Skillquality 0.46

spec-brainstorm

Conversational design workshop for new features. Interviews the human one question at a time, explores 2-3 approaches with trade-offs, then produces a focused spec. Combines requirements discovery with codebase research and architecture design. Use when the user says "create a sp

Price
free
Protocol
skill
Verified
no

What it does

Spec Brainstorm

Conversational design workshop that produces a focused, reviewed spec.

One question at a time. Multiple approaches explored. Ruthless scope control. No implementation until design is approved.

Artifact

docs/specs/YYYY-MM-DD-<topic>-design.md  ← This skill's output

Requirements are inline — no separate requirements.json needed.


Lessons

These principles apply to every spec, every time.

"Too simple for a design" is an anti-pattern

Every project goes through this process. No exceptions. The five-minute conversation often reveals assumptions that would cost hours in implementation. If it's truly trivial, the spec will be short — but it still gets written.

Design for isolation and clarity

Break the system into units with one clear purpose each. Well-defined interfaces between them. Each unit independently understandable and independently testable. If you can't explain a unit's job in one sentence, it's doing too much.

Working in existing codebases

Explore the current structure first. Follow existing patterns. Targeted improvements only. No unrelated refactoring. Understand why things are the way they are before proposing changes.

Decomposition

If the request describes multiple independent subsystems, flag it immediately. Decompose into sub-projects before diving into details. Each sub-project gets its own spec and its own plan. A spec that tries to cover three subsystems helps no one.

YAGNI ruthlessly

Remove unnecessary features from all designs. If a capability isn't needed for the first user story, it doesn't go in the spec. Every feature is a cost — to build, to test, to maintain, to understand later. Push back on scope creep during discovery.


Step 1: Orient

Before diving in, understand where you are.

  1. Read project context — AGENTS.md, README, existing architecture docs
  2. Check existing specs — Scan docs/specs/ for previous work. What domain model exists? What patterns are established? What has been built before?
  3. Read recent specs — What was the last thing built? Is this feature building on existing work, extending it, or something greenfield?

This is silent — don't narrate it. Let the context inform where you focus.


Step 2: Discovery

Ask questions to understand what to build. Skip this step if requirements are already clear from context (existing specs, human provided details, etc.).

Interview style

Ask one question at a time. Multiple choice preferred when possible — give 2-4 concrete options rather than open-ended prompts. Keep the conversation moving.

Good: "Should this be real-time or batch-processed? (a) Real-time via WebSocket, (b) Periodic polling every 30s, (c) On-demand when user requests it."

Bad: "How should the data synchronization work?"

When to skip discovery

  • Human provides clear, detailed requirements
  • Feature extends existing work with well-defined scope
  • Human says "spec out X" and X is specific enough

Decomposition check

Before asking any detail questions, assess scope. If the request describes multiple independent subsystems (e.g., "build a notification system with email, SMS, push, and an admin dashboard"):

  1. Flag it immediately: "This looks like multiple independent projects. Let me propose a decomposition."
  2. Break it down: Identify the subsystems and their dependencies.
  3. Get agreement: "Which of these should we spec first?"

Do not try to spec everything in one document.

YAGNI check

During discovery, push back on scope:

  • "Do you need this in the first version, or is it a nice-to-have?"
  • "Can we ship without this and add it later if needed?"
  • "This feature adds significant complexity — is the use case real or hypothetical?"

If the human insists, include it — but flag the trade-off in the spec.

Discovery questions

Adapt these to context. Not all are needed every time.

  1. What problem are we solving? — Concrete problem statement, not solution description
  2. Who has this problem? — User roles
  3. How do they solve it today? — Current workflow and pain points
  4. What does success look like? — Measurable outcomes
  5. What does this integrate with? — Existing systems, APIs
  6. What constraints exist? — Technical, business, regulatory

If you already know answers from orientation, confirm rather than ask.

Tell the human: "Based on my research, here's my understanding of what we're building. Does this look right?"

STOP. Wait for human confirmation.


Step 3: Research

Read the relevant codebase deeply. Not signatures — implementations, edge cases, error handling, data flows. Trace callers and callees. Read tests to understand expected behaviour.

Write findings directly into the spec as the foundation.

Tell the human: "I've written the research section of the spec. Ready for you to review before I continue with the design."

STOP. Wait for human review.


Step 4: Design — Explore Approaches

Before settling on a design, present 2-3 approaches with trade-offs.

Approach exploration

For each approach, address:

  1. What it looks like — Brief architecture sketch
  2. Pros — What makes this approach good
  3. Cons — What's painful, expensive, or risky
  4. Complexity estimate — Rough sense of implementation effort

Then make a recommendation and explain why.

Example:

Approach A: Single table with JSON columns

  • Simple schema, fast to implement
  • Querying inside JSON is limited, migration pain later
  • Complexity: Low

Approach B: Normalized relational tables

  • Clean queries, easy to evolve schema
  • More joins, more migration files, more code
  • Complexity: Medium

Recommendation: Approach B — the query flexibility matters more here than implementation speed.

Design approval gate

Get explicit approval on the chosen approach before writing the full spec.

Tell the human: "Which approach should we go with? Or should I explore a different direction?"

STOP. Wait for human to choose an approach.

Write the spec

Once an approach is chosen, write the full spec document.

Use the Skill tool to invoke oracle-architect for component design, domain modeling, and layer boundaries.

What the spec should contain

# Feature Name

## Problem
- What problem are we solving
- Who has this problem
- How they solve it today

## Scope
- **In scope:** [specific capabilities]
- **Out of scope:** [explicitly deferred]

## User Stories
- US-1: As a [role], I want [action], so that [benefit]
  - Given X, when Y, then Z
- Priority: must/should/could

## Constraints
- [Technical or business constraints]

## Context
- What exists today, how it works end-to-end
- Existing patterns and conventions
- Dependencies and integration points
- Gotchas, assumptions, technical debt

## Architecture
- Component structure (functional core / effectful edge)
- Domain model: entities, value objects, aggregates
- Where business logic lives, where IO lives

## API Design
- Endpoints, request/response contracts
- Error handling approach
- Event contracts (published/consumed)

## Data Model
- Schema design, access patterns
- Migrations needed

## Trade-offs
- Alternatives considered
- Why this approach wins
- Known limitations

## Open Questions
- Anything unresolved needing human input

Scale each section to complexity — a few sentences if straightforward, detailed if nuanced.

Reference implementations

If human provides reference code — from open source, from elsewhere in codebase — use it as a concrete guide. Working from a reference produces dramatically better designs.


Step 5: Self-Review

Before presenting the spec to the human, run this checklist silently:

1. Placeholder scan

Are there any TBD, TODO, FIXME, or incomplete sections? Every section should have real content or be removed.

2. Internal consistency

Do sections contradict each other? If the Architecture section says "stateless" but the Data Model includes session state, resolve the conflict before presenting.

3. Scope check

Is this focused enough for a single implementation plan? If the spec covers more than one independent subsystem, it should have been decomposed in Step 2. If it's still too broad, flag it now.

4. Ambiguity check

Could any requirement be interpreted two ways? If so, pick one interpretation, state it explicitly, and let the human correct you.

Fix any issues found. Then present.

Tell the human: "The spec is complete. Ready for your review."

STOP. Wait for human review.


Step 6: Annotation

Human may annotate the spec directly — adding corrections, rejections, domain knowledge, or "remove this section entirely."

When they say "I added notes":

  1. Re-read the full document
  2. Address every note
  3. Update the spec
  4. Run the self-review checklist again (Step 5)
  5. Do not move to planning

This may repeat 1-6 times. Spec is not approved until human explicitly says so.


Handoff

When the spec is approved, the next step is spec-plan.

"Spec is approved. Ready to write the implementation plan?"

If planning reveals design flaws, loop back to research. See spec-orchestrator for iteration patterns.

Do not start planning without explicit approval. Do not write code.

Capabilities

skillsource-martinffxskill-spec-brainstormtopic-agent-skillstopic-agentic-codingtopic-anthropictopic-claude-codetopic-claude-skillstopic-code-reviewtopic-codextopic-codex-skilltopic-opencodetopic-prompt-engineeringtopic-sddtopic-spec-driven-development

Install

Installnpx skills add martinffx/atelier
Transportskills-sh
Protocolskill

Quality

0.46/ 1.00

deterministic score 0.46 from registry signals: · indexed on github topic:agent-skills · 23 github stars · SKILL.md body (9,397 chars)

Provenance

Indexed fromgithub
Enriched2026-05-18 19:05:24Z · deterministic:skill-github:v1 · v1
First seen2026-05-18
Last seen2026-05-18

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