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Found 1,213 Skills
Build and configure a GraphQL API backed by Neo4j using @neo4j/graphql v7 (current) or v5 (LTS). Covers Neo4jGraphQL constructor, getSchema(), assertIndexesAndConstraints(), type definitions with @node, @relationship (IN/OUT/UNDIRECTED), @cypher for custom resolvers, @authorization/@authentication for JWT/JWKS security, auto-generated queries/mutations, OGM programmatic access, subscriptions via CDC, and Apollo Federation. Use when writing typeDefs, securing fields, or wiring Neo4j to Apollo Server. Does NOT handle raw Cypher outside resolvers — use neo4j-cypher-skill. Does NOT cover Spring Data Neo4j entity mapping — use neo4j-spring-data-skill.
Design backend services, APIs, and server-side boundaries. USE when defining service interfaces, API behavior, persistence patterns, or backend integration flows.
Build reliable data pipelines and analytics-ready datasets. USE when cleaning data, designing ETL/ELT, defining contracts, or shipping reproducible data workflows.
Signal-based outbound specialist who designs multi-channel prospecting sequences, defines ICPs, and builds pipeline through research-driven personalization — not volume.
This skill should be used when configuring Make module parameters, assigning connections, mapping data between modules, setting up webhooks or data stores in modules, working with IML expressions, handling keys, or defining data structures for module inputs/outputs. Covers the practical HOW of module configuration — complementary to make-scenario-building which covers WHICH modules to use and WHY.
Use when the user wants to create or update a DDD-style ubiquitous language glossary, define domain terms, resolve ambiguous terminology, harden naming, or write UBIQUITOUS_LANGUAGE.md from the current conversation and codebase context.
Use this skill when you need to create or modify a LookML Model file (.model.lkml). This includes defining connections, includes, and configuring model-level settings.
Use this skill when you need to create or modify a LookML Explore. This includes defining the Explore, joins, access grants, and basic configuration.
Run the SPARC Specification phase — gather requirements, define acceptance criteria, identify constraints, and store the spec in memory
Start a repo-local OptimizeSpec self-improvement change. Use when the user wants to create evals, optimize an agent with GEPA, define an agent self-improvement loop, or begin an ASI-first evaluation workflow.
Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.
Expert product management guidance for day-to-day PM work. Use when creating roadmaps, prioritizing features, managing stakeholders, planning sprints, grooming backlogs, scoping features, planning releases, defining OKRs, managing technical debt, or coordinating go-to-market. Covers RICE, ICE, MoSCoW frameworks, cross-functional collaboration, and product metrics.