agentic-engineering
Skill2 starsChanged 4 months agoMITView on GitHub
Apply Karpathy agentic engineering discipline: think before coding, minimal diffs, surgical changes, test-verified completion. Use for any implementation task in vpeetla-ai repos when quality bar matters.
We split this skill into the rules it gives an agent
4 rules. 0 are common, 3 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 22 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 11
Not vibe coding — preserve professional quality while moving faster.
- Distinctive: line 17
Read surrounding files — match naming, types, error handling
- Very specific: line 27
Run relevant tests (pytest -q, npm test, typecheck)
- Distinctive: line 35
No test strategy for new behavior
“Common” is measured: kept by at least 6 in 10 of the 22 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agentic Engineering
Not vibe coding — preserve professional quality while moving faster.
Before writing code
- State assumptions and success criteria (tests, API response, UI behavior)
- Identify smallest change that satisfies the request
- Read surrounding files — match naming, types, error handling
While coding
- Simplicity first — no speculative abstractions or "while I'm here" refactors
- Surgical diffs — touch only files required for the task
- Match conventions — see target repo's pyproject.toml, eslint, existing patterns
Before claiming done
- Run relevant tests (
pytest -q,npm test, typecheck) - For agent graphs: verify routing + at least one happy-path trace
- Summarize what changed and what was not changed (scope boundary)
Red flags — stop and ask
- Request touches governance + orchestration in one PR (split layers)
- Side effect without gateway/HITL (publish, push, notify)
- No test strategy for new behavior
Reference
Karpathy: From Vibe Coding to Agentic Engineering
Other versions28 projects use a version of this.
Word for word · 4
- vpeetla-ai/aegisai-enterprise-agent-platform★ 2100% same
- vpeetla-ai/multi-agent-system-pattern★ 2100% same
- vpeetla-ai/reflection-agent-pattern★ 2100% same
- vpeetla-ai/swarm-agent-pattern★ 2100% same
Edited · 0
None found.
Wrote their own version · 24
- loulanyue/awesome-claude-notes★ 272same name
- Fmarzochi/EGC★ 61same name
- drvoss/everything-copilot-cli★ 49same name
- gongyijie85/dsh-ecc★ 8same name
- bjornjee/skills★ 2same name
- joelbrilliant/agentic-delivery-skills★ 2same name
- ronmkr/PromptBook★ 2same name
- get-proofpilot/claude-skills-catalog★ 1same name
- HarambeeAI/bayes-ship★ 1same name
- junimnjw/everything-claude-code★ 1same name
14 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
Used alongsideProjects with it also use nuxt4-patterns, dart-flutter-patterns and 1 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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In this repository13 other files it gives its agents.
- AGENTS.mdAGENTS.md
- aegis-gatewaySkill
- deploy-vercel-renderSkill
- governed-ai-stackSkill
- grill-with-contextSkill
- hitl-side-effectsSkill
- langgraph-orchestrationSkill
- loop-engineeringSkill
- portfolio-adrSkill
- rag-governanceSkill
- repo-fix-prSkill
- setup-vpeetla-skillsSkill
- tdd-agent-loopsSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Your trail
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Now do this for your own.
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