About karpathy-planning
A planning skill for defining task scope, assumptions, and verifiable completion criteria. It favors simple approaches, reuses existing components, and proceeds to implementation when authorized and unblocked.
Key features
- 01Define scope and assumptions
- 02Resolve material ambiguities
- 03Prefer simple reusable designs
- 04Pair criteria with verification
- 05Adapt plans to task size
Use cases
- 01Planning a coding task before implementation
- 02Clarifying assumptions that affect outcomes
- 03Choosing checks for completion criteria
Install
Copy the command and run it in a terminal.
$
npx skills add https:/After installing, type/karpathy-planningin Claude Code to confirm it loaded.
Bundled filesagents/openai.yaml
Details
From the project READMEkarpathy-planning
Produce a plan that establishes scope, important assumptions, and verifiable completion. Include only the detail needed to choose an approach and carry out the task.
- Resolve material ambiguities from available context. Ask when an answer would change the outcome; otherwise state a reasonable assumption.
- Prefer the simplest design that meets the request. Identify existing components to reuse and preserve unrelated work.
- Pair success criteria with relevant verification. Complete required checks; broaden testing only for changes, failures, or unresolved concerns.
- Describe substantial tradeoffs, dependencies, or irreversible steps when they matter.
- Match the output to the task. A four-part template and a repository-wide survey are not prerequisites to coding.
- If implementation is already authorized, proceed once blocking decisions are resolved; planning alone is not completion.
Adapted from multica-ai/andrej-karpathy-skills.
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