Writing Plans

This skill guides the creation of comprehensive implementation plans for engineers, assuming they have limited context about the codebase. It emphasizes...

Install

npx promptshop add writing-plans

Details

What This Skill Does

This skill guides the creation of comprehensive implementation plans for engineers, assuming they have limited context about the codebase.
It emphasizes documenting everything an engineer needs to know, including file modifications, code details, testing procedures, and relevant documentation.
The skill promotes DRY, YAGNI, TDD, and frequent commits.

When to Use

Plan implementation for new features.
Guide engineers unfamiliar with the codebase.
Document file modifications for each task.
Outline testing procedures and documentation checks.
Break down complex tasks into bite-sized pieces.
Ensure each plan produces testable software.

Key Features

Assumes zero context from the engineer.
Emphasizes comprehensive documentation.
Promotes DRY, YAGNI, and TDD principles.
Suggests saving plans to a specific directory.
Encourages breaking down specs into sub-projects.
Focuses on clear file structure and responsibilities.

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/superpowers/plans/YYYY-MM-DD-.md (User preferences for plan location override this default)

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.

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 superpowers:subagent-driven-development (recommended) or superpowers: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]

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 testpython 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 implementationpython 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: Commitbash 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

Plan Review Loop

After writing the complete plan:

Dispatch a single plan-document-reviewer subagent (see plan-document-reviewer-prompt.md) with precisely crafted review context — never your session history. This keeps the reviewer focused on the plan, not your thought process.

Provide: path to the plan document, path to spec document If ❌ Issues Found: fix the issues, re-dispatch reviewer for the whole plan If ✅ Approved: proceed to execution handoff

Review loop guidance: Same agent that wrote the plan fixes it (preserves context) If loop exceeds 3 iterations, surface to human for guidance Reviewers are advisory — explain disagreements if you believe feedback is incorrect

Execution Handoff

After saving the plan, offer execution choice:

"Plan complete and saved to docs/superpowers/plans/.md. Two execution options:

Subagent-Driven (recommended) - I dispatch a fresh subagent per task, review between tasks, fast iteration
Inline Execution - Execute tasks in this session using executing-plans, batch execution with checkpoints

Which approach?"

If Subagent-Driven chosen: REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development Fresh subagent per task + two-stage review

If Inline Execution chosen: REQUIRED SUB-SKILL: Use superpowers:executing-plans Batch execution with checkpoints for reviewWriting Plans