karpathy-triplet-diag
Skill8 starsChanged 6 months agoNo licenceView on GitHub
Use this when: am I ready for auto-improvement, is my system ready for the Karpathy Loop, can I run autoresearch on this, evaluate auto-improvement readiness, define the editable surface, define the optimization metric, define the experiment time budget, write a program.md spec, build a program.md, optimization target spec, agent loop readiness, can an agent optimize this, is my pipeline ready for autoresearch, surface metric budget triplet, blocker report for auto-improvement, what's blocking my autoresearch loop, scope an optimization target, can I hand this to an agent loop, is this system loop-ready
In this repository74 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- agentic-economy-readiness-testSkill
- ai-innovation-radarSkill
- ai-skills-devSkill
- ai-systems-architectSkill
- agp-9-upgradeSkill
- android-autoSkill
- android-ble-hardwareSkill
- android-bluetoothSkill
- camera1-to-cameraxSkill
- android-cliSkill
- migrate-xml-views-to-jetpack-composeSkill
- android-compose-realtimeSkill
- android-foreground-serviceSkill
- navigation-3Skill
- android-obdSkill
- android-on-device-mlSkill
- play-billing-library-version-upgradeSkill
- r8-analyzerSkill
- android-securitySkill
- android-telemetry-pipelineSkill
- android-video-captureSkill
- api-integrationSkill
- arbitrage-auditSkill
- archivebox-knowledgeSkill
- browser-automationSkill
- career-gap-mapSkill
- cicd-pipelineSkill
- code-reviewerSkill
- content-strategySkill
- continue-from-acceptedSkill
- database-architectureSkill
- data-engineeringSkill
- deep-research-proSkill
- deploy-pipelineSkill
- docker-selfhostSkill
- federated-memorySkill
- five-verticals-positioning-auditSkill
- frontend-design-proSkill
- full-sdlcSkill
- github-workflowSkill
- grafana-prometheus-monitoringSkill
- gws-assistant-proSkill
- ham-radio-networkSkill
- harness-engineeringSkill
- homelab-commanderSkill
- infrastructure-as-codeSkill
- ios-developerSkill
- karpathy-metric-preSkill
- karpathy-trace-infrastructureSkill
- llm-inference-stackSkill
- mcp-server-devSkill
- mission-control-proSkill
- model-archive-managementSkill
- orchestration-scaffoldSkill
- org-level-model-dependencySkill
- outcome-based-system-promptSkill
- productivity-automationSkill
- project-orchestrator-proSkill
- proxmox-k3s-infraSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
11 rules. About 0 are common, 11 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈11
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

