💡 Summary
A skill that generates hyper-detailed, step-by-step implementation plans for developers, enforcing TDD and granular task breakdowns.
🎯 Target Audience
🤖 AI Roast: “This skill is a micromanager's dream, turning the art of coding into a paint-by-numbers exercise that might just bore a skilled developer to tears.”
The skill writes plan files to the local filesystem (`docs/plans/`). While low risk, if the plan content is generated from untrusted user input, it could potentially contain malicious code snippets or instructions that an executing agent might run. Mitigation: Treat generated plan files as untrusted code; review them before execution, especially if the initial requirements/spec came from an external source.
name: writing-plans description: Use when you have a spec or requirements for a multi-step task, before touching code
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:
# [Feature Name] Implementation Plan > **For Claude:** REQUIRED SUB-SKILL: Use superpowers: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
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
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:**
- **REQUIRED SUB-SKILL:** Use superpowers: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
- **REQUIRED SUB-SKILL:** New session uses superpowers:executing-plans
Pros
- Enforces disciplined, test-driven development practices
- Provides extreme clarity and reduces context-switching for implementers
- Creates reusable documentation (plans) for future reference
Cons
- Overly prescriptive structure may stifle creativity and problem-solving
- Risk of creating verbose, brittle plans that don't adapt to discovery
- Adds significant overhead for simple or exploratory tasks
Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author obra.
