Writing Plans
Create detailed implementation plans with bite-sized tasks for engineers with zero codebase context
Best use case
Writing Plans is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Create detailed implementation plans with bite-sized tasks for engineers with zero codebase context
Teams using Writing Plans should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/writing-plans/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Writing Plans Compares
| Feature / Agent | Writing Plans | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Create detailed implementation plans with bite-sized tasks for engineers with zero codebase context
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 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:**
```markdown
# [Feature Name] Implementation Plan
> **For Claude:** Use `@skills/collaboration/executing-plans/SKILL.md` 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
```markdown
### 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"
```
```
## 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
**2. Parallel Session (separate)** - Open new session with executing-plans, batch execution with checkpoints
**Which approach?"**
**If Subagent-Driven chosen:**
- Use skills/collaboration/subagent-driven-development
- Stay in this session
- Fresh subagent per task + code review
**If Parallel Session chosen:**
- Guide them to open new session in worktree
- New session uses skills/collaboration/executing-plansRelated Skills
Executing Plans
Execute detailed plans in batches with review checkpoints
Testing Anti-Patterns
Never test mock behavior. Never add test-only methods to production classes. Understand dependencies before mocking.
Test-Driven Development (TDD)
Write the test first, watch it fail, write minimal code to pass
Condition-Based Waiting
Replace arbitrary timeouts with condition polling for reliable async tests
Testing Skills With Subagents
RED-GREEN-REFACTOR for process documentation - baseline without skill, write addressing failures, iterate closing loopholes
Installing Skills System
Fork, clone to ~/.clank, run installer, edit CLAUDE.md
Gardening Skills Wiki
Maintain skills wiki health - check links, naming, cross-references, and coverage
Creating Skills
TDD for process documentation - test with subagents before writing, iterate until bulletproof
Getting Started with Skills
Skills wiki intro - mandatory workflows, search tool, brainstorming triggers
Verification Before Completion
Run verification commands and confirm output before claiming success
Systematic Debugging
Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.
Root Cause Tracing
Systematically trace bugs backward through call stack to find original trigger