alan-plan — Claude Code skill: implementation plans in Alan
Walks the agent through planning: analyze the task, ask clarifying questions, draft the plan and persist it as an Alan artifact.
npx skills add tryalan-ai/alan-skills --skill alan-plan -a claude-codeWhat alan-plan does
The skill fixes the order of work on an implementation plan. The agent reads the task description and linked context, explores the codebase with Read, Grep and Glob, and writes nothing. When scope is unclear it asks one question per message instead of dumping a list.
The draft is free-form markdown with no required format: a step list, a phased breakdown, a decision tree, or a file-by-file change list. Plans render mermaid, so the skill suggests putting a diagram at the top of a section — sequence for service-to-service calls, erDiagram for tables, flowchart for logic, stateDiagram-v2 for status transitions, C4Container for architecture. Trivial changes go without one.
Then the plan has to be saved with mcp__alan__create_plan, passing taskId, conversationId and teamId; skip that call and the plan is lost. The IDs come from the ALAN_TASK_ID and ALAN_SESSION_ID environment variables, while teamId is resolved through Alan's MCP tools. No Alan MCP server connected means no saved plan. Revisions run as a fresh cycle: the agent re-reads the feedback, goes back to the code, and saves a new version with parentId pointing at the previous artifact.
What it helps with
- get a plan before any code is touched
- pin down a vague task through clarifying questions
- persist the plan as an Alan artifact tied to the task
- rework a plan after feedback and ship a new version
- show architecture or data flow as a mermaid diagram
Example prompts for the agent
- Draft an implementation plan for this task and save it to Alan
- Explore the codebase and plan the schema migration, with a diagram
- Here's feedback on the last plan — revise it and save version 2
How to install alan-plan
1Skills CLI (Vercel)
npx skills add tryalan-ai/alan-skills --skill alan-plan -a claude-code2Manually: put the files in place
~/.claude/skills/alan-plan/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/alan-plan/
1Skills CLI (Vercel)
npx skills add tryalan-ai/alan-skills --skill alan-plan -a codex2Manually: put the files in place
.agents/skills/alan-plan/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add tryalan-ai/alan-skills --skill alan-plan -a cursor2Manually: put the files in place
.cursor/skills/alan-plan/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install tryalan-ai/alan-skills alan-plan2Manually: put the files in place
.github/skills/alan-plan/SKILL.md1Skills CLI (Vercel)
npx skills add tryalan-ai/alan-skills --skill alan-plan -a gemini-cli2Platform CLI
gemini skills install https://github.com/tryalan-ai/alan-skills --path skills/alan-planManually: put the files in place
.devin/skills/alan-plan/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add tryalan-ai/alan-skills --skill alan-plan -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about alan-plan
How do I install alan-plan in Claude?
Run npx skills add tryalan-ai/alan-skills --skill alan-plan -a claude-code. The skill lands in ~/.claude/skills/alan-plan/SKILL.md.
What does alan-plan do?
It moves the agent through analysis, clarifying questions and a markdown draft, then saves the plan as an Alan artifact via mcp__alan__create_plan.
What do I need for the plan to be saved?
A connected Alan MCP server — without the mcp__alan__create_plan call the plan is lost. The agent passes taskId, conversationId and teamId.
Source text
SKILL.md · Apache-2.0
---
name: alan-plan
version: 1.0.1
description: Create an implementation plan artifact in Alan
---
# Plan Creation
You are creating an implementation plan. Your job is to analyze the problem
and produce a clear, actionable plan in markdown.
---
## How to plan
1. **Analyze** — Read the task description and any linked context. Explore the
codebase to understand architecture, dependencies, constraints, and risks.
Use Read, Grep, Glob freely. Do NOT write or modify any files.
If this is a **revision request** (the user references feedback on an existing
plan, or mentions a plan artifact), first fetch the existing plan with
`mcp__alan__get_artifact` to understand what was already proposed.
2. **Clarify** — Before drafting, assess whether the scope is clear enough to
plan against. If it's not — **ask questions. One at a time.**
This is how a senior engineer operates: they don't guess, they don't
silently fill in gaps, they don't plan against assumptions. They ask until
they understand. Walk down each branch of the decision tree and resolve
ambiguity before committing it to a plan.
- Ask **one question per message**. Don't dump a list of 10 questions.
- If a question can be answered by exploring the codebase, explore instead
of asking.
- If the scope or requirements are genuinely unclear, say so directly:
_"I need more clarity on X before I can plan this well."_
- Don't be hesitant about asking. It's not friction — it's quality control.
A plan built on assumptions is worse than no plan.
**Break-glass: when to skip this step.** If the task description is detailed,
subtasks are clear, related documents exist, and the codebase exploration
answered your open questions — go straight to Draft. Don't force
clarification when none is needed. Read the room.
3. **Draft** — Write your plan as natural free-form markdown. Structure it
however makes sense for this specific problem:
- Bullet list of steps
- Phased breakdown with dependencies
- Decision tree with trade-offs
- File-by-file change list
- Whatever communicates the plan most clearly
There is NO required format. Good plans are clear, specific, and actionable.
Include file paths, function names, and reasoning where relevant.
**Be visual.** Plans render mermaid natively. Use diagrams to ground the
reader before the details — pick the right type for what you're showing:
| Diagram | When to use | Mermaid type |
|---|---|---|
| **Sequence** | Service-to-service interactions, API call chains, request lifecycle | `sequenceDiagram` |
| **ER (Schema)** | Database tables & relationships, schema changes | `erDiagram` |
| **Flowchart** | Logic & process flows, decision paths, branching logic | `flowchart TD` |
| **State** | Entity lifecycle, status transitions, workflow states | `stateDiagram-v2` |
| **C4 Container** | System architecture overview, service topology, boundaries | `C4Container` |
| **Data Flow** | How data moves through the system end-to-end | `flowchart LR` |
**Selection rule:** look at what the plan section is explaining, then pick:
- _"How do these services talk?"_ → Sequence
- _"What tables change?"_ → ER
- _"What's the logic?"_ → Flowchart
- _"What states can this be in?"_ → State
- _"What's the high-level architecture?"_ → C4 Container
- _"How does data flow through?"_ → Data Flow (left-to-right flowchart)
Place the diagram at the **top** of the relevant section — it sets context
for the text that follows. Don't diagram trivial changes; use them when the
plan involves multiple components, services, or non-obvious relationships.
Most plans with architectural changes should have at least one diagram.
4. **Persist** — You MUST call the `mcp__alan__create_plan` MCP tool to save
your plan. If you skip this, the plan is lost.
Use the active task context when it is present in the prompt. Otherwise:
- The task ID is available from the `ALAN_TASK_ID` environment variable.
- The conversation ID is available from the `ALAN_SESSION_ID` environment variable.
- Resolve `teamId` with Alan MCP context/tools before creating the plan.
Always pass `taskId`, `conversationId`, and `teamId` explicitly. Do not
substitute one ID for another.
```
Tool: mcp__alan__create_plan
Parameters: {
"title": "Short descriptive title — Version N",
"content": "<your full markdown plan>",
"summary": "One-line summary of what this plan achieves",
"taskId": "<active task ID or value of ALAN_TASK_ID, if set>",
"conversationId": "<active conversation ID or value of ALAN_SESSION_ID>",
"teamId": "<resolved team ID>"
}
```
5. **Exit plan mode** — After persisting, call `ExitPlanMode` to present the
plan for user approval. Lead with the plan title and, when possible, the
artifact link (`/teams/<teamId>/docs?artifactId=<artifactId>`). Do not lead
with a raw UUID; only include it as secondary debug context if no usable
title or link is available. The user will approve, reject, or ask questions.
## Handling feedback and revisions
Feedback is not a patch request — it's a signal that your understanding was
incomplete. Treat it as a new analysis cycle, not a quick edit.
1. **Understand the feedback** — Read every point carefully. What is the user
actually saying? Is it a correction, a concern, a missing requirement, or a
change in direction? Don't assume you know — ask if anything is ambiguous.
2. **Ask before replanning** — If the feedback raises questions, changes scope,
or introduces constraints you hadn't considered — ask. Get clarity before
revising. One good question prevents a bad revision. Don't silently
reinterpret feedback into something you're more comfortable with.
3. **Re-analyze** — Go back to the codebase. The feedback may reveal things you
missed in the first pass. Read the relevant code again. Check assumptions
that the feedback challenges. This is Phase 1 (Analyze) again, not a shortcut.
4. **Revise the plan** — Now rewrite with the deeper understanding. Address
each feedback point explicitly. If you changed your approach, explain why.
5. **Persist the revision** — When saving:
- Use the same title with an incremented version: `"Title — Version 2"`,
`"Title — Version 3"`, etc.
- Set `parentId` to the previous plan's artifact ID — this creates a version
chain and marks the old plan as "superseded"
- Reference the specific feedback points to show they were addressed
- If the feedback includes quoted text (e.g. `On "Setup DB":`), address
that specific section
Use `mcp__alan__get_artifact` to fetch the previous plan if you need to
reference its full content during revision.
## Available tools for plan artifacts
| Tool | Use |
|---|---|
| `mcp__alan__create_plan` | Persist a new plan (or revision with `parentId`) |
| `mcp__alan__get_artifact` | Fetch an existing plan/artifact by ID |
| `mcp__alan__update_artifact` | Update an existing plan's content/metadata |
| `mcp__alan__add_artifact_comment` | Add a comment to a plan artifact |
| `mcp__alan__resolve_artifact_comment` | Resolve a comment on a plan |
## Do NOT
- Write or modify any source files
- Execute destructive commands
- Skip the `create_plan` MCP call — the plan must be persisted
- Use any rigid sections format — write naturally, however the plan is best expressed
© tryalan-ai · Apache-2.0 · tryalan-ai/alan-skills