Explore our collection of Agent Skills to enhance your AI workflow.
Automatically identifies and resolves TypeScript and build errors through an iterative, self-verifying debug-and-fix cycle.
Synchronizes project documentation automatically using source-of-truth files like package.json and environment configurations.
Extracts and codifies reusable coding patterns, error resolutions, and project-specific conventions from active AI sessions.
Automates the generation and maintenance of high-level architecture documentation by analyzing codebase structure and dependencies.
Streamlines complex development tasks through sequential, multi-agent automated workflows.
Optimizes context management by suggesting manual compaction at logical task boundaries instead of arbitrary intervals.
Safely removes unused code, exports, and dependencies through automated analysis and rigorous test-driven verification.
Implements scalable backend architectures, RESTful API designs, and database optimization patterns for Node.js and Next.js environments.
Enforces test-driven development practices with comprehensive unit, integration, and E2E test coverage.
Performs systematic qualitative thematic analysis on document collections to extract deep structural insights and categorized themes.
Automates a multi-stage quality gate system to validate builds, types, linting, tests, and security before PR submission.
Analyzes local git history to extract repository-specific coding patterns and automatically generate SKILL.md files for Claude.
Implements an eval-driven development framework to systematically validate features and track regressions using pass@k metrics.
Bootstraps reproducible, high-performance Python development environments using Nix, uv, and Ruff.
Initializes a professional Quarto environment for survey data analysis using Python, uv, and Typst PDF pipelines.
Discovers and installs specialized agent capabilities from the open skills ecosystem to extend Claude's functionality.
Automates the generation of professional Quarto PDF reports and PowerPoint presentations from CSV survey data.
Analyzes codebase test coverage reports to automatically generate missing unit, integration, and end-to-end tests.
Implements a multi-phase loop to progressively refine code context retrieval for more accurate AI agent performance.
Optimizes content for traditional search engines and AI-powered answer engines using EEAT principles and structured data.
Facilitates interactive Behavior-Driven Development sessions to explore system requirements, define business rules, and generate structured Gherkin feature files.
Drafts comprehensive Oversight Board case decisions using IRAC analysis, precedent mapping, and rigorous citation verification.
Provides a comprehensive end-to-end framework for project planning and technical execution through structured templates and automated AI workflows.
Orchestrates end-to-end project success through a structured 14-section planning framework and 9 integrated technical execution skills.
Provides skeptical, second-opinion reviews of implementation plans and conclusions to identify logical flaws and untested assumptions.
Automates comprehensive framework governance through structure verification, index synchronization, and automated acceptance testing.
Automates the creation of standardized git checkpoint commits when significant development milestones are reached.
Audits Pegasus scientific workflows to identify configuration errors, optimize resource usage, and ensure best practices for distributed execution.
Streamlines inbox management with automated classification, mandatory archive logging, and integrated task creation.
Executes pre-assigned tasks autonomously using injected context, scope boundaries, and defined success criteria.
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