Catalog
All AI skills
20 skills. Every one is readable here; downloads and live use need a subscription.
yann-lecun-tecnico
Sub-skill técnica de Yann LeCun. Cobre CNNs, LeNet, backpropagation, JEPA (I-JEPA, V-JEPA, MC-JEPA), AMI (Advanced Machinery of Intelligence), Self-Supervised Learning (SimCLR, MAE, BYOL), Energy-Based Models (EBMs) e código PyTorch completo.
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
polis-protocol-a-self-optimizing-city-of-agents
Polis Protocol: A Self-Optimizing City of Agents
anti-sleep
Keep a Mac awake with caffeinate during long builds, downloads, or supervised automation runs.
agent-qa-debug-fix
Debug, patch, and verify failed Agent QA runs from MCP evidence, artifacts, logs, and local code without hiding product or infrastructure defects.
ai-native-cli
Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.
audit-agent-run-evidence
Use when an agent, harness, gateway, MCP workflow, or multi-step automation claims completion and the available traces, checkpoints, approvals, tool calls, or deployment records must be judged without trusting self-reported success.
autonomous-agents
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.
blueprint
Turn a one-line objective into a step-by-step construction plan any coding agent can execute cold. Each step has a self-contained context brief — a fresh agent in a new session can pick up any step without reading prior steps.
evolution
This skill enables makepad-skills to self-improve continuously during development.
github-actions-advanced
Design, debug, and harden GitHub Actions CI/CD workflows, including reusable workflows, matrix builds, self-hosted runners, OIDC authentication, caching, environments, secrets, and release automation.
mesh-memory
Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.
papers-skill
Skill for academic research workflows: search Semantic Scholar (200M+ papers), inspect citations, download arXiv PDFs, and extract PDF text. Bundles a self-contained Python CLI.
poka-yoke
Mistake-proof code, config and process: make the wrong action impossible or self-announcing rather than documented.
polis-protocol
Coordinate multi-vendor AI agents as a self-improving team — a learning router assigns work by track record and citizens can amend the protocol's own rules.
pr-merge-champion
Optimize pull requests for quick approval and merging by ensuring clean diffs, comprehensive self-reviews, and structured documentation.
test-automator
Master AI-powered test automation with modern frameworks, self-healing tests, and comprehensive quality engineering. Build scalable testing strategies with advanced CI/CD integration.
time-ledger
Natural-language time tracking: parse what the user says they did into Activity/Minutes/Date rows in their own Notion database — asking instead of guessing when unsure.
unified-ai-gateway
Operate and evaluate Unified AI System through nine governed MCP tools, including provider-free prompt enhancement, while preserving fake-provider, authorization, and evidence boundaries.