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writing-plans
Use when you have a spec or requirements for a multi-step task, before touching code
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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Use when you have a spec or requirements for a multi-step task, before touching code
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | writing-plans |
| description | Use when you have a spec or requirements for a multi-step task, before touching code |
Create implementation plans for technical coding agents that will execute a feature, fix, or refactor in a real codebase. The plan should minimize ambiguity, make dependencies explicit, and provide enough repository-level detail that an agent can carry out the work with limited additional interpretation.
Announce at the start: "I'm using the planning skill to create the implementation plan."
Use this skill when:
Do not use this skill for:
Write for a capable coding agent operating in an unfamiliar or partially familiar repository.
Assume the agent:
The plan should help the agent make correct local decisions without re-planning the entire feature.
Save plans to:
docs/superpowers/plans/YYYY-MM-DD-<feature-name>.md
If the user specifies a different location, follow the user’s preference.
Write plans that are:
Favor:
Do not pad the plan with generic engineering slogans unless they materially affect execution.
Before writing tasks, determine whether the request represents:
If the spec spans independent workstreams, recommend splitting into separate plans. Each plan should produce a testable, meaningful increment on its own.
If keeping one plan, define task boundaries so the execution agent can work through them in order without confusion about ownership or sequencing.
Before defining tasks, map the expected file-level surface area.
For each relevant file, specify:
This step should lock in the decomposition before task writing begins.
Guidelines:
If the implementation depends on discovering unknown files during execution, name the likely search targets or patterns the agent should inspect.
Break the work into small tasks and even smaller checkbox steps.
Target size:
Good step types:
Avoid multi-action checkboxes that mix discovery, implementation, and verification into one step.
Every plan must begin with this exact structure:
# [Feature Name] Implementation Plan
> **For agentic workers:** REQUIRED SUB-SKILL: Use mojosmind:subagent-driven-development (recommended) or mojosmind:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
**Goal:** [One sentence describing what this builds or changes]
**Architecture:** [2-3 sentences describing the implementation approach and where it fits in the codebase]
**Tech Stack:** [Key technologies, frameworks, libraries, test tools, and commands used by this work]
---
Organize the plan into tasks that reflect actual execution order.
Each task should:
Prefer plans where later tasks build on earlier completed states instead of requiring the agent to mentally merge parallel unfinished work.
Use this structure for each task:
### Task N: [Task Name]
**Objective:** [What this task accomplishes]
**Files:**
- Create: `path/to/new_file.py`
- Modify: `path/to/existing_file.py`
- Test: `tests/path/to/test_file.py`
**Notes:**
- [Key repository convention, dependency, interface contract, or constraint the agent must respect]
- [ ] **Step 1: Inspect the existing implementation surface**
Look at:
- `path/to/existing_file.py`
- `path/to/related_interface.py`
Confirm:
- where the behavior currently lives
- which public function, class, or module should own the change
- whether an existing test file should be extended or a new one added
- [ ] **Step 2: Write the failing test**
```python
def test_specific_behavior():
result = function(input)
assert result == expected
```
- [ ] **Step 3: Run the targeted test and confirm failure**
Run: `pytest tests/path/test_file.py::test_specific_behavior -v`
Expected: FAIL with `[expected reason]`
- [ ] **Step 4: Implement the minimal code change**
```python
def function(input):
return expected
```
- [ ] **Step 5: Re-run the targeted test**
Run: `pytest tests/path/test_file.py::test_specific_behavior -v`
Expected: PASS
- [ ] **Step 6: Run any related verification**
Run: `pytest tests/path/test_file.py -v`
Expected: PASS
- [ ] **Step 7: Commit the checkpoint**
```bash
git add tests/path/test_file.py src/path/file.py
git commit -m "feat: add specific behavior"
```
Every task must include the real execution details an agent needs.
Include:
If applicable, also include:
Do not assume the executing agent will discover these on its own if the spec already implies them.
These are plan failures and must not appear in the final plan:
TBDTODOimplement laterfill in detailsadd appropriate error handlingadd validationhandle edge caseswrite tests for the abovesimilar to Task NAlso avoid:
If a behavior needs error handling, validation, or edge-case coverage, specify the exact cases and where they belong.
The plan must be internally consistent and execution-safe.
Check for:
A later task must not depend on undefined code or unexplained earlier decisions.
When useful, include short agent-facing guidance such as:
Keep this guidance operational. Do not include generic commentary that does not change behavior.
Include explicit stop-and-ask checkpoints when execution should pause for user confirmation instead of continuing autonomously.
Use a checkpoint when:
For each checkpoint, state:
Format checkpoints like this:
### Stop-And-Ask Checkpoint: [Short Name]
**Trigger:** [What condition causes the pause]
**Why this needs confirmation:**
- [Risk, ambiguity, or tradeoff]
**Decision needed:**
- [Exact question the user or reviewer must answer]
**Options:**
1. `[Option A]` - [Impact]
2. `[Option B]` - [Impact]
**Recommended:** `[Option X]` - [Short reason]
Do not add checkpoints for routine implementation decisions that the agent can safely resolve from the codebase and spec. Only use them for decisions that could materially change scope, behavior, or risk.
After drafting the full plan, review it before saving.
Check:
If you find gaps, fix them directly in the plan.
After saving the plan, offer the user these execution options:
Plan complete and saved to `docs/mojosmind/plans/<filename>.md`.
Two execution options:
1. Subagent-Driven (recommended)
I dispatch a fresh subagent per task, with review between tasks for fast iteration.
2. Inline Execution
I execute the tasks in this session using executing-plans, with checkpointed progress.
Which approach?
**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 review
Use when a task needs current external information, live documentation, recent provider/model behavior, pricing, release notes, or source verification beyond the local workspace.
Build polished, specific, non-generic frontend web experiences. Use when designing or implementing UI, landing pages, marketing sites, product UI, dashboards, editorial layouts, or conversion flows. Produces and maintains a project DESIGN.md token system so visual decisions persist across sessions and models.