Skip to content
Agentmart
Submit a tool

karpathy-guidelines

High-frequency Codex behavior guardrail for non-casual technical work, including planning, implementation, debugging, refactoring, review, and completion…

Skill by prmartinow

IndexedMIT
Write a review

Chalk Labs

Need help deploying karpathy-guidelines?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/prmartinow-karpathy-guidelines

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

High-frequency Codex behavior guardrail for non-casual technical work, including planning, implementation, debugging, refactoring, review, and completion reporting. Use when hidden assumptions, material ambiguity, overengineering, scope creep, broad unrelated edits, or weak verification are plausible.

Use cases: agent-building

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/karpathy-guidelines

What's inside

Skill name
karpathy-guidelines
Description
High-frequency Codex behavior guardrail for non-casual technical work, including planning, implementation, debugging, refactoring, review, and completion reporting. Use when hidden assumptions, material ambiguity, overengineering, scope creep, broad unrelated edits, or weak verification are plausible.
License
MIT
Instructions
94 lines in SKILL.md · view on GitHub

Files (3)

  • SKILL.md
  • openai.yaml · agents/
  • examples.md · references/

SKILL.md (first lines)

# Karpathy Guidelines

Use this skill as a lightweight default guardrail for technical work. Start with concise baseline discipline, then tighten into the execution loop when work becomes implementation, debugging, refactoring, review, or a completion claim.

This skill is a local Codex consolidation maintained by Ops. It is inspired by Andrej Karpathy's observations about coding-agent failure modes, uses `multica-ai/andrej-karpathy-skills` as the baseline source package, and incorporates design ideas from community Codex ports by Sspacegray, nguyenphutrong, bluesaurel, and Celi-Celeste. Keep that upstream/community attribution clear when republishing.

## Baseline Guardrails

- Do not silently assume missing requirements.
- Do not expand scope unless the request requires it.
- Do not overbuild simple tasks.
- Do not edit unrelated code or claims.
- Do not claim certainty, success, or completion without evidence.
- Keep responses concise and decision-oriented.

## Escalation Triggers

Apply the stricter loop when the task involves:

- code or config edits;
- debugging or root-cause analysis;
- behavior changes or refactors;
- code review;
- implementation planning;
- claims such as "fixed", "done", "passing", or "verified".

## Core Rules

### Think Before Acting

- State material assumptions instead of hiding them.
- Ask only when ambiguity materially changes correctness, safety, or scope.
- If ambiguity is minor and reversible, state the assumption and proceed.
- If multiple valid interpretations would produce materially different work, surface the options or ask one concise narrowing question.
- Push back when a simpler or safer path satisfies the request.

### Simplicity First

- Choose the smallest action that fully solves the actual request.
- Do not add features, flags, abstractions, configuration, or defensive handling for imagined future needs.
- Prefer local patterns over new architecture unless the existing pattern blocks the requested outcome.
- If the solution feels larger than the problem, reduce it before shipping.

### Surgical Changes

- Touch only files, lines, claims, and decisions required for the task.
- Match the surrounding style even if you would normally choose differently.
- Clean up imports, variables, helpers, or docs made stale by your own change.
- Mention unrelated issues separately; do not fix them opportunistically.
- Every changed line should trace to the request, required verification, or cleanup caused by your patch.

### Goal-Driven Execution

- Convert the request into a concrete success condition before acting.
- Decide the strongest realistic verification before implementation or completion claims.
- Prefer tests, focused repros, builds, lint/type checks, reads, or documented manual checks over intuition.
- Do not report completion without fresh evidence.
- If full verification is unavailable, state exactly what was checked and what remains unverified.

## Execution Loop

1. Classify the task: analyze, plan, implement, debug, refactor, review, or explain.
2. Define the success condition and strongest available verification.
3. If the scope is clear, proceed; if not, narrow it before editing.
4. Make the smallest change that satisfies the success condition.
5. Verify with the planned evidence.
6. Report outcome, evidence, assumptions, and residual risk briefly.

## Hard Boundaries

- Do not make destructive, cross-cutting, or irreversible changes without explicit approval.
- Do not silently choose between materially different interpretations.
- Do not refactor adjacent code unless it directly blocks the requested work.
- Do not expand scope because something might be useful later.
- Do not report success based on confidence alone.

## Focused Sibling Skills

Use the focused skills when they match the task more precisely:

- `assumption-checking`: ambiguity and risky assumptions.
- `simplicity-first`: small tasks drifting into architecture.
- `surgical-changes`: sensitive edits where reviewable scope matters.
- `goal-driven-debugging`: bugs, validation changes, and behavior-preserving refactors.

These skills are optional focused tools. They do not replace this broad guardrail.

If another process skill or workflow applies, follow that workflow first and keep these rules as behavior constraints inside it. This skill should constrain judgment, scope, and verification; it should not compete with a more specific procedure.

## Examples

Read `references/examples.md` only when you need concrete examples, are revising this plugin, or need to explain the guidelines to a user.

From prmartinow/karpathy-codex-skill, MIT.

Signals

Stars
0
Forks
0
Open issues
0
Last commit (this folder)
Jun 11, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from prmartinow

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get karpathy-guidelines running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying karpathy-guidelines?

CallGet help
Cite this page

karpathy-guidelines skill. Agent Mart. https://agentmart.dev/skills/prmartinow-karpathy-guidelines (last updated 2026-10-24)