717 skills · sorted by relevance
Prepare a personal knowledge base for team sharing by removing compensation, performance assessments, personal details, and other sensitive content. The skill checks pages and searchable records, verifies the cleaned material, and addresses sensitive Git history with explicit confirmation.
Create or improve a company-specific data analysis skill by gathering analysts’ knowledge and examining database structures. Document business terms, metric formulas, table relationships, and common query patterns in reusable reference files.
Test LangBot through its WebUI and compare visible results with backend logs or network behavior. Use it to verify chat, model settings, bots, knowledge bases, and plugins, with recorded evidence for test results.
Build a lasting research knowledge base linking papers, ideas, experiments, and claims. Keep failed approaches and unresolved gaps available for future work, generate compact summaries, and check records for missing connections or conflicting evidence.
Design and implement RAG systems, which retrieve documents to inform AI answers. Get document preparation strategies, vector database comparisons, combined keyword and meaning-based search, result reranking, and an evaluation plan for retrieval quality.
Routes requests about a codebase to the appropriate skill for mapping its structure, generating knowledge graphs, updating documentation, extracting lessons, or storing and recalling project knowledge for future planning.
Search configured Yuxi knowledge bases to answer questions using internal or uploaded documents. Open source text, locate relevant passages, inspect mind maps, and identify supporting files so answers can be traced back to their evidence.
Test whether instructions planted in an agent's long-term memory or searchable knowledge base influence later behavior. Verify both a stored test marker and a resulting change in answers, permissions, or treatment of retrieved documents.
Extract a YouTube video’s full transcript and metadata, meaning details such as its title, channel, and like count, through the BrowserAct API. Use the results as source material for summaries, content research, or knowledge bases.
Manage the lifecycle of an Obsidian project knowledge base by stopping sync, archiving content, or permanently deleting it on explicit request. It also handles individual note archiving, deletion, and renaming with link repair, then summarizes the resulting state.
Set up an Obsidian knowledge base for a research repository containing code and Markdown. It creates project links, planning notes, source inventories, and code summaries, importing structure and summaries while leaving large research artifacts out.
[omh] Scattered knowledge needing a wiki: wiki construction blueprints and retained knowledge capture with destination-aware external knowledge connection guidance. Use when the user says: wiki, project wiki, build a wiki, start a wiki, organize my notes, external knowledge store, knowledge base, Obsidian.
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Expert knowledge for Azure Database Migration Service development including troubleshooting, decision making, limits & quotas, security, integrations & coding patterns, and deployment. Use when planning Azure DMS migrations for MySQL, PostgreSQL, MongoDB, SSIS-to-Azure SQL, or hybrid workloads, and other Azure Database Migration Service related development tasks. Not for Azure Migrate (use azure-migrate), Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines).
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Load project-specific context -- tech stack, architecture overview, directory layout, trusted sources, and conventions -- so that all skills operate with awareness of what this project actually is. Use when a knowledge base document exists, or when the user asks about the project's tech stack, architecture, conventions, framework, directory layout, or says 'tell me about this project', 'what are we using?', 'what's our stack?', or 'what framework is this?'. Use the knowledge-priming-refiner to create a knowledge base document.
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Initialise a project for knowledge base use. Appends the [Knowledge Base] section to the project's CLAUDE.md, creates the library/ directory structure, optionally seeds with three example library files from the Agentic SDLC research, and reports next steps. Run once after installing sdlc-knowledge-base.
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Build AI knowledge base creation systems. TRIGGERS - Use when user needs help with ai-knowledge-base-builder related tasks.
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A persistent, compounding knowledge base combining Karpathy's LLM Wiki pattern with a structured knowledge graph. Ingest documents once — the LLM writes wiki pages, extracts entities/relations into the graph, and stores raw content for evidence retrieval. Knowledge accumulates and cross-references; it is never re-derived from scratch. Use when building a knowledge base from many documents that should accumulate and cross-reference over time instead of being re-read each session.
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Build AI knowledge base creation systems. TRIGGERS - Use when user needs help with ai-knowledge-base-builder related tasks.
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Review database schema design and detect anti-patterns. Based on common RDB design knowledge and best practices. Supports Prisma, Drizzle, Rails, Django, Laravel, TypeORM, Sequelize, SQLAlchemy, and raw SQL (DDL). Use when the user says "review DB design", "check schema", "review table design", "review migration", "check for anti-patterns", "DB設計をレビューして", "スキーマを見て", "テーブル設計を確認して", "マイグレーションをレビューして", "アンチパターンがないか調べて", "この設計で問題ないか見て".
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Expert knowledge of the melosys-api Oracle database schema. Use when: (1) Writing SQL queries against the melosys database, (2) Understanding table relationships and foreign keys, (3) Debugging data issues by querying the database, (4) Understanding what data is stored where, (5) Creating or modifying Flyway migrations, (6) Mapping domain entities to database tables. Triggers: SQL against melosys DB, table/column lookup, FK relationships, "where is X stored", "what column stores X", "why is data missing", beh_resultat_id, behandlingsresultat_id, saksnummer, schema.
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Build document search with AgentDB that finds related content by meaning. Store documents as numerical representations, combine similarity search with metadata filters, and retrieve relevant passages for systems that generate answers using source material.
Build advanced AgentDB workflows with database synchronization, multiple databases, and search that combines meaning with attribute filters. Covers similarity measures, diverse search results, and operational patterns for distributed AI applications.
Ask questions about a codebase using a knowledge graph, a map of its components and relationships. Get explanations tied to specific files, functions, dependencies, and architectural layers, with warnings when the graph may be outdated.
Build document search with AgentDB that finds related content by meaning. Store documents as numerical representations, combine similarity search with metadata filters, and retrieve relevant passages for systems that generate answers using source material.