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."

Context: This should be run in a dedicated worktree (created by brainstorming skill).

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

Bite-Sized Task Granularity

Each step produces exactly one artifact: a written test, a passing test run output, a code file, a commit. If a step produces two artifacts, split it.

Examples:

• "Write the failing test" - step (artifact: test file)
• "Run it to make sure it fails" - step (artifact: test run output)
• "Implement the minimal code to make the test pass" - step (artifact: code file)
• "Run the tests and make sure they pass" - step (artifact: passing test run output)
• "Commit" - step (artifact: commit)

Path Convention

For files that don't exist yet, use paths based on the project's existing naming convention. If no convention exists, document the path convention you're using at the top of the plan.

Plan Document Header

Every plan MUST start with this header:

# [Feature Name] Implementation Plan

> **For Antigravity:** REQUIRED SUB-SKILL: Load executing-plans to implement this plan task-by-task.

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

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

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

---

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"
```

Plan Validation

Before handing the plan to execution: read it from the perspective of an engineer who has never seen this codebase. Does every task have enough context to start without asking questions? If not, add it.

Checklist:

• Every file path is exact and follows the documented convention
• Every command includes expected output
• Every task's purpose is clear from its name and description alone
• No task assumes knowledge of a prior conversation or undocumented context

Remember

• Exact file paths always
• Complete code in plan (not "add validation")
• Exact commands with expected output
• Reference relevant skills with @ syntax
• DRY, YAGNI, TDD, frequent commits

Execution Handoff

After saving the plan, offer execution choice:

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

1. Subagent-Driven (this session) - I dispatch fresh subagent per task, review between tasks, fast iteration. REQUIRED: Switch Antigravity to Fast Mode for this implementation phase.

2. Parallel Session (separate) - Open new session with executing-plans, batch execution with checkpoints

Which approach?"

If Subagent-Driven chosen:

• REQUIRED SUB-SKILL: Load executing-plans
• Stay in this session
• Fresh subagent per task + code review

If Parallel Session chosen:

• Guide them to open new session in worktree
• REQUIRED SUB-SKILL: New session loads executing-plans