Skills publicadas
Mostrando 12 de 187api-documentation-generator
Generate comprehensive API documentation from repository sources including OpenAPI specs, code comments, docstrings, and existing documentation. Use when documenting APIs, creating API reference guides, or summarizing API functionality from codebases. Extracts endpoint details, request/response schemas, authentication methods, and generates code examples. Triggers when users ask to document APIs,
template-code-generator
Generate boilerplate code and project templates/skeletons automatically. Use when: (1) Creating new projects from scratch (React app, FastAPI backend, Express API), (2) Generating repetitive code patterns (CRUD endpoints, models, controllers), (3) Scaffolding components, services, or modules, (4) Creating test boilerplate, (5) Setting up monorepo structures. Provides project templates and code gen
static-bug-detector
Analyze source code statically to detect potential functional bugs including null dereferences, incorrect condition checks, unreachable code, inconsistent state updates, logic errors, resource leaks, and type mismatches. Report suspicious code locations with detailed explanations, severity levels, and confidence assessments. Use when reviewing code for bugs, performing code audits, or when the use
release-change-analyzer
Compares HEAD with the latest published version to analyze real changes, group by type, and recommend version bumps. Use before publishing a release to understand what actually changed.
imperative-to-coq-model-extractor
Extract abstract mathematical models from imperative code (C, C++, Python, Java, etc.) suitable for formal reasoning in Coq. Use when the user asks to model imperative code in Coq, create Coq specifications from imperative programs, extract mathematical models for verification, or translate imperative algorithms to Coq for formal reasoning and proof.
scenario-generator
Generate comprehensive test scenarios, user stories, and acceptance criteria from requirements and specifications. Use this skill when planning testing efforts, writing user stories, creating test cases, documenting acceptance criteria, exploring edge cases, designing test coverage, or translating requirements into actionable scenarios. Supports BDD (Given-When-Then), Gherkin syntax, user story fo
refinement-step-generator
Generate systematic refinement steps from high-level specifications to concrete implementations in Isabelle/HOL or Coq, preserving correctness obligations at each step. Use when working with formal verification, program refinement, proof development, or when translating abstract specifications into executable code while maintaining formal guarantees. Supports data refinement (abstract types → conc
requirement-enhancer
Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification. Use when: (1) Users provide initial requirements that need refinement, (2) Requirements are vague, incomplete, or ambiguous, (3) Creating formal specifications from informal descriptions, (4) Identifying missing constraints, edge cases, or acceptance criteria, (5) Clarifying as
build-ci-migration-assistant
Automatically migrates build systems and CI/CD configurations to target platforms. Use when modernizing build infrastructure, switching CI/CD providers, or standardizing across projects. Supports common migration paths including Maven↔Gradle, npm↔Yarn, Travis CI→GitHub Actions, CircleCI→GitHub Actions, Jenkins→GitLab CI, and GitLab CI→GitHub Actions. Analyzes existing configuration, generates equi
code-optimizer
Analyzes and optimizes code for better performance, memory usage, and efficiency. Use when code is slow, memory-intensive, or inefficient. Supports Python and Java optimization including execution speed improvements, memory reduction, database query optimization, and I/O efficiency. Provides before/after examples with detailed explanations of why optimizations work, complexity analysis, and measur
python-api-consistency-validator
Validate API consistency between two versions of Python libraries. Use when you need to compare API behavior, signatures, and exceptions between library versions to identify breaking changes, incompatible modifications, and behavior differences. The skill performs static analysis of Python code, compares function signatures, class definitions, parameter types, return types, and generates a detaile
agent-browser
CLI-based browser automation with persistent page state using ref-based element interaction. Use when users ask to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.