This repository is a comprehensive, reusable, task-oriented Skills collection designed to support software engineering activities across the entire development lifecycle, including:
Requirement understanding, system design, implementation, testing, verification, deployment, and maintenance.
We provide:
- 🌐 Website to quick browse skills
- 📦 8 Core Skill Packs
- 🚀 180+ Coding Skills
🌐 Skills Manager Web Interface
You can also deploy the website locally. 👉 Guideline
Browse, search, and install skills through our interactive web interface. The Skills Manager provides:
- 📦 One-click installation of all skills
- ✅ Selective installation of specific skills
- 🔍 Search and filter by category
- 📖 Bilingual help documentation (English/中文)
- 🎨 Modern, responsive interface
📦 Skill Packs
Organized collections of related skills for common software engineering workflows. Instead of installing skills individually, you can install curated skill packs that bundle related capabilities together.
🚀 Available Skill Packs (8 Total)
- 🐛 Bug Fixing Suite - 12 skills for bug detection, localization, and automated repair
- ✨ Code Quality Toolkit - 13 skills for code quality, refactoring, and technical debt management
- 🧪 Test Automation Suite - 18 skills for comprehensive test generation and optimization
- 📋 Requirements Engineering Suite - 12 skills for requirements analysis, formalization, and traceability
- 🔄 Code Understanding and Manipulation Suite - 19 skills for code understanding, analysis, search, translation, and manipulation
- 🚀 DevOps Automation Toolkit - 10 skills for CI/CD pipelines, containerization, and deployment
- 🔍 Formal Verification Toolkit - 17 skills for formal verification of software systems
- 🔒 Security Scanner Suite - 13 skills for comprehensive security analysis
Quick Installation
# Install a single pack
cd skill-packs/formal-verification-toolkit
./install.sh
# Install multiple packs
cd skill-packs
./install-packs.sh formal-verification-toolkit security-scanner-suite
# Install all packs
cd skill-packs
./install-all-packs.sh
👉 Learn more about Skill Packs
✨ Why Skills (not just prompts)?
Modern LLMs are powerful, but raw prompting is fragile:
- Hard to reproduce
- Hard to evaluate
- Hard to integrate into real workflows
We treat Skills as first-class engineering artifacts, in preparation for the future metaprogramming.
A Skill in this repo is more than a prompt:
- It encodes procedural knowledge
- It specifies expected inputs / outputs
- It documents failure modes
- It can be evaluated, composed, and reused
🤗 Think of this repo as a standard library of software engineering capabilities for LLM-powered systems.
List of Skills
- Skills by Category
- ⌨️ Code Generation
- 👩🏽💻 Testing
- ⚖️ Code Quality & Analysis
- 📕 Documentation
- 💡 Architecture & Design
- 📗 Requirements & Specifications
- 💻 DevOps & Deployment
- 🔀 Version Control & Collaboration
- 📋 Project Management & Issue Tracking
- 💬 Team Communication
- 📊 Monitoring & Error Tracking
- 🗄️ Database & Backend Services
- 🛠️ Development Tools & Builders
- 🔗 Integration & Webhooks
- 🔨 Debugging & Error Handling
- ✅ Formal Methods & Verification
- 🔧 Maintenance & Refactoring
- 🎨 UI/UX Design
- 👀 Visualization
- Skills by Stages
- 📕 Requirement Analysis
- 💡Software Design
- ⌨️ Implementation
- 👩🏽💻 Testing
- ✅ Verification
- 💻 Deployment
- 🔧 Maintenance
- 📖 Usage
- 🫶 Contributing
- 🎯 Vision
- 🙏 Reference
Skills by Category
Code Generation
- Generates functions and classes from specifications
- Supports multiple programming languages
- Includes type hints, documentation, and error handling
- Builds complete modules from interface contracts
- Generates layered architectures (model, repository, service)
- Supports Python and Java with design patterns
- Creates boilerplate code from templates
- Supports common patterns and frameworks
- Customizable templates for different use cases
Specification-Driven Generation
- Generates code from formal specifications
- Ensures specification compliance
- Validates generated code against requirements
- Generates implementation from test cases
- Follows TDD principles
- Ensures test coverage
- Implements new features in Python repositories from natural language descriptions
- Generates comprehensive unit and integration tests
- Ensures all tests pass and follows existing code patterns
- Implements new features in Java repositories from natural language descriptions
- Supports Maven and Gradle build systems
- Generates JUnit tests and ensures all tests pass successfully
- Extracts programming-language-agnostic pseudocode from source code
- Preserves control flow and logical structure
- Filters out implementation details for clarity
- Translates source code between programming languages at module level
- Preserves behavior and adapts to target language idioms
- Generates verification tests for translated code
- Converts pseudocode descriptions into complete, executable Java programs
- Preserves original logic and control flow
- Applies appropriate Java idioms and best practices
- Converts pseudocode and algorithm descriptions into executable Python code
- Provides proper structure, documentation, and tests
- Maintains algorithmic logic while following Python conventions
Testing
- Generates unit tests for functions and classes
- Supports multiple testing frameworks
- Includes edge cases and assertions
- Creates integration tests for system components
- Tests component interactions
- Includes setup and teardown logic
- Updates Java tests to work with new code versions after refactoring
- Handles signature changes, refactoring, and behavior modifications
- Updates method calls, assertions, mocks, and ensures tests pass
- Identifies non-deterministic tests
- Analyzes test execution patterns
- Suggests fixes for common flaky patterns
- Generates expected outputs for test cases
- Creates assertions and validation logic
- Supports property-based testing
- Identifies and generates edge case tests
- Covers boundary conditions
- Includes corner cases and error scenarios
- Generates targeted test inputs
- Focuses on specific code paths
- Uses symbolic execution techniques
- Creates randomized test inputs
- Discovers unexpected behaviors
- Supports mutation-based fuzzing
- Prioritizes test execution order
- Optimizes for early failure detection
- Considers test dependencies and coverage
- Identifies uncovered code paths
- Generates tests to improve coverage
- Reports coverage metrics
- Documents test cases and their purposes
- Explains test scenarios and expected outcomes
- Maintains test documentation
- Updates Python tests to work with new code versions
- Fixes broken tests due to signature and behavior changes
- Analyzes code diffs and updates assertions accordingly
Bug Reproduction Test Generator
- Automatically generates tests that reproduce reported bugs from issue reports
- Analyzes bug symptoms, stack traces, and triggering conditions
- Creates minimal, focused tests that reliably trigger the bug
- Supports Python, Java, and JavaScript test frameworks
Interval-Guided Regression Test Update
- Updates regression tests based on interval analysis
- Converts requirements to test cases
- Ensures requirement coverage
- Traces tests back to requirements
- Reduces test cases to minimal form using delta debugging
Java Regression Test Generator
- Automatically generates regression tests for Java codebases
- Analyzes changes between old and new code versions
- Ensures tests cover refactored or modified functionality
Python Regression Test Generator
- Automatically generates regression tests for Python codebases
- Analyzes changes between code versions and migrates existing tests
- Generates tests for new functionality
- Generates unit tests with proper mocking for Python and Java
- Supports unittest.mock/pytest for Python and Mockito/JUnit for Java
- Handles external dependencies and complex interactions
- Analyzes failing tests to detect functional bugs in code
- Examines execution behavior, assertions, and stack traces
- Identifies suspicious code regions causing test failures
- Systematically analyzes surviving mutants from mutation testing
- Identifies test suite weaknesses and generates improvements
- Categorizes why mutants survived and suggests test enhancements
Metamorphic Property Extractor
- Automatically identifies metamorphic properties from programs
- Enables metamorphic testing without explicit test oracles
- Discovers input-output relationships for test generation
- Generates test cases using metamorphic testing principles
- Applies transformations based on metamorphic properties
- Expands test suites and detects bugs through input-output relationships
Counterexample to Test Generator
- Converts formal verification counterexamples into executable test cases
- Transforms model checker outputs into unit or integration tests
- Bridges formal verification and testing workflows
- Optimizes test suites using mutation testing analysis
- Selects minimal subset of tests maximizing mutation kill rate
- Reduces execution time and eliminates redundancy
- Analyzes test suites to identify redundant or duplicate tests
- Examines code coverage, semantic similarity, and execution behavior
- Groups equivalent tests and explains deduplication rationale
Java API Consistency Validator
- Validates API consistency between two versions of Java libraries
- Compares signatures, behavior, and exceptions
- Identifies breaking changes and incompatible modifications
Python API Consistency Validator
- Validates API consistency between two versions of Python libraries
- Compares signatures, behavior, and exceptions
- Identifies breaking changes and provides migration guidance
Code Quality & Analysis
- Performs automated code reviews
- Identifies issues and suggests improvements
- Checks coding standards compliance
- Detects code smells and anti-patterns
- Suggests refactoring opportunities
- Categorizes smells by severity
- Identifies architectural and design issues
- Detects violations of design principles
- Suggests design improvements
- Optimizes code for performance
- Identifies bottlenecks
- Suggests algorithmic improvements
- Identifies unused code
- Safely removes dead code
- Reports elimination opportunities
- Identifies technical debt
- Quantifies debt impact
- Prioritizes debt reduction
- Analyzes codebases to identify reusable code patterns and duplications
- Generates pattern catalogs with refactoring suggestions
- Creates reusable template code for high-value patterns
- Searches repositories for code related to given snippets
- Ranks results by call chain, textual, and functional similarity
- Outputs ranked file lists with matching code snippets
- Identifies module/component boundaries
- Detects boundary violations
- Analyzes architectural separation
- Generates concise summaries of source code at multiple scales
- Explains code functionality from functions to entire codebases
- Helps understand complex code structures quickly
- Analyzes source code statically to detect potential functional bugs
- Identifies null dereferences, incorrect conditions, unreachable code
- Detects logic errors, resource leaks, and inconsistent state updates
- Statically analyzes code to detect security vulnerabilities
- Identifies buffer overflows, injection risks, insecure deserialization
- Detects improper authentication and unsafe cryptographic usage
- Detects security vulnerabilities by matching known patterns
- Identifies insecure coding idioms and CVE-style patterns
- Explains why patterns are risky and conditions for exploitation
Vulnerability Root Cause Analyzer
- Analyzes vulnerable code to identify underlying root causes
- Identifies violated assumptions, incorrect invariants, missing validation
- Detects unsafe component interactions
- Assesses realistic exploitability of detected vulnerabilities
- Examines control flow, input sources, and sanitization logic
- Determines if vulnerabilities are practically exploitable
- Proposes secure remediation strategies for security vulnerabilities
- Addresses buffer overflows, injection risks, insecure deserialization
- Provides fixes for improper authentication and unsafe cryptographic usage
- Analyzes whether CVE vulnerabilities in dependencies are reachable from application code
- Performs static and dynamic reachability analysis
- Prioritizes CVE remediation based on actual exploitability
CVE Watchlist Action Recommendation Generator
- Generates actionable recommendations for CVEs in dependency watchlists
- Prioritizes CVEs based on severity, exploitability, and impact
- Suggests patching, mitigation, or monitoring strategies
Time-Aware Dependency CVE Scanner
- Scans dependencies for CVEs with temporal context awareness
- Tracks CVE disclosure timelines and patch availability
- Provides time-sensitive vulnerability management recommendations
- Detects semantic-level bugs by analyzing code behavior vs. intent
- Infers intended purpose from names, comments, and documentation
- Identifies mismatches between implementation and expected behavior
- Validates that migrated or refactored codebase preserves original behavior
- Compares runtime behavior, test results, and execution traces
- Identifies behavioral divergences between code versions
- Analyzes semantic equivalence between two code artifacts
- Compares control flow, data flow, and observable behavior
- Provides rigorous equivalence analysis for functions, classes, or modules
Multi-Version Behavior Comparator
- Compares behavior across multiple versions of programs
- Identifies functional changes, regressions, and behavioral divergences
- Guides safe upgrades and validation processes
Regression Consistency Checker
- Checks whether new version preserves behavior observed by tests on old version
- Validates behavioral consistency across versions
- Identifies unexpected behavioral changes
- Analyzes differences in program intervals (variable value ranges) between versions
- Detects behavioral changes and identifies potential bugs
- Guides testing efforts based on interval analysis
Interval Profiling Performance Analyzer
- Profiles programs to identify performance bottlenecks
- Generates optimization recommendations with visualizations
- Uses interval analysis for performance insights
Modular Code Enforcement (Inspired by oh-my-opencode)
- Enforces strict modular architecture with SRP and 200 LOC limits
- Bans catch-all files (utils.ts, helpers.ts) in favor of focused modules
- Detects and splits files with multiple responsibilities
Dead Code Removal (Inspired by oh-my-opencode)
- Systematic dead code removal with LSP-verified safety
- Parallel batch processing with conflict-free execution
- Atomic commits per batch with automatic rollback on failure
Documentation
- Generates API documentation
- Creates reference documentation
- Includes usage examples
- Generates inline code comments
- Explains complex logic
- Follows documentation standards
- Reorganizes markdown documents into well-structured format
- Fixes heading hierarchy and generates table of contents
- Standardizes formatting and improves readability
- Generates comprehensive, user-friendly README.md files
- Includes project introduction, prerequisites, and setup instructions
- Provides executable usage examples and repository structure overview
- Creates change logs from commits
- Categorizes changes by type
- Follows semantic versioning
- Generates structured pull request descriptions from code changes
- Documents breaking changes with migration guides
- Adds testing instructions and context enhancements
- Writes release notes
- Highlights new features and fixes
- Targets end users
- Summarizes legacy codebases
- Explains code functionality
- Aids in understanding old code
- Quickly analyzes Python repositories
- Identifies project type, entry points, and dependencies
- Generates setup and execution instructions
- Explains error messages
- Provides context and solutions
- Helps with debugging
Init Deep (Inspired by oh-my-opencode)
- Generates hierarchical AGENTS.md context files throughout a project tree
- Provides AI agents with directory-specific knowledge automatically
- Supports max-depth control and incremental generation
Session Handoff (Inspired by oh-my-opencode)
- Creates structured context summaries for cross-session continuation
- Captures completed work, remaining tasks, key files, and gotchas
- Enables seamless handoff between AI sessions or teammates
Architecture & Design
- Assists in API design
- Suggests RESTful patterns
- Validates API consistency
- Suggests appropriate design patterns
- Explains pattern applicability
- Provides implementation guidance
- Generates configuration files
- Supports multiple formats (YAML, JSON, XML)
- Validates configuration schemas
- Resolves dependency conflicts
- Suggests compatible versions
- Analyzes dependency trees
Requirements & Specifications
- Summarizes requirements documents
- Extracts key requirements
- Organizes by priority
- Checks requirement coverage
- Identifies gaps in implementation
- Traces requirements to code and test
Requirement Comparison Reporter
- Compares old and new requirement documents
- Maps requirement changes to code components
- Generates detailed modification plans in Markdown format
- Detects ambiguous requirements
- Highlights unclear specifications
- Suggests clarifications
- Generates usage scenarios
- Creates user stories
- Develops test scenarios
- Generates formal specifications
- Converts natural language to specs
- Validates specification completeness
Natural Language to Constraints
- Converts NL requirements to formal constraints
- Supports constraint languages
- Validates constraint consistency
Strategic Planner (Inspired by oh-my-opencode)
- Interview-based strategic planning for complex software tasks
- Conducts gap analysis to catch hidden intentions and ambiguities
- Generates detailed work plans with acceptance criteria and test strategy
DevOps & Deployment
- Migrates build systems and CI/CD configurations
- Creates CD pipeline configurations for automated deployment
- Supports AWS, GCP, and Azure cloud platforms
- Includes environment separation, approval gates, and rollback capabilities
- Generates CI pipeline configurations for automated building and testing
- Supports GitHub Actions with dependency caching and matrix testing
- Includes templates for Node.js, Python, Go, and Rust projects
- Detects configuration inconsistencies across environments
- Creates Dockerfiles and container configs
- Optimizes container images
- Supports multi-stage builds
- Generates environment setup scripts
- Manages dependencies and configurations
- Supports multiple platforms
- Suggests rollback strategies
- Plans deployment reversions
- Minimizes downtime
- Automates Docker Hub tasks via Rube MCP (Composio)
- Manages repositories, images, tags, and container registry
- Supports Docker Hub operations
Code Instrumentation Generator
- Automatically instruments source code to collect runtime information
- Preserves program semantics while adding instrumentation
- Supports various instrumentation strategies for debugging and analysis
Security-Sensitive Path Instrumenter
- Adds structured logging instrumentation to security-critical code paths
- Monitors authentication, authorization, input validation, and session management
- Enables runtime monitoring of security-relevant events
Taint Instrumentation Assistant
- Instruments code to track untrusted and sensitive data flow
- Detects security vulnerabilities through taint analysis
- Identifies potential injection points and data leaks
Critical Interval Security Checker
- Analyzes code to identify security-critical time intervals
- Detects timing vulnerabilities that could compromise security
- Identifies race conditions and time-of-check-time-of-use issues
Release Change Analyzer (Inspired by oh-my-opencode)
- Compares HEAD with latest published version to analyze real changes
- Groups changes by type (feat/fix/refactor) with actual diff descriptions
- Recommends version bump (major/minor/patch) with reasoning
Debugging & Error Handling
- Localizes bugs in code
- Analyzes stack traces and logs
- Suggests likely bug locations
- Generates patches for identified bugs
- Creates minimal fixes
- Includes test cases for fixes
- Analyzes merge conflicts
- Suggests conflict resolutions
- Explains conflicting changes
Failure-Oriented Instrumentation
- Selectively instruments code to capture runtime data for debugging
- Automates git bisect to find the first bad commit
Regression Root Cause Analyzer
- Analyzes regression failures
- Identifies root causes
- Suggests fixes
Replay-Oriented Instrumentation
- Records execution for deterministic replay debugging
- Explains runtime errors
- Provides debugging guidance
- Suggests fixes
- Automatically generates clear, actionable issue reports from failing tests
- Analyzes test failures to understand expected vs. actual behavior
- Identifies affected code components and suggests fixes
- Traces and summarizes the complete lifecycle of a bug across code versions
- Provides historical context for bug evolution
- Helps understand bug patterns and resolution strategies
- Instruments code to support efficient git bisect operations
- Produces deterministic pass/fail signals and concise runtime summaries
- Creates robust test scripts for bisect workflows
Reproduction Trace Instrumenter
- Instruments source code to capture detailed execution traces for bug reproduction
- Records function calls, variable values, control flow, and program state
- Generates replay scripts for deterministic bug reproduction
- Instruments programs to capture snapshots of key program states at runtime
- Includes variable values, memory state, call stacks, and execution context
- Saves snapshots in structured JSON format for analysis
- Collects, normalizes, and structures execution traces from instrumented programs
- Processes strace, ltrace, and custom trace formats
- Makes traces suitable for debugging, reproduction, or performance analysis
- Performs SZZ algorithm analysis to identify bug-introducing commits
- Traces modified lines back through version history
- Links bug fixes to their originating changes
- Extends traditional SZZ algorithm with semantic analysis
- Distinguishes actual bug-introducing changes from refactoring
- Provides more accurate identification of bug origins
Formal Methods & Verification
- Assists with ACSL annotations
- Generates function contracts
- Validates annotation correctness
- Synthesizes program assertions
- Generates invariants and pre/post-conditions
- Validates assertion correctness
- Infers loop and program invariants
- Uses static and dynamic analysis
- Validates inferred invariants
- Verifies code using static analysis
- Checks co
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