Turn requirements into a clear step-by-step execution plan before implementation.
The material indicates this is an open-source, prompt-only writing-plans skill with no required secrets and no declared remote endpoints. Overall risk is low; the main consideration is that it may guide creation of plan documents in a local repo, which is normal content generation rather than a clear security red flag.
The material explicitly states there are no required keys or environment variables; the README does not request logins, API tokens, or other sensitive credentials, so no direct credential exposure or misuse surface is evident.
No remote endpoints are declared, and the system flags it as prompt-only; the documentation focuses on generating implementation plans and does not describe sending user data to external services.
As a skill document/prompt, it does not itself provide a mechanism to spawn local processes or execute code; the README mentions testing, commits, and worktrees as workflow guidance, but does not grant additional execution privileges.
The README explicitly suggests saving plans to `docs/superpowers/plans/...` and identifying files to create or modify; this means the skill operates on local repository context and file structure, which is a normal capability but does involve local project file context.
The source is an open-source GitHub repository, which is a meaningful risk-reducing factor due to auditability; however, it has 0 stars, no declared license, and unknown maintenance status, so community validation and governance signals are weak and warrant some supply-chain caution.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "writing-plans" skill from askskill: 1. Download https://raw.githubusercontent.com/obra/superpowers/main/skills/writing-plans/SKILL.md 2. Save it as ~/.claude/skills/writing-plans/SKILL.md 3. Reload skills and tell me it's ready
I have a requirement: add a notification center to an existing web app with in-app messages, read/unread states, and message filtering. Do not write code yet. First create a phased implementation plan with key tasks, dependencies, risks, and acceptance criteria.
A structured implementation plan broken into phases with dependencies, risks, and acceptance criteria.
Here is a multi-step task: automate the team's weekly manual sales reporting workflow. Based on the current process description, produce an execution plan including requirement clarification, data source review, automation approach, testing steps, and rollout order.
A full task plan from discovery to rollout that helps the team execute the automation in order.
I already have a product requirements document for launching a file upload and permission management module. Review the requirements and output a technical implementation plan first, without coding. Include module breakdown, API design focus, testing checkpoints, and possible blockers.
A developer-focused technical plan covering modules, API priorities, test checkpoints, and potential blockers.
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: If working in an isolated worktree, it should have been created via the superpowers:using-git-worktrees skill at execution time.
Save plans to: docs/superpowers/plans/YYYY-MM-DD-<feature-name>.md
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.
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.
This structure informs the task decomposition. Each task should produce self-contained changes that make sense independently.
Each step is one action (2-5 minutes):
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 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"
```
Every step must contain the actual content an engineer needs. These are plan failures — never write them:
…
Execute implementation plans by splitting and advancing independent tasks in-session.
Set conversation rules to discover and invoke skills before replying.
Create, revise, and validate AI skills before deployment.
Systematically investigate bugs, test failures, and unexpected behavior before fixing.
Helps decide merge, PR, or cleanup steps after branch work is complete.
Clarify intent, requirements, and solution direction before any creative implementation work.
Create detailed implementation plans for engineers with little or no codebase context.
Create step-by-step implementation plans for engineers new to a codebase.
Review implementation plans for gaps, assumptions, and sequencing before coding starts
Execute detailed plans in batches with review checkpoints and course correction.
Turn Notion specs into implementation plans, tasks, and progress tracking.
Create objective-driven plans for agent-led development with an audit trail.