codebase-index
Index project files for semantic code search. Supports incremental updates, progress tracking, and batch embedding generation.
Discover testing security llm ai skills, compare source repositories and read the instructions for each workflow.
Index project files for semantic code search. Supports incremental updates, progress tracking, and batch embedding generation.
Compress memories into structured summaries using low-cost AI models (Claude Haiku, GPT-4o-mini). Triggers when memory count exceeds 50 or token estimate exceeds 40000. Outputs structured JSON with compression...
Create, edit, and analyze Word documents with formatting, templates, and content generation (Official Anthropic skill)
Create, edit, and analyze PowerPoint presentations with AI-powered slide generation, template management, and content extraction (Official Anthropic skill)
Documentation for the main LLM performance experiments (exps_performance)
Generate new Agent Skills following the open standard specification. Use this when asked to create a new skill, teach Copilot a new capability, or capture domain expertise as a reusable skill.
Developer Relations toolkit for Nostr ecosystem and freedom tech. Use for community building, developer advocacy, conference prep, Shakespeare demos/workshops, and decentralized social evangelism.
Comprehensive administrative support for task management, meeting notes, email drafting, document organization, and staying on track. Use for any organizational, scheduling, or administrative work.
Guide for creating new Claude Code skills following best practices. Use when the user asks to create a new skill, agent capability, or wants to extend Claude's autonomous functionality.
Guide for creating, configuring, and distributing Claude Code plugins with hooks, skills, commands, and MCP servers. Use when user asks to create a plugin, set up hooks, add plugin functionality, create a marke...
Send Slack messages and DMs as yourself directly from Claude Code using your browser session credentials. Extracts the target channel or user and message content directly from natural language prompts. Supports...
Convert AI fluency into throughput by embedding AI into repeatable workflows with triggers, quality gates, and iteration loops that compound over time.
Assess AI fluency proficiency using 5-level certification criteria (A through E) based on demonstrated capabilities across the 4D Framework dimensions.
Select appropriate human-AI collaboration modes: Automation (AI acts independently), Augmentation (AI assists human work), or Agency (AI takes delegated responsibility).
Recognize and avoid 15 common AI fluency anti-patterns that undermine effectiveness: over-reliance, prompt magic thinking, verification theater, and more.
Control AI output through structured specifications: define roles, scope, format, decision rules, and abstraction levels. Prompts become contracts, not requests.
Apply Anthropic's 4D Framework for AI delegation: Delegation (task selection), Description (instructions), Discernment (verification), and Diligence (iteration).
Turn vague intent into solvable structures with explicit objectives, constraints, success criteria, and clear human vs AI responsibility boundaries.
Scale AI fluency beyond individuals through standards, guardrails, audit trails, and organizational policies that maintain quality and accountability.
Retain epistemic control by validating AI outputs against logic, first principles, and reality. Detect confident nonsense, false completeness, and category errors.
Build accurate mental models of AI behavior: understand context windows, probabilistic generation, hallucination causes, and predict failure modes before they occur.
Use AI as a thinking partner by injecting checklists, reasoning trees, critique loops, and stepwise logic. Delegate sub-reasoning without losing coherence.
Use AI to reshape strategic decisions, not just execution. Identify where AI creates competitive advantage, shifts constraints, and enables new business models.
Develop pre-fluency cognitive habits: recognize when not to use AI, separate thinking from generation, resist automation bias and output authority.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.