Loading...
Loading...
Found 739 Skills
Full-stack hybrid memory system with vector + keyword search. Stores embeddings in SQLite with FTS5 for BM25 keyword search and cosine similarity. Enables semantic memory recall for agents.
Hot-reload Go apps with cosmtrek/air during development. Use when setting up dev workflows for Go HTTP servers, configuring .air.toml, or debugging hot-reload issues with SQLite, port binding, or file watchers.
Record transaction flow in accordance with unified rules. Save records by individual stock in Markdown format, and simultaneously write to SQLite for statistics and quantitative review.
Use when the user asks to write SQL queries, optimize database performance, generate migrations, explore database schemas, or work with ORMs like Prisma, Drizzle, TypeORM, or SQLAlchemy.
Run Neo4j Graph Analytics algorithms (PageRank, Louvain, WCC, Dijkstra, KNN, Node2Vec, FastRP, GraphSAGE) directly inside Snowflake without moving data. Use when running graph algorithms against Snowflake tables via the Neo4j Snowflake Native App ("GDS Snowflake", "graph algorithms in Snowflake", "Neo4j Graph Analytics"). Covers installation, privilege setup, project-compute-write pattern, and SQL CALL syntax. Does NOT cover Cypher or Neo4j DBMS queries — use neo4j-cypher-skill. Does NOT cover Aura Graph Analytics — use neo4j-aura-graph-analytics-skill. Does NOT cover self-managed GDS — use neo4j-gds-skill.
Manage LLMem — structured memory system with SQLite-backed factual memory, semantic search, and background dreaming (decay, boost, promote, merge). Use when the user wants to: (1) add, search, update, or delete memories, (2) generate context for injection, (3) check memory stats, (4) run background consolidation/dream. Triggers on: "memory", "remember", "recall", "llmem", "memories", "forget", "consolidate memories", "dream".
Salesforce Data Cloud Segment phase. Use this skill when the user creates or publishes segments, manages calculated insights, or troubleshoots audience SQL in Data Cloud. TRIGGER when: user creates or publishes segments, manages calculated insights, inspects segment counts or membership, or troubleshoots audience SQL in Data Cloud. DO NOT TRIGGER when: the task is DMO/mapping/identity-resolution work (use harmonizing-datacloud), activation work (use activating-datacloud), query/search-index work (use retrieving-datacloud), or Standard Data Model (STDM)/session tracing (use observing-agentforce).
Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces). Covers HogQL syntax differences from ClickHouse SQL, system table schemas (system.*), available functions, query examples, and the schema-discovery workflow.
Alibaba Cloud PolarDB-X Distributed Database AI Assistant. Use for PolarDB-X cluster management, topology inspection, performance diagnostics, SQL optimization, data distribution analysis, elastic scaling diagnostics, connection/session analysis, security audit, backup/restore, parameter tuning, and other O&M operations. Triggers: "PolarDB-X", "distributed database", "pxc-", "DN/CN nodes", "data sharding", "PolarDB-X diagnostics", "PolarDB-X performance", "PolarDB-X slow SQL", "YaoChi Agent", "PolarDB-X topology", "PolarDB-X backup", "PolarDB-X security audit", "PolarDB-X scaling"
Queries data warehouse and answers business questions about data. Handles questions requiring database/warehouse queries including "who uses X", "how many Y", "show me Z", "find customers", "what is the count", data lookups, metrics, trends, or SQL analysis.
Expert FastAPI developer specializing in production-ready async REST APIs with Pydantic v2, SQLAlchemy 2.0, OAuth2/JWT authentication, and comprehensive security. Deep expertise in dependency injection, background tasks, async database operations, input validation, and OWASP security best practices. Use when building high-performance Python web APIs, implementing authentication systems, or securing API endpoints.
For writing and executing SQL queries - from simple single-table queries to complex multi-table JOINs and aggregations