# Spec Brainstorm

> Conversational design workshop for substantial work. Interviews the human one question at a time, explores 2-3 approaches with trade-offs, and presents the design section by section for approval before writing only design.md, then stops. Combines requirements discovery with codebase research and architecture design. Use when the user explicitly requests a spec or when atelier-orchestrator selects a Spec-backed Plan. Ambiguous design or discovery requests route through atelier-orchestrator.

- Skill: `martinffx/spec-brainstorm` (Agent Skill)
- Install (CLI): `npx skillmds@latest add martinffx/spec-brainstorm`
- Raw SKILL.md: https://api.skillmd.com/api/skills/martinffx/spec-brainstorm/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Product & Planning
- Author: martinffx (https://skillmd.com/u/martinffx)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/martinffx/spec-brainstorm

---


# Spec Brainstorm

Conversational design workshop for substantial work that produces a focused, reviewed spec.

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

Run this skill only after `atelier-orchestrator` selects a Spec-backed Plan or the human
explicitly requests a spec. Bounded work should go directly to `spec-plan` for an Inline
Plan. Do not reclassify the planning mode here.

## Artifact

```
docs/specs/YYYY-MM-DD-<feature>/
└── design.md  ← This skill's output
```

Requirements are inline — no separate requirements.json needed.

### Exclusive output contract

This skill may create or update only the `design.md` shown above. It may inspect the
repository and discuss drafts in conversation, but it must not modify any other file, create
`plan.json`, create tracker entries, invoke another workflow skill, or write implementation
code. This boundary still applies when the human asks to brainstorm, plan, and implement in
one request. Finish `design.md`, report it, and stop.

---

## Lessons

These principles apply to every spec, every time.

### Specs must earn their cost

Persisted specs are for work whose discovery, architecture, dependencies, or coordination
needs justify a durable artifact. Do not pull bounded work into this workflow merely because
it touches multiple files or takes time. That work belongs in an Inline Plan.

### 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. Treat loaded skills as relevant guidance, not as a requirement to apply every pattern
they contain.

### Decomposition

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

Keep migrations separate from authorization, product behavior, infrastructure, schema, and
test-platform projects. Do not use a migration as permission to redesign adjacent systems.

### 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.

Future consumers do not justify shared infrastructure. A "reusable foundation" may describe
an architectural quality, but it is not a user story or a current requirement.

---

## 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.

Collect research findings for the spec as the foundation. Do not write `design.md` until the
approved design sections are assembled in Step 4c.

The research section must map each relevant concern to the code that already handles it and
the current requirement that drives the decision:

| Concern | Existing solution | Decision | Current requirement |
|---------|-------------------|----------|---------------------|
| IDs | Shared parser and ID type | reuse | Parse route parameters |

Use only `reuse`, `modify`, `delete`, or `new` in the Decision column. Every `new` concept must
map to a present requirement; a future or hypothetical consumer does not qualify.

**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

Design happens in three phases: explore approaches, present the design in sections,
then write the spec file.

### 4a. Explore approaches

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

The first approach must keep the existing architecture and make the smallest correct change.
Present broader approaches only when a current requirement makes their extra cost relevant.

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

Lead with your recommended option and explain why it wins.

Before asking the human to approve an approach or design batch, remove anything justified only
by completeness, consistency, or hypothetical reuse.

**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.

Get explicit approval on the chosen approach before presenting the design.

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

**STOP. Wait for human to choose an approach.**

### 4b. Present the design in sections

Present the design in batches. Get approval after each batch before continuing.

Sections already confirmed in earlier steps (Problem, Scope, Constraints, Context)
are written into the spec from those confirmations — do not re-present them.

**Batch A: User Stories** — the contract you're designing against. Formal stories
with acceptance criteria and priorities. If rejected: revise. If the rejection
reveals a scope misunderstanding, loop back to Discovery (Step 2).

**Batch B: Architecture** — component design, domain modeling, and layer
boundaries. Use installed language-specific architecture or API-design skills as relevant to
your stack. Then present: component structure, domain model, where business
logic lives, where IO lives. If rejected: revise. If the rejection undermines
the chosen approach, offer to return to approach exploration (4a). If it
reveals a fundamental gap, loop back to Research (Step 3). If the detail reveals
the work is far more complex than estimated, say so and offer to revisit the
approach.

**Batch C: API Design + Data Model** — contracts derived from the approved
architecture. Skip sections that don't apply, but say so explicitly ("No API
changes — moving to Trade-offs"). Never skip silently. If rejected: revise. If
the rejection implicates the architecture, go back to Batch B.

**Batch D: Trade-offs + Open Questions** — alternatives considered, why this
approach wins, known limitations, anything unresolved. Usually revisable inline.

Each batch ends with:

**Tell the human:** "Does this look right?"

**STOP. Wait for approval before continuing.**

If you loop twice on the same batch, stop and ask:

> "We've looped on [batch] twice. Should we reconsider the approach?"

**Terminology discipline:** while drafting batches, challenge terms against `CONTEXT.md` and
record resolved terminology in `design.md`. Do not update `CONTEXT.md` from this skill. If
domain confusion runs deep, suggest pausing for **oracle-grill-me** before continuing.

### 4c. Write the spec

Once all batches are approved, write the full spec document.

#### What the spec should contain

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

#### Self-review

After writing the file, check it with fresh eyes:

1. **Placeholder scan** — 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.
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.
5. **Necessity check** — Delete concepts justified only by completeness, consistency, or
   hypothetical reuse. Confirm every remaining new concept maps to a current requirement.

**Substance rule:** if a fix changes the substance of an approved section,
re-present that section for approval. Wording and consistency fixes go inline —
note them at handoff.

---

## Step 5: Handoff

**Tell the human:**

> "Brainstorm complete. Design written to `docs/specs/<path>/design.md`. A separate
> `spec-plan` invocation can create `plan.json` after you approve this document."

If the human requests changes — in conversation or by annotating the file — address every note,
update the spec, and re-run the self-review. If a change alters the substance of an approved
section, re-present that section for approval before continuing. Resolve questions that affect
scope, architecture, contracts, data, security, or task ordering before handoff.

Stop after reporting the completed `design.md`. Do not invoke `spec-plan`, offer to continue
automatically, create `plan.json`, or write code. The human must start the next phase with a
separate request.

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

