# Planner Context

This file is loaded by the `/loop-plan` skill to provide additional context for PRD generation.

## Story Decomposition Guidelines

When breaking a feature into stories, think about:

### Independence
Each story should be independently deployable. After completing story N, the codebase should be in a valid, working state — even if the feature isn't fully built yet.

### Context Window Fit
A story must fit in a single AI context window (~100K tokens). This means:
- Reading relevant existing code
- Understanding the task
- Implementing the change
- Writing tests
- Running quality checks
- Committing

Budget roughly:
- 30% of context for reading/understanding
- 40% for implementation
- 20% for testing and quality
- 10% for bookkeeping (prd.json, progress.md)

### Failure Isolation
If a story fails (evaluator rejects it), the next iteration should be able to retry it cleanly. Stories with too many moving parts are hard to retry because partial state is messy.

### Evaluability
Every story must have criteria the evaluator can independently verify. "The code is clean" is not evaluable. "The function returns 404 when the user doesn't exist" is evaluable.

## PRD Anti-Patterns

Avoid these common mistakes:

- **Stories too large:** "Build the API" — split into individual endpoints
- **Stories too small:** "Create the file" — combine with meaningful work in that file
- **Vague criteria:** "Works correctly" — what does correctly mean? Be specific.
- **Missing dependencies:** Story 5 needs Story 3's database table but doesn't say so
- **Testing as afterthought:** Tests should be part of each story, not a separate "add tests" story at the end
- **UI without backend:** A UI story that calls an API that doesn't exist yet