Loading...
Loading...
Found 2,039 Skills
Guide for building MCP (Model Context Protocol) servers that integrate external APIs/services with LLMs. Covers Python (FastMCP) and TypeScript (MCP SDK) implementations.
Execute Python code locally with marketplace API access for 90%+ token savings on bulk operations. Activates when user requests bulk operations (10+ files), complex multi-step workflows, iterative processing, or mentions efficiency/performance.
NCBI BLAST sequence similarity search using BioPython. Use when a user wants to run BLAST programmatically with blastn/blastp and retrieve results in JSON format.
AlgoKit Utils library for interacting with the Algorand blockchain from TypeScript or Python applications. Use when connecting to Algorand networks (LocalNet, TestNet, MainNet), sending payments or transferring assets, creating and managing accounts, deploying or interacting with smart contracts from client code, or composing transaction groups. NOT for writing smart contract code (use build-smart-contracts skill). Strong triggers include "How do I connect to Algorand?", "send a payment transaction", "create an account", "deploy my contract", "get an AlgorandClient", "AlgorandClient.fromEnvironment".
Deterministic syntax for Frappe Document Controllers (Python server-side). Use when Claude needs to generate code for DocType controllers, lifecycle hooks (validate, on_update, on_submit, etc.), document methods, controller override, submittable documents, or when questions concern controller structure, naming conventions, autoname patterns, UUID naming (v16), or the flags system. Triggers: document controller, controller hook, validate, on_update, on_submit, autoname, naming series, UUID naming, flags system.
Requires detailed type annotations for all Python functions, methods, and class members.
Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks.
Transform this Python script into a polished, beginner-friendly project by refactoring the code, adding clear instructional comments, and generating a complete markdown tutorial.
Use when creating professional architecture diagrams, cloud infrastructure visuals, network topologies, Kubernetes cluster diagrams, or microservices architecture diagrams as PNG/SVG images using Python Diagrams library with real provider icons (AWS, Azure, GCP, K8s, OnPrem, Generic)
PowerPoint翻訳機能の実装・デバッグ・改善を支援する。PPTXファイル処理、python-pptxライブラリ、 Claude API連携、テキスト抽出・挿入、翻訳ワークフロー全体をカバー。翻訳が動かない、 PPTXの処理でエラーが出る、テキスト抽出がおかしい、スライドのレイアウトが崩れるなど、 PPTX翻訳パイプラインに関わる問題が発生したら必ずこのスキルを使うこと。 Cloud Runバックエンドとの連携問題も対象。
Integrate Mem0 Platform into AI applications for persistent memory, personalization, and semantic search. Use this skill when the user mentions "mem0", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python and TypeScript SDKs, framework integrations (LangChain, CrewAI, Vercel AI SDK, OpenAI Agents SDK, Pipecat), and the full Platform API. Use even when the user doesn't explicitly say "mem0" but describes needing conversation memory, user context retention, or knowledge retrieval across sessions.
Instrument Python LLM apps, build golden datasets, write eval-based tests, run them, and root-cause failures — covering the full eval-driven development cycle. Make sure to use this skill whenever a user is developing, testing, QA-ing, evaluating, or benchmarking a Python project that calls an LLM, even if they don't say "evals" explicitly. Use for making sure an AI app works correctly, catching regressions after prompt changes, debugging why an agent started behaving differently, or validating output quality before shipping.