Explore our collection of Agent Skills to enhance your AI workflow.
Configures secure, encrypted environment variable management optimized for Git worktrees and parallel development workflows.
Equips Claude with visual browser access to debug, automate, and audit web applications in real-time.
Simplifies the process of editing, querying, and managing OBO format ontologies through specialized scripts and standardized curation workflows.
Automates local web application testing and UI verification using Playwright scripts and managed server lifecycles.
Generates structured, conventional commit messages by analyzing staged git changes to maintain a professional project history.
Generates precise Home Assistant YAML configurations, automations, and blueprints while enforcing strict intent clarification to ensure accuracy.
Generates actionable remediation steps and code examples by analyzing error patterns and failure logs.
Monitors project completion rates and identifies development blockers using GitHub issue data to ensure timely software delivery.
Automates the test-driven development lifecycle by generating standardized Mojo and Python test suites and enforcing the Red-Green-Refactor pattern.
Executes Mojo test suites with advanced filtering and reporting to ensure code correctness in high-performance AI frameworks.
Generates and analyzes comprehensive test coverage reports to identify untested code paths and ensure software reliability.
Validates and formats code using pre-commit hooks to ensure high quality and consistency before committing to a repository.
Verifies agent hierarchies, delegation chains, and escalation paths to ensure stable multi-agent system orchestration.
Streamlines GitHub project management using native sub-issue hierarchies, label-driven status tracking, and optional Project v2 visualizations.
Creates GitHub pull requests that are automatically linked to specific issues for streamlined project tracking and automation.
Validates memory safety, ownership transfers, and borrowing rules within Mojo code to prevent segmentation faults and data corruption.
Automates replies to inline GitHub pull request review comments using the correct GitHub API endpoints.
Diagnoses and resolves CI/CD pipeline failures by analyzing logs, reproducing errors locally, and applying systematic fixes.
Ensures code quality and style consistency by running automated linting tools across Python and Mojo source files.
Optimizes Mojo tensor and array operations by implementing parallel computation through SIMD vectorization patterns.
Generates and manages Architecture Decision Records (ADRs) to document significant technical choices and their rationale.
Automates local Mojo builds and environment setup to ensure parity with CI pipelines.
Standardizes project documentation by generating comprehensive, 9-section plan files to guide development workflows.
Optimizes parallel development by enabling rapid switching between isolated Git worktrees without stashing or branch jumping.
Manages the full quality assurance lifecycle from test planning and bug reproduction to regression analysis and quality reporting.
Generates professional technical documentation, API references, and user guides tailored for both developers and business stakeholders.
Generates comprehensive, production-ready unit tests across multiple programming languages and frameworks automatically.
Automates comprehensive pull request reviews using a multi-agent system to analyze security, performance, architecture, and code quality.
Automates code quality checks and testing workflows by configuring standardized Git hooks for any project environment.
Automates the modernization of legacy codebases by migrating frameworks, languages, and architectural patterns with integrated risk analysis and testing.
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