read the plan file completelyin 16 of 1360
- Order tasks by dependencyin 16 of 1360
- Gather context from the conversationin 15 of 1360, across 9 files
- Explore the codebase instead of askingin 15 of 1360, across 13 files
- Wait for explicit user approvalin 14 of 1360, across 13 files
- Quiz the user on the breakdownin 13 of 1360, across 7 files
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.