karpathy-agentic-guidelines-q8
Compact q8 Karpathy-inspired agentic coding guidance.
Skill by TheAngryPit
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/theangrypit-karpathy-agentic-guidelines-q8
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.
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About
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/karpathy-agentic-guidelines-q8
What's inside
- Skill name
karpathy-agentic-guidelines-q8- Description
- Compact q8 Karpathy-inspired agentic coding guidance. Use when you need bounded autonomy, verification discipline, and context control without loading the full skill.
- License
- MIT
- Instructions
- 190 lines in SKILL.md · view on GitHub
Files (2)
- SKILL.md
- research-loop.md · references/
SKILL.md (first lines)
# Karpathy Agentic Guidelines - Q8 Compact ## Overview Use agents for generation and iteration. Keep human authority over intent, truth, review, and release. This quantized variant keeps only the highest-signal operating rules in `SKILL.md`. Load references only when the task is exploratory enough to need them. ## When to Use Use when: - the task is large enough that agent loops are useful - assumptions could silently drift - success criteria are clearer than the implementation path - you care about keeping the result understandable - the work involves delegation, verification, or bounded autonomy Do not use when: - the task is trivial - there is no meaningful verification surface yet - the real problem is missing product direction, not execution discipline For exploratory optimization or research-like loops, also load: - [research-loop.md](references/research-loop.md) ## Core Rules ### 1. Program in Outcomes Prefer: - success criteria - invariants - boundaries - explicit non-goals Do not over-specify the path unless the path itself matters. ### 2. Make Assumptions Explicit Require the agent to: - surface assumptions that matter - name unclear inputs - call out conflicting evidence - push back when the requested shape looks riskier than a simpler one Silent assumption choice is one of the main failure modes. ### 3. Keep a Human Review Surface Open Agents generate. Humans discriminate. Review the actual changed files and check that every changed line traces back to the request. Do not treat "it ran" as sufficient proof. ### 4. Pick the Lightest Viable Mode Choose the smallest execution mode that preserves clarity: - `direct execution` for small, obvious, low-risk work - `declarative plan` when success is clear but the path should stay flexible - `task-sliced plan` when multiple files or checkpoints matter - `supervised delegation` when tasks can be isolated cleanly Do not default to either maximum ceremony or maximum autonomy. ### 4.5. Use Defaults, Not Menus When multiple paths could work: - pick one default - say why it is the default - keep alternatives as escape hatches For example: - `direct execution` is the default for small, obvious bugfixes - `task-sliced plan` is the default for research loops or multi-surface work ### 5. Bias Toward Simple Construction Prefer: - direct code - local reasoning - fewer moving parts - the naive correct version first Do not invent extra helper layers, config surfaces, or abstractions without need. ### 6. Treat Unrelated Edits as Regressions Do not allow: - unrelated refactors - style churn - comment churn - orthogonal deletions Clean up only what your requested change made unnecessary. ### 7. Anchor the Loop Use: - failing tests - reproducible bug cases - browser or runtime checks - explicit output contracts - diff constraints If the loop has no anchor, it will drift. ### 8. Control Autonomy Use bounded autonomy: - scoped tasks - explicit authority boundaries - visible verification - clear escalation points Do not let any session become a hidden planning authority, hidden truth source, or hidden release gate.
From TheAngryPit/TheAngrySkills, MIT.
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Signals
- Stars
- 0
- Forks
- 1
- Open issues
- 0
- Last commit (this folder)
- Jul 2, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/TheAngryPit/TheAngrySkills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Use when changing or proving OpenClaw Control UI behavior with deterministic Gateway fixtures, browser flows, rendered evidence or interaction profiling.
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Cite this page
karpathy-agentic-guidelines-q8 skill. Agent Mart. https://agentmart.dev/skills/theangrypit-karpathy-agentic-guidelines-q8 (last updated 2026-10-24)