using-git-worktrees
Use this whenever you need to create an isolated workspace.
Discover DevOps skills, compare source repositories and read the instructions for each workflow.
Use this whenever you need to create an isolated workspace.
Use when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure fir...
Use when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with exact file paths, complete code examples, and ve...
Write or update documentation in the server-side noridocs system.
Use this when you have finished making code changes and you are ready to update the documentation based on those changes.
Use this skill to split large plans into smaller chunks. This skill manages your context window for large tasks. Use it when a task will take a long time and cause context issues.
Use when writing or changing tests, adding mocks, or tempted to add test-only methods to production code - prevents testing mock behavior, production pollution with test-only methods, and mocking without unders...
List all server-side noridocs, optionally filtered by repository and/or path prefix.
Read documentation from the server-side noridocs system by file path.
Search the Nori knowledge base for relevant context, solutions, and documentation.
This skill should be used when the user asks to 'assess my knowledge state', 'run preflight', 'do a postflight', 'use CASCADE workflow', 'track what I know', 'measure learning', 'check epistemic drift', 'spawn...
Interactive documentation guide - helps users explore and understand project documentation. Use when user asks about features, APIs, configuration, or wants to learn how something works. Retrieves focused docs...
Meta-cognitive skill for improving Empirica using Empirica's own framework
Empirica epistemic workflow - creates goals, submits findings/unknowns, manages sessions, runs CASCADE phases (PREFLIGHT/CHECK/POSTFLIGHT). Use when working with epistemic assessments, goals, findings, or sessi...
Competence in data analytics and machine learning, enabling developers to build data-driven features and integrate AI/ML capabilities.
Communicating the intended behavior and context of code through clear documentation and comments, and sharing knowledge with the team.
The practice of restructuring and simplifying code continuously – reducing complexity, improving design, and keeping codebases clean.
Skill in automating software deployment pipelines and managing cloud infrastructure for scalable, reliable systems.
Working effectively with others in coding projects – including code reviews, clear communication, and contributing to shared or open-source codebases.
Leveraging AI coding assistants and tools to boost development productivity, while maintaining oversight to ensure quality results.
Ensuring software correctness and reliability by writing automated tests, using quality assurance tools, and systematically debugging issues.
Writing clean, understandable, and self-documenting code that is easy to review and maintain over time.
Ability to develop both front-end and back-end systems, integrating user interfaces with server logic and databases.
Incorporating security at every step of software development – writing code that defends against vulnerabilities and protects user data.
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.