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Found 1,631 Skills
Technical research methodology with YAGNI/KISS/DRY principles. Phases: scope definition, information gathering, analysis, synthesis, recommendation. Capabilities: technology evaluation, architecture analysis, best practices research, trade-off assessment, solution design. Actions: research, analyze, evaluate, compare, recommend technical solutions. Keywords: research, technology evaluation, best practices, architecture analysis, trade-offs, scalability, security, maintainability, YAGNI, KISS, DRY, technical analysis, solution design, competitive analysis, feasibility study. Use when: researching technologies, evaluating architectures, analyzing best practices, comparing solutions, assessing technical trade-offs, planning scalable/secure systems.
Type-driven design principle: transform unstructured data into structured types at system boundaries, making illegal states unrepresentable. Use when writing or reviewing code that validates input, designs data types, defines function signatures, handles errors, or models domain logic. Use when you see validation functions that return void/undefined, redundant null checks, stringly-typed data, boolean flags controlling behavior, or functions that can receive data they shouldn't. Triggers on: "parse don't validate", "type-driven design", "make illegal states unrepresentable", "input validation", "data modeling", "refactor types", "strengthen types", "smart constructor", "newtype", "branded type".
Synthesize structured directives and command specifications. Creates executable instruction sets with proper syntax and parameter definitions.
When the user wants to define, audit, or apply brand strategy—purpose, values, positioning, storytelling, voice, visual identity. Also use when the user mentions "brand strategy," "brand story," "brand storytelling," "brand voice," "brand identity," "brand guidelines," "brand purpose," "brand values," "origin story," "brand narrative," "brand personality," or "brand archetype."
GraphQL API design. Covers schema, queries, mutations, and resolvers. Use when building or consuming GraphQL APIs. USE WHEN: user mentions "GraphQL", "schema definition", "resolvers", "mutations", "queries", "DataLoader", "N+1 problem", asks about "how to design GraphQL API", "GraphQL schema", "GraphQL authentication", "GraphQL pagination", "Apollo Server" DO NOT USE FOR: REST APIs - use `rest-api` instead; tRPC - use `trpc` instead; GraphQL code generation - use `graphql-codegen` instead
Universal generation template for OpenHarmony XTS test cases. Supports test case generation for various subsystems, API definition parsing, test coverage analysis, and code specification checking. Trigger keywords: XTS, test generation, case generation, test case.
Define and organize design tokens (color, spacing, typography, elevation) with naming conventions and usage guidance.
Specify micro-interactions with trigger, rules, feedback, and loop/mode definitions.
Diagnose and fix broken Goldsky Turbo pipelines interactively. Use whenever the user has a specific pipeline that is misbehaving — error state, stuck in 'starting', connection refused, slow backfill, not getting data in postgres/clickhouse, duplicate rows, missing fields, named pipeline failing ('my base-usdc-transfers keeps failing'), or any symptom where something is wrong with a deployed pipeline. Runs goldsky turbo logs and status commands, identifies root cause, and offers to run fixes. For looking up CLI syntax or error message definitions WITHOUT an active problem, use /turbo-monitor-debug instead.
Manages the end-to-end cyber threat intelligence lifecycle from planning and direction through collection, processing, analysis, dissemination, and feedback to ensure intelligence products meet stakeholder requirements and continuously improve. Use when establishing or maturing a CTI program, defining intelligence requirements with business stakeholders, or building feedback loops between intelligence consumers and producers. Activates for requests involving CTI program maturity, intelligence requirements, PIRs, or intelligence lifecycle management.
Define version control strategies for design files, components, and libraries.
Use this skill when implementing SRE practices, defining error budgets, reducing toil, planning capacity, or improving service reliability. Triggers on SRE, error budgets, SLOs, SLAs, toil automation, incident management, postmortems, on-call rotation, capacity planning, chaos engineering, and any task requiring reliability engineering decisions.