nia
Use Nia MCP server for external documentation, GitHub repos, package source code, and research. Invoke when needing to index/search remote codebases, fetch library docs, explore packages, or do web research.
Discover Testing & security skills, compare source repositories and read the instructions for each workflow.
Use Nia MCP server for external documentation, GitHub repos, package source code, and research. Invoke when needing to index/search remote codebases, fetch library docs, explore packages, or do web research.
Use when implementation complete and tests pass - closes bd epic, presents integration options (merge/PR/keep/discard), executes choice
Use when facing 3+ independent failures that can be investigated without shared state or dependencies - dispatches multiple Claude agents to investigate and fix independent problems concurrently
Use to expand bd tasks with detailed implementation steps - adds exact file paths, complete code, verification commands assuming zero context
Use when creating new skills, editing existing skills, or verifying skills work - applies TDD to documentation by testing with subagents before writing
Use when writing or changing tests, adding mocks - prevents testing mock behavior, production pollution with test-only methods, and mocking without understanding dependencies
Use when creating Claude Code hooks - covers hook patterns, composition, testing, progressive enhancement from simple to advanced
Use before claiming work complete, fixed, or passing - requires running verification commands and confirming output; evidence before assertions always
Use when encountering bugs or test failures - systematic debugging using debuggers, internet research, and agents to find root cause before fixing
Use when you have to refine subtasks into actionable plans ensuring that all corner cases are handled and we understand all the requirements.
Use when skills aren't activating reliably - covers official solutions (better descriptions) and custom hook system for deterministic skill activation
Use to audit test quality with Google Fellow SRE scrutiny - identifies tautological tests, coverage gaming, weak assertions, missing corner cases. Creates bd epic with tasks for improvements, then runs SRE task...
Use to execute bd tasks iteratively - executes one task, reviews learnings, creates/refines next task, then STOPS for user review before continuing
Use when encountering a bug - complete workflow from discovery through debugging, bd issue, test-driven fix, verification, and closure
Use when errors occur deep in execution - traces bugs backward through call stack to find original trigger, not just symptom
Use for advanced bd operations - splitting tasks mid-flight, merging duplicates, changing dependencies, archiving epics, querying metrics, cross-epic dependencies
Use when implementing features or fixing bugs - enforces RED-GREEN-REFACTOR cycle requiring tests to fail before writing code
Use when refactoring code - test-preserving transformations in small steps, running tests between each change
Use after hyperpowers:executing-plans completes all tasks - verifies implementation against bd spec, all success criteria met, anti-patterns avoided
Use when creating or developing anything, before writing code - refines rough ideas into bd epics with immutable requirements
Use when starting any conversation - establishes mandatory workflows for finding and using skills
Recommend architecture patterns (monolith, microservices, serverless, modular monolith) based on scale, team size, and constraints. Use when cto-architect needs to select the right architectural approach for a...
Transform clarified user requests into structured delegation prompts optimized for specialist agents (cto-architect, strategic-cto-mentor, cv-ml-architect). Use after clarification is complete, before routing t...
Generate phased implementation roadmaps with Epic/Story/Task breakdown, effort estimates, and validation checkpoints. Use when cto-architect needs to create actionable technical roadmaps from architecture desig...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.