writing-plans

Writing Plans

Overview

Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.

Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.

Announce at start: "I'm using the writing-plans skill to create the implementation plan."

Save plans to: docs/agent-harness/plans/YYYY-MM-DD-<feature-name>.md

• (User preferences for plan location override this default)
• Before saving: Check if the target directory is gitignored (git check-ignore <dir>). If so, inform the user and suggest .agent-harness/plans/ as an alternative, but respect the user's choice.

Scope Check

If the spec covers multiple independent subsystems, it should have been broken into sub-project specs during brainstorming. If it wasn't, suggest breaking this into separate plans — one per subsystem. Each plan should produce working, testable software on its own.

Sprint Contract Verification

Before defining tasks, check for sprint contract:

1. Look for docs/agent-harness/contracts/{feature-name}.contract.md
2. If exists: read and align plan tasks with Definition of Done
3. If missing: prompt user to run agent-harness:sprint-contract first
   • User can skip with explicit "skip contract" — proceed without contract
   • Default: assume contract exists from prior brainstorming phase

If contract exists: Plan tasks must trace to contract acceptance criteria.

File Structure

Before defining tasks, map out which files will be created or modified and what each one is responsible for. This is where decomposition decisions get locked in.

• Design units with clear boundaries and well-defined interfaces. Each file should have one clear responsibility.
• You reason best about code you can hold in context at once, and your edits are more reliable when files are focused. Prefer smaller, focused files over large ones that do too much.
• Files that change together should live together. Split by responsibility, not by technical layer.
• In existing codebases, follow established patterns. If the codebase uses large files, don't unilaterally restructure - but if a file you're modifying has grown unwieldy, including a split in the plan is reasonable.

This structure informs the task decomposition. Each task should produce self-contained changes that make sense independently.

Bite-Sized Task Granularity

Each step is one action (2-5 minutes):

• "Write the failing test" - step
• "Run it to make sure it fails" - step
• "Implement the minimal code to make the test pass" - step
• "Run the tests and make sure they pass" - step
• "Commit" - step

Plan Document Header

Every plan MUST start with this header:

# [Feature Name] Implementation Plan

> **For agentic workers:** REQUIRED SUB-SKILL: Use agent-harness:subagent-driven-development (recommended) or agent-harness:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.

**Goal:** [One sentence describing what this builds]

**Architecture:** [2-3 sentences about approach]

**Tech Stack:** [Key technologies/libraries]

---

Commit Strategy

Before generating tasks, determine the commit strategy:

• Ask the user: "Should each task include a commit step, or do you prefer to commit manually at the end?"
• Default to manual-commit if the user has previously expressed this preference (check session-learnings or project CLAUDE.md)
• If auto-commit: include "Step N: Commit" in each task as shown in the Task Structure below
• If manual-commit: omit commit steps from all tasks; add a single "Final commit" reminder at the end of the plan

Task Structure

### Task N: [Component Name]

**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`

- [ ] **Step 1: Write the failing test**

```python
def test_specific_behavior():
    result = function(input)
    assert result == expected
```

- [ ] **Step 2: Run test to verify it fails**

Run: `pytest tests/path/test.py::test_name -v`
Expected: FAIL with "function not defined"

- [ ] **Step 3: Write minimal implementation**

```python
def function(input):
    return expected
```

- [ ] **Step 4: Run test to verify it passes**

Run: `pytest tests/path/test.py::test_name -v`
Expected: PASS

- [ ] **Step 5: Commit**

```bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"
```

No Placeholders

Every step must contain the actual content an engineer needs. These are plan failures — never write them:

• "TBD", "TODO", "implement later", "fill in details"
• "Add appropriate error handling" / "add validation" / "handle edge cases"
• "Write tests for the above" (without actual test code)
• "Similar to Task N" (repeat the code — the engineer may be reading tasks out of order)
• Steps that describe what to do without showing how (code blocks required for code steps)
• References to types, functions, or methods not defined in any task

Remember

• Exact file paths always
• Complete code in every step — if a step changes code, show the code
• Exact commands with expected output
• DRY, YAGNI, TDD, frequent commits

Scope Scan

After defining the task list, check whether any task involves a global pattern replacement (token rename, CSS class migration, API signature change, import path shift). If it does, run a project-wide search (Grep) for the pattern before finalizing the plan. List every affected file in the relevant task — do not assume the brainstorming-confirmed file list is exhaustive. A cleanup task that discovers 13 affected files when the plan listed 8 is a plan failure, not a win for the cleanup task.

API Type Verification

When the plan references API types (interfaces, request/response types, DTOs), verify each referenced field exists before finalizing the plan:

1. Check type definitions: open the actual type definition files (e.g., data-contracts.ts, *.d.ts, auto-generated API types) and confirm every field name and type mentioned in the plan matches
2. Check imports: verify that named exports exist in the specified source files — do not assume re-exports
3. Record findings: if a type mismatch is found, correct the plan before presenting it to the user

This prevents plan execution interruptions from type errors discovered during implementation.

Self-Review

After writing the complete plan, look at the spec with fresh eyes and check the plan against it. This is a checklist you run yourself — not a subagent dispatch.

1. Spec coverage: Skim each section/requirement in the spec. Can you point to a task that implements it? List any gaps.

2. Placeholder scan: Search your plan for red flags — any of the patterns from the "No Placeholders" section above. Fix them.

3. Type consistency: Do the types, method signatures, and property names you used in later tasks match what you defined in earlier tasks? A function called clearLayers() in Task 3 but clearFullLayers() in Task 7 is a bug.

If you find issues, fix them inline. No need to re-review — just fix and move on. If you find a spec requirement with no task, add the task.

Execution Handoff

After saving the plan, offer execution choice:

"Plan complete and saved to docs/agent-harness/plans/<filename>.md. Two execution options:

1. Subagent-Driven (recommended) - I dispatch a fresh subagent per task, review between tasks, fast iteration

2. Inline Execution - Execute tasks in this session using executing-plans, batch execution with checkpoints

Which approach?"

If Subagent-Driven chosen:

• REQUIRED SUB-SKILL: Use agent-harness:subagent-driven-development
• Fresh subagent per task + two-stage review

If Inline Execution chosen:

• REQUIRED SUB-SKILL: Use agent-harness:executing-plans
• Batch execution with checkpoints for review