2.4천건 · 관련도순
Use when working with Deno Deploy Deep — deep Deno Deploy analysis covering project inventory, deployment history, KV database usage, cron job schedules, custom domain mappings, analytics metrics, and environment variable auditing. Use for comprehensive Deno Deploy platform management.
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Use when working with Appwrite — appwrite backend platform management covering project inventory, database collections, user authentication stats, storage bucket usage, function deployments, webhook configuration, and platform health. Use for comprehensive Appwrite project assessment and resource monitoring.
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Use when working with Alibaba Cloud — alibaba Cloud infrastructure management via the aliyun CLI. Covers ECS instances, RDS databases, VPCs, SLB load balancers, OSS storage, and billing. Use when managing Alibaba Cloud resources or checking infrastructure health.
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Use when working with Aws Rds Deep — aWS RDS deep analysis covering Performance Insights, event subscriptions, proxy management, and global database status. Covers PI counter metrics, wait event analysis, top SQL queries, read replica lag, storage autoscaling, and Aurora-specific diagnostics.
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Use when working with Azure Cosmos Db — azure Cosmos DB throughput analysis, partition key distribution, consistency levels, metrics monitoring, and database management via Azure CLI.
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Use when working with Aws Glue — aWS Glue crawler management, ETL job run analysis, Data Catalog exploration, and schema registry management. Covers crawler schedules, job performance metrics, database and table inventory, partition analysis, and connection health.
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Use when working with Neo4J — neo4j graph database analysis, index management, Cypher query optimization, APOC utilities, and cluster health monitoring.
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PostgreSQL database analysis, performance tuning, and health monitoring. You MUST read this entire skill document before executing any PostgreSQL operations — it contains mandatory workflows, safety constraints, and two-phase execution rules that prevent common errors like hallucinated column names and unsafe queries.
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Use when working with Planetscale — planetScale branch management, deploy requests, schema analysis, query insights, and database health.
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Use when working with Mongodb — mongoDB database analysis, performance tuning, query optimization, and health monitoring. Covers collection analysis, index recommendations, aggregation pipelines, replica set health, Atlas cluster management, and slow query investigation.
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Use when working with Mysql — mySQL and MariaDB database analysis, performance tuning, query optimization, and health monitoring. Covers slow query investigation, index analysis, table statistics, replication health, InnoDB status, connection pool analysis, and schema inspection.
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Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.
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Access AlphaFold DB's 200M+ predicted structures by UniProt ID. Download PDB/mmCIF, analyze pLDDT/PAE, bulk-fetch proteomes via Google Cloud. For experimental structures use PDB; for prediction use ColabFold or ESMFold.
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Search and retrieve preprints from arXiv via the Atom API. Use this skill when searching for papers in physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering, or economics by keywords, authors, arXiv IDs, date ranges, or categories.
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Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.
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Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
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Use when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).
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Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.
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Notion workspace management via MCP - create databases, pages, comments, and knowledge bases. Use when building Notion documentation, organizing project wikis, or managing Notion content.
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PHP 8.0+ development — XAMPP, RESTful APIs, PDO/MySQL/MariaDB, and authentication. Use when building PHP backends, creating API endpoints, configuring XAMPP, or integrating PHP with databases.
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Expert en Airtable (bases, views, automations, scripts, interfaces, extensions)
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Expert en Airtable avancé (bases, views, automations, scripts, integrations, API)
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Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications.
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RAG (Retrieval-Augmented Generation) implementation workflow covering embedding selection, vector database setup, chunking strategies, and retrieval optimization.
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