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/project-planning.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/project-planning)<a href="https://agentmods.dev/commands/waniwani-ai/sdk/project-planning"><img src="https://agentmods.dev/badge/commands/waniwani-ai/sdk/project-planning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/waniwani-ai/sdk/project-planning"><img src="https://agentmods.dev/badge/commands/waniwani-ai/sdk/project-planning.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00012 | $0.01334 |
| Opus 5 | $0.00006 | $0.00667 |
| Sonnet 5 | $0.00002 | $0.00267 |
| Haiku 4.5 | $0.00001 | $0.00133 |
Grade A, and why
project-planning 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create implementation tickets for the Linear project specified in $ARGUMENTS.
Steps
- Fetch project details using
mcp__linear__get_projectwith the project name from $ARGUMENTS - Fetch team info using
mcp__linear__list_teamsto get the team ID for creating issues - Analyze the project description to understand:
- The overall goal and scope
- Key implementation areas (database, API, UI, etc.)
- Dependencies between components
- Break down into atomic tickets following these principles:
- Each ticket should be completable by a single agent in isolation
- Tickets should have clear inputs and outputs
- Dependencies should be explicit (use Linear's blocking relations)
- Group by layer: Schema → Types → API → Backend Logic → UI
- Present the plan for approval - Show the user the complete ticket breakdown:
- Display each planned ticket with title and description summary
- Show the dependency graph (what blocks what)
- Highlight parallelization opportunities
- Ask the user to approve before proceeding
- Wait for user approval - Use AskUserQuestion to get explicit confirmation:
- Option to approve and create all tickets
- Option to request modifications to the plan
- Option to cancel
- Create tickets in Linear (only after approval) using
mcp__linear__create_issuefor each ticket - Set up dependencies using the
blocksparameter when creating issues - Summarize the created tickets to the user
Plan Presentation Format
Before creating tickets, present the plan to the user in this format:
## Proposed Implementation Plan for [Project Name]
### Summary
[Brief overview of the approach and total number of tickets]
### Ticket Breakdown
#### Layer 1: Database (X tickets)
1. **[Title]** - [One-line description]
2. **[Title]** - [One-line description]
#### Layer 2: Types (X tickets)
3. **[Title]** - [One-line description]
- Blocked by: #1
#### Layer 3: API (X tickets)
4. **[Title]** - [One-line description]
- Blocked by: #1, #3
[Continue for all layers...]
### Dependency Graph
#1 Database Schema
├── #3 Types (blocked by #1)
│ └── #5 Service (blocked by #3, #4)
└── #4 API Endpoints (blocked by #1)
└── #6 UI Components (blocked by #4)
#2 Config Setup (independent)
### Parallelization Opportunities
- **Phase 1** (can start immediately): #1, #2
- **Phase 2** (after Phase 1): #3, #4
- **Phase 3** (after Phase 2): #5, #6
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.
- 9d ago First seen · 176 lines · 12 tokens per session scan A 0f2d761c2909
project-planning is a command published in the GitHub repository WaniWani-AI/sdk (17 stars, last pushed yesterday), licensed MIT. It adds 12 tokens to every session and 1,334 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.
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gsd:ship
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backlog
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roadmap
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