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Found 1,813 Skills
Mass spectrometry toolkit (OpenMS Python). Process mzML/mzXML, peak picking, feature detection, peptide ID, proteomics/metabolomics workflows, for LC-MS/MS analysis.
Build conversational AI agents using Pydantic AI + OpenRouter. Use when creating type-safe Python agents with tool calling, validation, and streaming.
Sets up a Mac for ButterCut. Installs all required dependencies (Homebrew, Ruby, Python, FFmpeg, WhisperX). Use when user says "install buttercut", "set up my mac", "get started", "first time setup", "install dependencies" or "check my installation".
Use this skill when you need to test or evaluate LangGraph/LangChain agents: writing unit or integration tests, generating test scaffolds, mocking LLM/tool behavior, running trajectory evaluation (match or LLM-as-judge), running LangSmith dataset evaluations, and comparing two agent versions with A/B-style offline analysis. Use it for Python and JavaScript/TypeScript workflows, evaluator design, experiment setup, regression gates, and debugging flaky/incorrect evaluation results.
Initialize, validate, and troubleshoot Deep Agents projects in Python or JavaScript using the `deepagents` package. Use when users need to create agents with built-in planning/filesystem/subagents, configure middleware/backends/checkpointing/HITL, migrate from `create_react_agent` or `create_agent`, scaffold projects with repo scripts, validate agent config files, and confirm compatibility with current LangChain/LangGraph/LangSmith docs.
Setup Sentry Tracing (Performance Monitoring) in any project. Use this when asked to add performance monitoring, enable tracing, track transactions/spans, or instrument application performance. Supports JavaScript, TypeScript, Python, Ruby, React, Next.js, and Node.js.
Setup Spanora AI observability in any project (JavaScript/TypeScript or Python). Use when user asks to "add spanora", "setup spanora", "integrate spanora", "add AI observability", "monitor LLM calls with spanora", "track AI costs", or mentions spanora in the context of adding observability to their project. Detects the language and installed AI SDKs (Vercel AI, Anthropic, OpenAI, LangChain) and configures the optimal integration pattern.
Central authority for Claude Code status line configuration. Covers custom status line creation, /statusline command, status line settings (statusLine in settings.json), JSON input structure (model, workspace, cost, session info), status line scripts (Bash, Python, Node.js), terminal color codes, git-aware status lines, helper functions, and status line troubleshooting. Supports creating custom status lines, configuring status line behavior, and displaying contextual session information. Delegates 100% to docs-management skill for official documentation.
Compare Nim and Python scripted agent implementations and align behavior. Use when asked to port or ensure parity between Nim and Python.
Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
Create or improve Makefiles with minimal complexity. Templates available: base, python-uv, python-fastapi, nodejs, go, chrome-extension, flutter.
Generate publication-ready scientific figures in Python/matplotlib with a consistent figures4papers house style. Use when creating or refining academic bar/trend/heatmap/scatter/multi-panel figures, enforcing visual consistency, or exporting paper-ready PNG/PDF/SVG outputs.