Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
501 skills found
Enforces a strict evidence-before-assertion protocol for coding agents, requiring fresh command-line verification output before any claim of completion, success, or bug fixes.
Implement ReasoningBank adaptive learning with AgentDB's ultra-fast vector backend. Features trajectory tracking, verdict judgment, memory distillation, and pattern recognition for self-learning autonomous agents.
Handles large-scale tasks by automatically breaking them down into manageable, recursive sub-tasks to overcome context window limits and improve reasoning accuracy on large codebases and document sets.
Direct access to the Opper REST API for LLM orchestration, model management, task execution, and seamless migration from OpenAI, Anthropic, or OpenRouter.
Validates and coordinates batch study guide operations, preventing errors by enforcing template compatibility, file availability, and source-only policies before agent execution.
Perform cohort analysis on user engagement data. Identify retention trends, feature adoption rates, churn patterns, and generate actionable research recommendations through quantitative data analysis.
Provides real-time weather forecasts and personalized clothing recommendations for any city using wttr.in.
Fetch YouTube transcripts and subtitles. Ideal for video summarization, language learning, accessibility, and content analysis. Supports timestamped data and raw text extraction.
Interactive Archon integration for knowledge base and project management. Features RAG-powered semantic search, website crawling, document versioning, and hierarchical task management via REST API.
Generate a structured academic paper outline from research narrative, experiment data, and review conclusions.
Transforms feature requests, bug reports, and improvement ideas into structured, actionable markdown project plans using repository research and industry best practices.
Process massive files and large codebases (10M+ tokens) by recursively chunking, sub-querying, and aggregating results to overcome LLM context limits.