# Write Plan

> Create an implementation plan for a multi-step task. Optionally review with external LLMs.

- Skill: `raine/write-plan` (Agent Skill)
- Install (CLI): `npx skillmds@latest add raine/write-plan`
- Raw SKILL.md: https://api.skillmd.com/api/skills/raine/write-plan/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: raine (https://skillmd.com/u/raine)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/raine/write-plan

---


Create an implementation plan for a multi-step task.

User request: $ARGUMENTS

## Flags

Check arguments for optional review flags:
- `--review` → review with both Gemini and Codex (parallel)
- `--gemini` → review with Gemini only
- `--codex` → review with Codex only
- `--claude` → review with a Claude subagent
- No flag → skip review (default)

Strip flags from arguments to get the task description.

## Phase 1: Understand the Task

Start by understanding what exists and what the user wants.

1. If relevant, explore the codebase to understand current state
2. Use `AskUserQuestion` to ask clarifying questions **one at a time**
3. Keep asking until you have enough clarity to write a plan

Rules for questions:

- ONE question per message (never batch multiple questions)
- Use `AskUserQuestion` with 2-4 options whenever possible
- Keep option labels concise (1-5 words), use descriptions for details
- If you realize you misunderstood something, acknowledge it and course-correct

## Phase 2: Write the Plan

Create a plan document with bite-sized tasks. Each task should be a small,
focused unit of work.

### Plan Structure

````markdown
# [Feature Name] Implementation Plan

**Goal:** [One sentence describing what this builds]

**Approach:** [2-3 sentences about the approach]

---

### Task 1: [Short description]

**Files:**

- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py` (lines 123-145)

**Steps:**

1. [Specific action]
2. [Specific action]

**Code:**

```language
// Include actual code, not placeholders like "add validation"
```

---

### Task 2: [Short description]

...
````

### Guidelines

- **Exact file paths** - never "somewhere in src/"
- **Complete code** - show the actual code, not "implement the logic"
- **Small tasks** - each task should be 2-5 minutes of work
- **Assume no context** - write as if the implementer knows nothing about this
  codebase
- **DRY, YAGNI** - only what's needed, no speculative features

## Phase 3: Save

Save the plan:

- Write to a markdown file at `history/<date>-plan-<feature-name>.md` (e.g. `history/2026-02-15-plan-user-auth.md`)
- Include context, decisions made, and rationale

## Phase 4: Review (if flag provided)

**Skip this phase if no review flag was provided.**

Based on the flag, get external feedback on the plan:

### If `--gemini`: Gemini only

Call `mcp__consult-llm__consult_llm` with:
- `model`: "gemini"
- `prompt`: Review prompt below
- `files`: Array including the plan file and relevant source files

### If `--codex`: Codex only

Call `mcp__consult-llm__consult_llm` with:
- `model`: "openai"
- `prompt`: Review prompt below
- `files`: Array including the plan file and relevant source files

### If `--claude`: Claude subagent

Use the Task tool with `subagent_type: "general-purpose"` and a prompt like:
```
Review this implementation plan. The plan is in: [plan file path]

Consider:
- Are the tasks correctly ordered and sized?
- Are there any missing steps or edge cases?
- Are the file paths and code snippets accurate?
- Any architectural concerns or better approaches?

Read the plan file and relevant source files, then provide specific, actionable feedback. Be concise.
```

### If `--review`: Both Gemini and Codex in parallel

Spawn BOTH as parallel subagents (`Agent` tool, `subagent_type: "general-purpose"`, `model: "sonnet"`). NEVER run subagents in the background — always run them in the foreground so you can process their results immediately. Each subagent prompt must include the full review prompt and file list so it can make the MCP call independently.

**Gemini subagent** — prompt must include:
- Call `mcp__consult-llm__consult_llm` with `model: "gemini"`, `prompt`: the review prompt, `files`: [array including the plan file and relevant source files]
- Return the COMPLETE response

**Codex subagent** — prompt must include:
- Call `mcp__consult-llm__consult_llm` with `model: "openai"`, `prompt`: the review prompt, `files`: [array including the plan file and relevant source files]
- Return the COMPLETE response

---

**Review prompt:**
```
Review this implementation plan. Consider:
- Are the tasks correctly ordered and sized?
- Are there any missing steps or edge cases?
- Are the file paths and code snippets accurate?
- Any architectural concerns or better approaches?

Provide specific, actionable feedback. Be concise.
```

After receiving feedback, present it to the user and ask if they want to revise the plan.

## Principles

- **One question at a time** - never batch multiple questions
- **Use AskUserQuestion** - clickable options are faster for the user
- **YAGNI** - ruthlessly cut unnecessary features
- **Validate incrementally** - check understanding at each step
- **Concrete over abstract** - exact paths, actual code, specific commands