Total 50,706 skills, AI & Machine Learning has 8496 skills
Showing 12 of 8496 skills
Analyze finance text sentiment using FinBERT or LLM. Use when the user needs to determine the sentiment (positive/negative/neutral) and score of financial text markets.
Synthesize structured directives and command specifications. Creates executable instruction sets with proper syntax and parameter definitions.
This skill should be used for multi-session autonomous agent work requiring progress checkpointing, failure recovery, and task dependency management. Triggers on '/harness' command, or when a task involves many subtasks needing progress persistence, sleep/resume cycles across context windows, recovery from mid-task failures with partial state, or distributed work across multiple agent sessions. Synthesized from Anthropic and OpenAI engineering practices for long-running agents.
Proactively discover, install, and create Claude skills for specialized tasks. AUTOMATICALLY activates when encountering niche domains, unfamiliar APIs, specialized knowledge areas, or when user expresses wanting to learn/know something new. Searches the community registry at claude-plugins.dev and auto-installs matching skills. Creates new skills when no match exists. Use when user says "I want to know...", "help me with [specialized domain]", or when you recognize a task requires specialized expertise you don't have.
Log a workflow mistake, fix its root cause, and graduate the lesson to learned memory. Use when the agent makes an error you want to prevent recurring.
Comprehensive quality audit for Claude Code agents, skills, and commands with comparative analysis
Meta-skill for making the agent self-improving. Covers updating AGENTS.md, creating new skills from repeated workflows, and deciding what to systematize. Invoke after completing tasks, when noticing repeated friction, or at session end.
Creates, updates, or optimizes an AGENTS.md file for a repository with minimal, high-signal instructions covering non-discoverable coding conventions, tooling quirks, workflow preferences, and project-specific rules that agents cannot infer from reading the codebase. Use when setting up agent instructions or Claude configuration for a new repository, when an existing AGENTS.md is too long, generic, or stale, when agents repeatedly make avoidable mistakes, or when repository workflows have changed and the agent configuration needs pruning. Applies a discoverability filter—omitting anything Claude can learn from README, code, config, or directory structure—and a quality gate to verify each line remains accurate and operationally significant.
Conduct comprehensive research on any topic. Synthesize information from multiple angles, provide structured analysis, and generate detailed research reports.
Integration patterns for Mapbox MCP Server in AI applications and agent frameworks. Covers runtime integration with pydantic-ai, mastra, LangChain, and custom agents. Use when building AI-powered applications that need geospatial capabilities.
Expert guidance for Anthropic Claude API development including Messages API, tool use, prompt engineering, and building production applications with Claude models.
Coin comparison. Use this skill whenever the user asks to compare two or more coins. Trigger phrases include: compare, versus, vs, which is better, difference. MCP tools: info_marketsnapshot_get_market_snapshot, info_coin_get_coin_info per coin (or batch/search when available).