| name | feature-planner |
| version | 1.0.1 |
| description | Upstream feature planning — requirement clarification, constraint discovery, design outline, vertical-slice task breakdown ordered by risk. Hands off to grill-with-docs and tdd. Use when starting new feature work from a vague request and no plan exists yet; if a plan or design already exists, use grill-with-docs to stress-test it instead. |
Feature Planner
The first step in the new-feature pipeline. Turns a vague request into a clarified requirement, a thought-through design, and an ordered list of vertical slices small enough to implement test-first. Hands off to grill-with-docs for stress-testing the plan, then to tdd for implementation.
1. When to invoke
- User says "I want to build X", "let's add a feature for Y", "I'm starting on Z".
- A request is vague enough that the right shape of the work isn't obvious.
- A task is large enough that "just start coding" would lead to mid-flight rework.
- The user explicitly asks for a plan, breakdown, or task list.
If the work fits in one commit and the shape is obvious, skip planning and go straight to TDD. Plans pay back when the work is non-trivial.
2. The flow
Request → Requirement → Constraints → Design outline → Vertical-slice tasks
↓ ↓ ↓ ↓ ↓
"build X" what + why what's fixed shape + risks ordered, testable
Each step is a checkpoint with the user. Don't proceed to the next until the current one is confirmed.
3. Requirement clarification
Distill the request into a one-paragraph description of what must be true after the work ships, and why it's worth shipping. Two paragraphs at most.
Questions to ask before writing the requirement:
- Who is the user? A human? Another service? A scheduled job?
- What outcome do they get? Phrase as a present-tense fact: "the user can export their order history as CSV", not "we will build a CSV export feature".
- What's the success criterion? How does the user (and you) know it's done? A test that fails today and passes when complete.
- What's explicitly out of scope? Naming exclusions up front prevents scope creep mid-work.
Anti-pattern: writing a requirement that's actually a design ("we'll add a /export endpoint that streams CSV from users.orders"). That's the design step; the requirement is what the user gets, not how.
4. Constraint discovery
Constraints are everything the design must work within. Surface them now or they'll surprise you later.
Ask the user (and check the code):
- Performance — latency budgets, throughput, payload size limits.
- Compatibility — clients on old versions, public API stability, backwards-compatible DB migrations.
- Security & compliance — auth requirements, audit trails, PII handling, regulatory rules.
- Cost — anything that bills per call (cloud APIs, LLM tokens, queue messages).
- Existing architecture — what does this feature have to fit into? Read CONTEXT.md for the domain language, check
docs/adr/ for prior decisions (improve-codebase-architecture §1).
- Team & timeline — who owns the work, what's the deadline, what's the cost of being late.
Record constraints in the plan, even if they're "no constraint" — explicit nothing beats implicit nothing.
5. Design outline
A design outline is not a design document. It's a short description of:
- The shape — where the new code lives (which module, which layer, which bounded context). Use the vocabulary from hexagonal-arch and ddd-architect.
- The seams — what new interfaces are introduced, what existing seams are crossed. One new port? One new adapter? An aggregate gains a method?
- The risks — the parts you're least sure about. Name them. The first slice in the breakdown will tackle the highest-risk one.
- The alternatives considered — what other shapes were possible, and why this one wins. Even a one-line "considered X, picked Y because Z" prevents the next person from re-litigating the choice.
Skip patterns reflexively. The design isn't "Repository + Strategy + Decorator"; it's "the order intake module gains a cancel() method, which raises an OrderCancelled domain event, which the shipping module consumes." Pattern names are reached for if and when they earn it (design-patterns §5).
6. Task breakdown — vertical slices ordered by risk
The critical step. Per tdd's anti-horizontal-slicing rule, break the work into vertical slices: each slice delivers one observable behavior end-to-end.
Slice properties:
- Independently testable. Each slice can be merged on its own without breaking what already exists.
- Small. A slice should fit in one TDD red-green-refactor loop. If it takes a day, it's too big — split.
- Ordered by risk, not by layer. The first slice tackles the most uncertain part of the design — proving the riskiest assumption first. If the riskiest part can't be made to work, you want to know on day one, not at integration.
- Ends in a real assertion. Each slice's success criterion is a test that fails before the slice starts and passes when it's done.
Wrong (horizontal slicing — common, painful):
- Add the database migration.
- Add the repository code.
- Add the service code.
- Add the HTTP handler.
- Add the tests.
Right (vertical slicing):
- Tracer bullet: a stub endpoint returns a hardcoded response; one test passes end-to-end (proves the wire works).
- Riskiest assumption: a single happy-path slice runs the real logic, hits the real DB, returns real data; one test.
- Edge case A — one more test, the smallest amount of code to make it pass.
- Edge case B — same.
- N. Refactor the now-duplicated bits as the third occurrence appears (logic-cleaner §6).
7. Output — the plan deliverable
A plan is a short markdown document or a structured message the user can react to. Shape:
# Plan: <feature name>
## Requirement
<one paragraph: who + outcome + success criterion + out-of-scope>
## Constraints
- <constraint or "no constraint">
- ...
## Design outline
- Shape: <module/layer/context>
- New seams: <port, adapter, aggregate method>
- Risks: <ordered, highest first>
- Alternatives: <"considered X, picked Y because Z" — one line each>
## Tasks (vertical slices, in order)
1. <tracer bullet — establishes the wire>
2. <riskiest assumption — proves the design>
3. <edge cases — one per slice>
4. ...
N. <refactor / cleanup as duplication accumulates>
Keep it tight. A plan that's longer than the code it describes is over-planning.
8. Hand-off
The plan is the input to the next pipeline step:
- grill-with-docs — stress-test each decision in the plan with questions. The grilling loop will surface gaps in constraints or risks that weren't obvious during planning.
- ddd-architect — if the feature shapes the domain (new aggregate, new value object, new domain event), apply DDD discipline now.
- hexagonal-arch — confirm port placement and dependency direction before the first slice.
- tdd — implement each slice in red-green-refactor; never write all tests first.
When the plan changes mid-implementation (and it will), re-plan the remaining slices, don't continue with stale ones. Sunk cost on a slice list is real but tiny compared to the cost of building the wrong thing.
9. When NOT to plan
Planning earns its place when the work is non-trivial and the shape isn't obvious. Skip it for:
- Trivial changes — a typo fix, a one-line config tweak, a bug fix with a known root cause.
- Exploratory spikes — when you're learning whether a thing is possible. Spike, learn, discard, then plan the real implementation.
- Bug fixes with reproductions — go straight to a failing test, then fix.
- Pure refactors — those go through code-design-refactor or improve-codebase-architecture.
Forcing a plan onto trivial work makes the planning process feel like ceremony and erodes trust in it. Save plans for when they pay back.
10. Cross-skill ties
- grill-with-docs — next step in the pipeline; stress-tests the plan.
- ddd-architect — domain-shaping decisions belong here, not in the requirement.
- hexagonal-arch — seam decisions in the design outline.
- tdd — vertical-slice principle inherited from here; implementation follows.
- improve-codebase-architecture — alternative entry point for refactor work (not new features); reads the codebase first.
- logic-cleaner — rule-of-three justifies waiting on the refactor slice until duplication is real.
