libwally-core: Blockstream's C library for wallet primitives. BIP32/39, PSBT, Liquid Confidential Transactions, BIP143, Schnorr. Bindings to Python, JS, Java, Swift. USE WHEN: building cross-language wallets via libwally bindings, integrating Liquid CT.

mempool.js (@mempool/mempool.js): TypeScript client for mempool.space API. REST + WebSocket; address history, fee estimates, mining stats. USE WHEN: integrating mempool.space data, building wallets / explorers.

rust-dlc: Rust DLC implementation. Funding, CET construction, oracle attestation handling, refund logic. USE WHEN: building DLC apps in Rust, integrating oracle-driven Bitcoin contracts.

libsecp256k1: the canonical secp256k1 C library. Used by Bitcoin Core, rust-secp256k1, all major language bindings. USE WHEN: low-level crypto in C/C++, building bindings, performance- critical paths.

rust-secp256k1: Rust bindings to libsecp256k1 (C). ECDSA, Schnorr, ECDH, key tweaking, MuSig2 (in newer versions). USE WHEN: low-level crypto in Rust, working with raw secp256k1 operations.

Nigiri: regtest stack with Bitcoin + Esplora + electrs + Liquid + optional LN. CLI-based, fast iteration, includes faucet. USE WHEN: regtest with explorer dependency, full-stack E2E testing, dev environment with Esplora API.

Polar: GUI for spinning up Lightning regtest networks. Supports LND, CLN, Eclair, LDK Node. Per-node config, payment simulation, channel topology editor. USE WHEN: building / testing Lightning apps, designing regtest channel topologies, demoing LN flows.

Regtest mode: instant block generation, deterministic fork, multi-node setup, generatetoaddress, fallbackfee config. USE WHEN: building Bitcoin tests, simulating network conditions, scaffolding integration tests.

bcoin: full-node Bitcoin implementation in JavaScript. Wallets, HTTP API, SPV mode. Alternative to running bitcoind. USE WHEN: needing a Node-native Bitcoin full node, evaluating alternative implementations.

bdk-jvm / bdk-android: Kotlin/Java bindings to BDK. Same descriptor- first wallet API. UniFFI-generated. USE WHEN: building JVM / Android wallets with BDK quality.

bolt11 decoder libraries: parse / encode BOLT11 Lightning invoices in JS, Python, Rust, Go. USE WHEN: parsing LN invoices in app code, building Lightning payment flows.

This skill provides reusable implementation patterns extracted from the better-chatbot project for custom AI chatbot deployments. Use this skill when building AI chatbots with server action validators, tool abstraction systems, workflow execution, or multi-AI provider integration in your own projects (not contributing to better-chatbot itself). Use when: building AI chatbot features, implementing server action validators, creating tool abstraction layers, setting up multi-AI provider support, building workflow execution systems, adapting better-chatbot patterns to custom projects Keywords: AI chatbot patterns, server action validators, tool abstraction, multi-AI providers, workflow execution, MCP integration, validated actions, tool type checking, Vercel AI SDK patterns, chatbot architecture

This skill provides comprehensive knowledge for working with the Anthropic Claude Agent SDK. It should be used when building autonomous AI agents, creating multi-step reasoning workflows, orchestrating specialized subagents, integrating custom tools and MCP servers, or implementing production-ready agentic systems with Claude Code's capabilities. Use when building coding agents, SRE systems, security auditors, incident responders, code review bots, or any autonomous system that requires programmatic interaction with Claude Code CLI, persistent sessions, tool orchestration, and fine-grained permission control. Keywords: claude agent sdk, @anthropic-ai/claude-agent-sdk, query(), createSdkMcpServer, AgentDefinition, tool(), claude subagents, mcp servers, autonomous agents, agentic loops, session management, permissionMode, canUseTool, multi-agent orchestration, settingSources, CLI not found, context length exceeded

Comprehensive guide for the Cloudflare Agents SDK - build AI-powered autonomous agents on Workers + Durable Objects. Use when: building AI agents, creating stateful agents with WebSockets, implementing chat agents with streaming, scheduling tasks with cron/delays, running asynchronous workflows, building RAG (Retrieval Augmented Generation) systems with Vectorize, creating MCP (Model Context Protocol) servers, implementing human-in-the-loop workflows, browsing the web with Browser Rendering, managing agent state with SQL, syncing state between agents and clients, calling agents from Workers, building multi-agent systems, or encountering Agent configuration errors. Prevents 15+ documented issues: migrations not atomic, missing new_sqlite_classes, Agent class not exported, binding name mismatch, global uniqueness gotchas, WebSocket state handling, scheduled task callback errors, state size limits, workflow binding missing, browser binding required, vectorize index not found, MCP transport confusion, authentication bypassed, instance naming errors, and state sync failures. Keywords: Cloudflare Agents, agents sdk, cloudflare agents sdk, Agent class, Durable Objects agents, stateful agents, WebSocket agents, this.setState, this.sql, this.schedule, schedule tasks, cron agents, run workflows, agent workflows, browse web, puppeteer agents, browser rendering, rag agents, vectorize agents, embeddings, mcp server, McpAgent, mcp tools, model context protocol, routeAgentRequest, getAgentByName, useAgent hook, AgentClient, agentFetch, useAgentChat, AIChatAgent, chat agents, streaming chat, human in the loop, hitl agents, multi-agent, agent orchestration, autonomous agents, long-running agents, AI SDK, Workers AI, "Agent class must extend", "new_sqlite_classes", "migrations required", "binding not found", "agent not exported", "callback does not exist", "state limit exceeded"

Complete knowledge domain for Cloudflare D1 - serverless SQLite database on Cloudflare's edge network. Use when: creating D1 databases, writing SQL migrations, configuring D1 bindings, querying D1 from Workers, handling SQLite data, building relational data models, or encountering "D1_ERROR", "statement too long", "too many requests queued", migration failures, or query performance issues. Keywords: d1, d1 database, cloudflare d1, wrangler d1, d1 migrations, d1 bindings, sqlite workers, serverless database, edge database, d1 queries, sql cloudflare, prepared statements, batch queries, d1 api, wrangler migrations, D1_ERROR, D1_EXEC_ERROR, statement too long, database bindings, sqlite cloudflare, sql workers api, d1 indexes, query optimization, d1 schema

Comprehensive guide for Cloudflare Durable Objects - globally unique, stateful objects for coordination, real-time communication, and persistent state management. Use when: building real-time applications, creating WebSocket servers with hibernation, implementing chat rooms or multiplayer games, coordinating between multiple clients, managing per-user or per-room state, implementing rate limiting or session management, scheduling tasks with alarms, building queues or workflows, or encountering "do class export", "new_sqlite_classes", "migrations required", "websocket hibernation", "alarm api error", or "global uniqueness" errors. Prevents 15+ documented issues: class not exported, missing migrations, wrong migration type, constructor overhead blocking hibernation, setTimeout breaking hibernation, in-memory state lost on hibernation, outgoing WebSocket not hibernating, global uniqueness confusion, partial deleteAll on KV backend, binding name mismatches, state size limits exceeded, non-atomic migrations, location hints misunderstood, alarm retry failures, and fetch calls blocking hibernation. Keywords: durable objects, cloudflare do, DurableObject class, do bindings, websocket hibernation, do state api, ctx.storage.sql, ctx.acceptWebSocket, webSocketMessage, alarm() handler, storage.setAlarm, idFromName, newUniqueId, getByName, DurableObjectStub, serializeAttachment, real-time cloudflare, multiplayer cloudflare, chat room workers, coordination cloudflare, stateful workers, new_sqlite_classes, do migrations, location hints, RPC methods, blockConcurrencyWhile, "do class export", "new_sqlite_classes", "migrations required", "websocket hibernation", "alarm api error", "global uniqueness", "binding not found"

Complete knowledge domain for Cloudflare Hyperdrive - connecting Cloudflare Workers to existing PostgreSQL and MySQL databases with global connection pooling, query caching, and reduced latency. Use when: connecting Workers to existing databases, migrating PostgreSQL/MySQL to Cloudflare, setting up connection pooling, configuring Hyperdrive bindings, using node-postgres/postgres.js/mysql2 drivers, integrating Drizzle ORM or Prisma ORM, or encountering "Failed to acquire a connection from the pool", "TLS not supported by the database", "connection refused", "nodejs_compat missing", "Code generation from strings disallowed", or Hyperdrive configuration errors. Keywords: hyperdrive, cloudflare hyperdrive, workers hyperdrive, postgres workers, mysql workers, connection pooling, query caching, node-postgres, pg, postgres.js, mysql2, drizzle hyperdrive, prisma hyperdrive, workers rds, workers aurora, workers neon, workers supabase, database acceleration, hybrid architecture, cloudflare tunnel database, wrangler hyperdrive, hyperdrive bindings, local development hyperdrive

Use this skill when building Model Context Protocol (MCP) servers on Cloudflare Workers. This skill should be used when deploying remote MCP servers with TypeScript, implementing OAuth authentication (GitHub, Google, Azure, etc.), using Durable Objects for stateful MCP servers, implementing WebSocket hibernation for cost optimization, or configuring dual transport methods (SSE + Streamable HTTP). The skill prevents 15+ common errors including McpAgent class export issues, OAuth redirect URI mismatches, WebSocket state loss, Durable Objects binding errors, and CORS configuration mistakes. Includes production-tested templates for basic MCP servers, OAuth proxy integration, stateful servers with Durable Objects, and complete wrangler.jsonc configurations. Covers all 4 authentication patterns: token validation, remote OAuth with DCR, OAuth proxy (workers-oauth-provider), and full OAuth provider implementation. Self-contained with Worker and Durable Objects basics. Token efficiency: ~87% savings (40k → 5k tokens). Production tested on Cloudflare's official MCP servers. Keywords: MCP server, Model Context Protocol, cloudflare mcp, mcp workers, remote mcp server, mcp typescript, @modelcontextprotocol/sdk, mcp oauth, mcp authentication, github oauth mcp, durable objects mcp, websocket hibernation, mcp sse, streamable http, McpAgent class, mcp tools, mcp resources, mcp prompts, oauth proxy, workers-oauth-provider, mcp deployment, McpAgent export error, OAuth redirect URI, WebSocket state loss, mcp cors, mcp dcr

Complete knowledge domain for Cloudflare R2 - S3-compatible object storage on Cloudflare's edge network. Use when: creating R2 buckets, uploading files to R2, downloading objects, configuring R2 bindings, setting up CORS, generating presigned URLs, multipart uploads, storing images/assets, managing object metadata, or encountering "R2_ERROR", CORS errors, presigned URL failures, multipart upload issues, or storage quota errors. Keywords: r2, r2 storage, cloudflare r2, r2 bucket, r2 upload, r2 download, r2 binding, object storage, s3 compatible, r2 cors, presigned urls, multipart upload, r2 api, r2 workers, file upload, asset storage, R2_ERROR, R2Bucket, r2 metadata, custom metadata, http metadata, content-type, cache-control, aws4fetch, s3 client, bulk delete, r2 list, storage class

This skill provides comprehensive knowledge for building applications with Cloudflare Sandboxes SDK, which enables secure, isolated code execution in full Linux containers at the edge. It should be used when executing untrusted code, running Python/Node.js scripts, performing git operations, building AI code execution systems, creating interactive development environments, or implementing CI/CD workflows that require full OS capabilities. Use when: Setting up Cloudflare Sandboxes, executing Python/Node.js code safely, managing stateful development environments, implementing AI code interpreters, running shell commands in isolation, handling git repositories programmatically, building chat-based coding agents, creating temporary build environments, processing files with system tools (ffmpeg, imagemagick, etc.), or when encountering issues with container lifecycle, session management, or state persistence. Keywords: cloudflare sandbox, container execution, code execution, isolated environment, durable objects, linux container, python execution, node execution, git operations, code interpreter, AI agents, session management, ephemeral container, workspace, sandbox SDK, @cloudflare/sandbox, exec(), getSandbox(), runCode(), gitCheckout(), ubuntu container

Production-tested setup for Cloudflare Workers with Hono, Vite, and Static Assets. Use when: creating new Cloudflare Workers projects, setting up Hono routing with Workers, configuring Vite plugin for Workers, adding Static Assets to Workers, deploying with Wrangler, or encountering deployment errors, routing conflicts, or HMR crashes. Prevents 6 documented issues: export syntax errors, Static Assets routing conflicts, scheduled handler errors, HMR race conditions, upload race conditions, and Service Worker format confusion. Keywords: Cloudflare Workers, CF Workers, Hono, wrangler, Vite, Static Assets, @cloudflare/vite-plugin, wrangler.jsonc, ES Module, run_worker_first, SPA fallback, API routes, serverless, edge computing, "Cannot read properties of undefined", "Static Assets 404", "A hanging Promise was canceled", "Handler does not export", deployment fails, routing not working, HMR crashes

Type-safe ORM for Cloudflare D1 databases using Drizzle. This skill provides comprehensive patterns for schema definition, migrations management, type-safe queries, relations, and Cloudflare Workers integration. Use when: building D1 database schemas, writing type-safe SQL queries, managing database migrations with Drizzle Kit, defining table relations, implementing prepared statements, using D1 batch API for transactions, or encountering "D1_ERROR", transaction errors, foreign key constraint failures, migration apply errors, or schema inference issues. Prevents 12 documented issues: D1 transaction errors (SQL BEGIN not supported), foreign key constraint failures during migrations, module import errors with Wrangler, D1 binding not found, migration apply failures, schema TypeScript inference errors, prepared statement caching issues, transaction rollback patterns, TypeScript strict mode errors, drizzle.config.ts not found, remote vs local database confusion, and wrangler.toml vs wrangler.jsonc mixing. Keywords: drizzle orm, drizzle d1, type-safe sql, drizzle schema, drizzle migrations, drizzle kit, orm cloudflare, d1 orm, drizzle typescript, drizzle relations, drizzle transactions, drizzle query builder, schema definition, prepared statements, drizzle batch, migration management, relational queries, drizzle joins, D1_ERROR, BEGIN TRANSACTION d1, foreign key constraint, migration failed, schema not found, d1 binding error

Use this skill when building MCP (Model Context Protocol) servers with FastMCP in Python. FastMCP is a framework for creating servers that expose tools, resources, and prompts to LLMs like Claude. The skill covers server creation, tool/resource definitions, storage backends (memory/disk/Redis/DynamoDB), server lifespans, middleware system (8 built-in types), server composition (import/mount), OAuth Proxy, authentication patterns, icons, OpenAPI integration, client configuration, cloud deployment (FastMCP Cloud), error handling, and production patterns. It prevents 25+ common errors including storage misconfiguration, lifespan issues, middleware order errors, circular imports, module-level server issues, async/await confusion, OAuth security vulnerabilities, and cloud deployment failures. Includes templates for basic servers, storage backends, middleware, server composition, OAuth proxy, API integrations, testing, and self-contained production architectures. Keywords: FastMCP, MCP server Python, Model Context Protocol Python, fastmcp framework, mcp tools, mcp resources, mcp prompts, fastmcp storage, fastmcp memory storage, fastmcp disk storage, fastmcp redis, fastmcp dynamodb, fastmcp lifespan, fastmcp middleware, fastmcp oauth proxy, server composition mcp, fastmcp import, fastmcp mount, fastmcp cloud, fastmcp deployment, mcp authentication, fastmcp icons, openapi mcp, claude mcp server, fastmcp testing, storage misconfiguration, lifespan issues, middleware order, circular imports, module-level server, async await mcp

This skill provides complete coverage of Google Gemini embeddings API (gemini-embedding-001) for building RAG systems, semantic search, document clustering, and similarity matching. Use when implementing vector search with Google's embedding models, integrating with Cloudflare Vectorize, or building retrieval-augmented generation systems. Covers SDK usage (@google/genai), fetch-based Workers implementation, batch processing, 8 task types (RETRIEVAL_QUERY, RETRIEVAL_DOCUMENT, SEMANTIC_SIMILARITY, etc.), dimension optimization (128-3072), and cosine similarity calculations. Prevents 8+ embedding-specific errors including dimension mismatches, incorrect task types, rate limiting issues (100 RPM free tier), vector normalization mistakes, text truncation (2,048 token limit), and model version confusion. Includes production-ready RAG patterns with Cloudflare Vectorize integration, chunking strategies, and caching patterns. Token savings: ~60%. Production tested. Keywords: gemini embeddings, gemini-embedding-001, google embeddings, semantic search, RAG, vector search, document clustering, similarity search, retrieval augmented generation, vectorize integration, cloudflare vectorize embeddings, 768 dimensions, embed content gemini, batch embeddings, embeddings api, cosine similarity, vector normalization, retrieval query, retrieval document, task types, dimension mismatch, embeddings rate limit, text truncation, @google/genai

This skill provides comprehensive knowledge for building type-safe APIs with Hono, focusing on routing patterns, middleware composition, request validation, RPC client/server patterns, error handling, and context management. Use when: building APIs with Hono (any runtime), setting up request validation with Zod/Valibot/Typia/ArkType validators, creating type-safe RPC client/server communication, implementing custom middleware, handling errors with HTTPException, extending Hono context with custom variables, or encountering middleware type inference issues, validation hook confusion, or RPC performance problems. Keywords: hono, hono routing, hono middleware, hono rpc, hono validator, zod validator, valibot validator, type-safe api, hono context, hono error handling, HTTPException, c.req.valid, middleware composition, hono hooks, typed routes, hono client, middleware response not typed, hono validation failed, hono rpc type inference

Complete guide for OpenAI's Assistants API v2: stateful conversational AI with built-in tools (Code Interpreter, File Search, Function Calling), vector stores for RAG (up to 10,000 files), thread/run lifecycle management, and streaming patterns. Both Node.js SDK and fetch approaches. ⚠️ DEPRECATION NOTICE: OpenAI plans to sunset Assistants API in H1 2026 in favor of Responses API. This skill remains valuable for existing apps and migration planning. Use when: building stateful chatbots with OpenAI, implementing RAG with vector stores, executing Python code with Code Interpreter, using file search for document Q&A, managing conversation threads, streaming assistant responses, or encountering errors like "thread already has active run", vector store indexing delays, run polling timeouts, or file upload issues. Keywords: openai assistants, assistants api, openai threads, openai runs, code interpreter assistant, file search openai, vector store openai, openai rag, assistant streaming, thread persistence, stateful chatbot, thread already has active run, run status polling, vector store error

Use this skill when building MCP (Model Context Protocol) servers with TypeScript on Cloudflare Workers. This skill provides production-tested patterns for implementing tools, resources, and prompts using the official @modelcontextprotocol/sdk. It prevents 10+ common errors including export syntax issues, schema validation failures, memory leaks from unclosed transports, CORS misconfigurations, and authentication vulnerabilities. This skill should be used when developers need stateless MCP servers for API integrations, external tool exposure, or serverless edge deployments. For stateful agents with WebSockets and persistent storage, consider the Cloudflare Agents SDK instead. Supports multiple authentication methods (API keys, OAuth, Zero Trust), Cloudflare service integrations (D1, KV, R2, Vectorize), and comprehensive testing strategies. Production tested with token savings of ~70% vs manual implementation. Keywords: mcp, model context protocol, typescript mcp, cloudflare workers mcp, mcp server, mcp tools, mcp resources, mcp sdk, @modelcontextprotocol/sdk, hono mcp, streamablehttpservertransport, mcp authentication, mcp cloudflare, edge mcp server, serverless mcp, typescript mcp server, mcp api, llm tools, ai tools, cloudflare d1 mcp, cloudflare kv mcp, mcp testing, mcp deployment, wrangler mcp, export syntax error, schema validation error, memory leak mcp, cors mcp, rate limiting mcp

Complete knowledge domain for Cloudflare Workers KV - global, low-latency key-value storage on Cloudflare's edge network. Use when: creating KV namespaces, storing configuration data, caching API responses, managing user preferences, implementing TTL expiration, handling KV metadata, or encountering "KV_ERROR", "429 too many requests", "kv rate limit", cacheTtl errors, or eventual consistency issues. Keywords: kv storage, cloudflare kv, workers kv, kv namespace, kv bindings, kv cache, kv ttl, kv metadata, kv list, kv pagination, cache optimization, edge caching, KV_ERROR, 429 too many requests, kv rate limit, eventually consistent, wrangler kv, kv operations, key value storage

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.

Generates production-ready API clients with TypeScript types, retry logic, rate limiting, authentication (OAuth, API keys), error handling, and mock responses. Use when user says "integrate API", "API client", "connect to service", or requests third-party service integration.

Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.

Primary Python toolkit for molecular biology. Preferred for Python-based PubMed/NCBI queries (Bio.Entrez), sequence manipulation, file parsing (FASTA, GenBank, FASTQ, PDB), advanced BLAST workflows, structures, phylogenetics. For quick BLAST, use gget. For direct REST API, use pubmed-database.

Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database).

Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.

Test authenticated routes in the your project using cookie-based authentication. Use this skill when testing API endpoints, validating route functionality, or debugging authentication issues. Includes patterns for using test-auth-route.js and mock authentication.

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical research and patient matching.

Query NCBI ClinVar for variant clinical significance. Search by gene/position, interpret pathogenicity classifications, access via E-utilities API or FTP, annotate VCFs, for genomic medicine.

DNAnexus cloud genomics platform. Build apps/applets, manage data (upload/download), dxpy Python SDK, run workflows, FASTQ/BAM/VCF, for genomics pipeline development and execution.

Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.

Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.

Lab automation platform for Flex/OT-2 robots. Write Protocol API v2 protocols, liquid handling, hardware modules (heater-shaker, thermocycler), labware management, for automated pipetting workflows.

Query PubChem via PUG-REST API/PubChemPy (110M+ compounds). Search by name/CID/SMILES, retrieve properties, similarity/substructure searches, bioactivity, for cheminformatics.

Query STRING API for protein-protein interactions (59M proteins, 20B interactions). Network analysis, GO/KEGG enrichment, interaction discovery, 5000+ species, for systems biology.

Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.

Comprehensive backend development guide for Node.js/Express/TypeScript microservices. Use when creating routes, controllers, services, repositories, middleware, or working with Express APIs, Prisma database access, Sentry error tracking, Zod validation, unifiedConfig, dependency injection, or async patterns. Covers layered architecture (routes → controllers → services → repositories), BaseController pattern, error handling, performance monitoring, testing strategies, and migration from legacy patterns.

Electronic lab notebook API integration. Access notebooks, manage entries/attachments, backup notebooks, integrate with Protocols.io/Jupyter/REDCap, for programmatic ELN workflows.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Query Ensembl genome database REST API for 250+ species. Gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, VEP predictions, for genomic research.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Access European Nucleotide Archive via API/FTP. Retrieve DNA/RNA sequences, raw reads (FASTQ), genome assemblies by accession, for genomics and bioinformatics pipelines. Supports multiple formats.

Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.

Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.

Securely authenticate with GitHub using stored credentials for API operations and git commands

Keycloak administration including realm management, client configuration, OAuth 2.0 setup, user management with custom attributes, role and group management, theme deployment, and token configuration. Activate for Keycloak Admin API operations, authentication setup, and identity provider configuration.

Keycloak administration including realm management, client configuration, OAuth 2.0 setup, user management with custom attributes, role and group management, theme deployment, and token configuration. Activate for Keycloak Admin API operations, authentication setup, and identity provider configuration.

This skill should be used when the user asks to "add WebSocket", "implement real-time", "create file upload", "add S3 upload", "send email", "implement notifications", "broadcast events", or mentions WebSockets, file storage, email service, push notifications, or real-time communication. Provides WebSocket, file upload, and notification patterns.

This skill should be used when the user asks to "add WebSocket", "implement real-time", "create file upload", "add S3 upload", "send email", "implement notifications", "broadcast events", or mentions WebSockets, file storage, email service, push notifications, or real-time communication. Provides WebSocket, file upload, and notification patterns.

This skill should be used when the user asks to "add logging", "implement metrics", "add tracing", "configure Prometheus", "setup OpenTelemetry", "add health checks", "monitor API", or mentions observability, APM, monitoring, structured logging, distributed tracing, or Grafana. Provides comprehensive observability patterns.

This skill should be used when the user asks to "add logging", "implement metrics", "add tracing", "configure Prometheus", "setup OpenTelemetry", "add health checks", "monitor API", or mentions observability, APM, monitoring, structured logging, distributed tracing, or Grafana. Provides comprehensive observability patterns.

This skill should be used when the user asks to "add Keycloak authentication", "implement OIDC", "configure SSO", "validate JWT token", "add role-based access", "protect API endpoint", or mentions Keycloak, OAuth2, OpenID Connect, identity provider, or authentication in FastAPI. Provides Keycloak/OIDC integration patterns.

This skill should be used when the user asks to "add Keycloak authentication", "implement OIDC", "configure SSO", "validate JWT token", "add role-based access", "protect API endpoint", or mentions Keycloak, OAuth2, OpenID Connect, identity provider, or authentication in FastAPI. Provides Keycloak/OIDC integration patterns.

MUI X Charts — BarChart, LineChart, PieChart, ScatterChart, composition API, custom axes, tooltips, and responsive patterns

MUI X Charts — BarChart, LineChart, PieChart, ScatterChart, composition API, custom axes, tooltips, and responsive patterns

This skill should be used when the user asks to "add caching", "implement Redis cache", "cache API response", "invalidate cache", "add cache layer", "optimize with caching", or mentions Redis, caching strategies, cache invalidation, or performance optimization. Provides Redis caching patterns for FastAPI.

This skill should be used when the user asks to "add caching", "implement Redis cache", "cache API response", "invalidate cache", "add cache layer", "optimize with caching", or mentions Redis, caching strategies, cache invalidation, or performance optimization. Provides Redis caching patterns for FastAPI.

This skill should be used when the user asks to "create MongoDB model", "define Beanie document", "write MongoDB query", "create aggregation pipeline", "run database migration", "index MongoDB collection", or mentions Beanie, Motor, MongoDB documents, or async database operations. Provides MongoDB/Beanie ODM patterns for FastAPI.

This skill should be used when the user asks to "create MongoDB model", "define Beanie document", "write MongoDB query", "create aggregation pipeline", "run database migration", "index MongoDB collection", or mentions Beanie, Motor, MongoDB documents, or async database operations. Provides MongoDB/Beanie ODM patterns for FastAPI.

This skill should be used when the user asks to "create background task", "add async job", "implement task queue", "schedule periodic task", "use Celery", "use ARQ", "process async", or mentions background processing, task queues, job scheduling, workers, or async jobs. Provides multiple task queue framework patterns.

This skill should be used when the user asks to "create background task", "add async job", "implement task queue", "schedule periodic task", "use Celery", "use ARQ", "process async", or mentions background processing, task queues, job scheduling, workers, or async jobs. Provides multiple task queue framework patterns.

ASP.NET Core API development with minimal APIs, controllers, middleware, OpenAPI, and best practices

ASP.NET Core API development with minimal APIs, controllers, middleware, OpenAPI, and best practices

This skill should be used when writing or reviewing GraphQL queries against the Linear API — selecting fragments, navigating connection types, batching, and avoiding deprecated fields. Activates on "linear graphql", "linear query", "linear api", "linear schema".

This skill should be used when writing or reviewing GraphQL queries against the Linear API — selecting fragments, navigating connection types, batching, and avoiding deprecated fields. Activates on "linear graphql", "linear query", "linear api", "linear schema".

This skill should be used when implementing Linear integrations using the official @linear/sdk — creating issues programmatically, advanced fetch/modify patterns, error handling, and type safety. Activates on "linear sdk", "@linear/sdk", "linear client", "linear typescript".

This skill should be used when implementing Linear integrations using the official @linear/sdk — creating issues programmatically, advanced fetch/modify patterns, error handling, and type safety. Activates on "linear sdk", "@linear/sdk", "linear client", "linear typescript".

# Claude Agent SDK

# Claude Agent SDK

Universal reference for Claude Code automation surface — hooks, skills, plugins, sub-agents, agent teams, MCP, scheduled tasks, channels, routines, headless/SDK, checkpointing, permissions. Invoke when designing automations that leverage Claude Code features or when user asks "how do I automate X with Claude Code".

Universal reference for Claude Code automation surface — hooks, skills, plugins, sub-agents, agent teams, MCP, scheduled tasks, channels, routines, headless/SDK, checkpointing, permissions. Invoke when designing automations that leverage Claude Code features or when user asks "how do I automate X with Claude Code".

Using and creating project templates for webapp, API, ML pipeline, mobile, and infrastructure projects

Using and creating project templates for webapp, API, ML pipeline, mobile, and infrastructure projects

Core Home Assistant API integration patterns, authentication, and entity management.

Core Home Assistant API integration patterns, authentication, and entity management.

Tests authentication and authorization mechanisms in mobile application APIs to identify broken authentication, insecure token management, session fixation, privilege escalation, and IDOR vulnerabilities. Use when performing API security assessments against mobile app backends, testing JWT implementations, evaluating OAuth flows, or assessing session management. Activates for requests involving mobile API auth testing, token security assessment, OAuth mobile flow testing, or API authorization bypass.

Intercepts and analyzes HTTP/HTTPS traffic from mobile applications using Burp Suite proxy to identify insecure API communications, authentication flaws, data leakage, and server-side vulnerabilities. Use when performing mobile application penetration testing, assessing API security, or evaluating client-server communication patterns. Activates for requests involving mobile traffic interception, Burp Suite mobile proxy, API security testing, or mobile HTTPS analysis.

This skill covers integrating OWASP ZAP (Zed Attack Proxy) for Dynamic Application Security Testing in CI/CD pipelines. It addresses configuring baseline, full, and API scans against running applications, interpreting ZAP findings, tuning scan policies, and establishing DAST quality gates in GitHub Actions and GitLab CI.

Deploys and configures osquery for real-time endpoint monitoring using SQL-based queries to inspect running processes, open ports, installed software, and system configuration. Use when building visibility into endpoint state, threat hunting across fleet, or implementing compliance monitoring. Activates for requests involving osquery deployment, endpoint visibility, fleet management, or SQL-based endpoint querying.

Conduct a thick client application penetration test to identify insecure local storage, hardcoded credentials, DLL hijacking, memory manipulation, and insecure API communication in desktop applications using dnSpy, Procmon, and Burp Suite.

Detect and exploit NoSQL injection vulnerabilities in MongoDB, CouchDB, and other NoSQL databases to demonstrate authentication bypass, data extraction, and unauthorized access risks.

Integrate FIRST's Exploit Prediction Scoring System (EPSS) API to prioritize vulnerability remediation based on real-world exploitation probability within 30 days.

Configure and execute agentless vulnerability scanning using network protocols, cloud snapshot analysis, and API-based discovery to assess systems without installing endpoint agents.

Perform forensic acquisition and analysis of cloud storage services including Google Drive, OneDrive, Dropbox, and Box by collecting both API-based remote data and local sync client artifacts from endpoint devices.

Kubernetes penetration testing systematically evaluates cluster security by simulating attacker techniques against the API server, kubelet, etcd, pods, RBAC, network policies, and secrets. Using tools