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Found 38 Skills
Search the web and read documentation when stuck or learning something new
Use this skill when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. This skill provides access to 600+ scientific tools including machine learning models, datasets, APIs, and analysis packages. Use when searching for scientific tools, executing computational biology workflows, composing multi-step research pipelines, accessing databases like OpenTargets/PubChem/UniProt/PDB/ChEMBL, performing tool discovery for research tasks, or integrating scientific computational resources into LLM workflows.
Specialized agent for multi-repository analysis, searching remote codebases, retrieving official documentation, and finding implementation examples using GitHub CLI, Context7, and Web Search. Use proactively when unfamiliar libraries or frameworks are involved, working with external dependencies, or needing examples from open-source projects to understand best practices and real-world implementations.
Automatically check and update folder-specific AGENTS.md during research. Before investigating a domain, read nearest AGENTS.md for existing context. After discovering valuable patterns, append learnings to that file.
Researches topics and trends for blog content with parallel multi-agent execution. USE WHEN orchestrator invokes research phase OR user says 'research topic', 'find trends', 'gather information for blog'.
Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.
Use when creating or developing anything, before writing code or implementation plans - refines rough ideas into fully-formed designs through structured Socratic questioning, alternative exploration, and incremental validation
Conduct deep research on any topic through structured investigation design. Use when the user needs comprehensive, multi-source analysis -- not a quick lookup. Triggers: deep research, comprehensive analysis, research report, compare X vs Y, analyze trends, investigate, or any request requiring synthesis across multiple perspectives. Do NOT use for simple questions answerable with 1-2 searches or for debugging.
Read research outline, launch independent agent for each item for deep research. Disable task output.
Delegate noisy investigation to one or more subagents so the orchestrator's context stays clean, then work from the distilled answer. Use this skill whenever answering a question would require reading many files, long logs, large diffs, or wide codebase surveys — i.e. when producing the answer generates far more noise than the answer itself. Use it for "how does X work", "where is Y used", "what's the root cause of Z", "summarize this PR/log" style questions, and reach for it liberally before reading a pile of files inline.
Deep web research with parallel investigators, multi-wave exploration, and structured synthesis. Spawns multiple web-researcher agents to explore different facets of a topic simultaneously, launches additional waves when gaps are identified, then synthesizes findings. Use when asked to research, investigate, compare options, find best practices, or gather comprehensive information from the web.\n\nThoroughness: quick for factual lookups | medium for focused topics | thorough for comparisons/evaluations (waves continue while critical gaps remain) | very-thorough for comprehensive research (waves continue until satisficed). Auto-selects if not specified.
Fetch and compile arXiv papers on LLMs, autonomous agents, and AI infrastructure into scored, grouped research digests. Stores digests at ~/.aibtc/arxiv-research/digests/. No API key required.