Borrowing it
Nothing to install: this file belongs to WaniWani-AI/sdk. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/WaniWani-AI/sdk/main/.claude/commands/plan.mdgit clone --depth 1 https://github.com/WaniWani-AI/sdkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/waniwani-ai/sdk/plan)<a href="https://agentmods.dev/commands/waniwani-ai/sdk/plan"><img src="https://agentmods.dev/badge/commands/waniwani-ai/sdk/plan.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00010 | $0.00493 |
| Opus 5 | $0.00005 | $0.00246 |
| Sonnet 5 | $0.00002 | $0.00099 |
| Haiku 4.5 | $0.00001 | $0.00049 |
Grade A, and why
plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Start planning the Linear ticket specified in $ARGUMENTS.
Steps
-
Fetch the Linear ticket using
mcp__linear__get_issuewith the ticket ID from $ARGUMENTS (e.g., "WAN-123")- If the ticket doesn't exist, inform the user and stop
-
Mark the ticket as "In Progress" using
mcp__linear__update_issue:- Set the state to "In Progress"
- This signals to the team that work has started on this ticket
-
Display ticket information to the user:
- Title
- Description
- Status
- Priority
- Any linked issues or parent tickets
-
Enter plan mode using the EnterPlanMode tool to start planning the implementation:
- The plan should be based on the ticket description and acceptance criteria
- Consider the project's architecture and coding standards (from CLAUDE.md)
- Break down the work into concrete implementation steps
Planning Guidelines
When entering plan mode, focus on:
- Understanding the scope - What exactly needs to be built?
- Identifying affected files - Which files need to be created or modified?
- Dependencies - What needs to happen first? (schema → types → API → UI)
- Testing approach - How will the implementation be verified?
- Edge cases - What could go wrong?
Structure the plan following the project's layered approach:
- Database changes (if any)
- Type definitions and Zod schemas
- API endpoints
- Backend logic
- UI components
Example Usage
/plan WAN-123
This will:
- Fetch WAN-123 from Linear
- Mark the ticket as "In Progress"
- Enter plan mode with the ticket context
When to Use /plan vs /implement
- Use
/planwhen you want to plan the work on an existing branch or without branch management - Use
/implementwhen you want to create a dedicated feature branch for the ticket
Error Handling
- If the ticket ID is not provided, ask the user for it
- If the ticket doesn't exist in Linear, inform the user
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 66 lines · 10 tokens per session scan A 857cb9df85aa
plan is a command published in the GitHub repository WaniWani-AI/sdk (17 stars, last pushed 2d ago), licensed MIT. It adds 10 tokens to every session and 493 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
onplana-connect
Connect Claude Code to the Onplana MCP server, then verify it works.
broadcast
Post a message to the project inbox so other sessions on this project can see it. Supports targeting and priority.
gsd:progress
Check progress, advance workflow, or dispatch freeform intent — the unified GSD situational command.
gsd:ship
Create PR, run review, and prepare for merge after verification passes.
backlog
Generate prioritised product backlog from ArcKit artifacts - convert requirements to user stories, organise into sprints.
service-assessment
Prepare for GDS Service Standard assessment - analyze evidence against 14 points, identify gaps, generate readiness report.