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Analyzes project structure, module dependencies, imports, and entry points to generate architecture diagrams in Mermaid format

Analyzes ETL and data pipeline code for optimization opportunities across Python (Pandas, PySpark), Rust (polars, datafusion), SQL, and general pipeline descriptions

Validates environment variable configurations and config files (YAML, TOML, JSON, .env) for missing required variables, type mismatches, deprecated keys, naming convention violations, secret exposure risks, and invalid value ranges

Analyzes code for performance bottlenecks including N+1 queries, O(n^2) or worse algorithms, unnecessary allocations, sync I/O in async contexts, excessive cloning, missing caching opportunities, and large payload transfers. Supports Rust, Python, TypeScript, and Go.

Analyzes, improves, and restructures LLM prompts for clarity, efficiency, and reliability

Analyzes source code for common security vulnerabilities including SQL injection, XSS, command injection, hardcoded secrets, insecure deserialization, path traversal, and SSRF

Agent reviews its own work before presenting to the user. Catches errors, style violations, and omissions before the user sees the output.

Analyzes multi-step workflows and agent pipelines for bottlenecks, unnecessary serialization, and optimization opportunities

Summarize long conversations or task histories to fit within token windows. Enables the agent to maintain context across sessions without hitting token limits.

Record architectural and design trade-off decisions so the agent doesn't re-analyze the same choices. Especially useful for long-running projects.

Analyze build, test, and runtime failures and propose structured recovery plans. Use when the agent encounters errors it cannot immediately resolve.

Persist completed and blocked steps across multi-turn agent invocations. Avoid re-analyzing already-resolved subtasks. Use when a task spans multiple agent turns.

Tests API endpoints with configurable requests, assertions, and response validation

Safely executes code snippets in a sandboxed environment with timeout, resource limits, and output capture

Analyzes full project structure, dependencies, architecture patterns, and generates comprehensive reports

Automated code review with customizable quality rules

Generates structured API documentation from source code, including endpoints, types, and examples

Generates structured changelogs from git commit history or structured input

Generates CI/CD pipeline configurations for GitHub Actions, GitLab CI, Jenkins, and CircleCI

Generates Conventional Commits-style commit messages from git diffs or change descriptions

Converts data between structured formats (JSON, CSV, YAML, TOML, XML) with schema mapping and validation

Analyzes project dependencies for security vulnerabilities, version drift, licensing, and upgrade paths

Generates optimized Dockerfiles and Docker Compose configurations for any language or framework

Analyzes application and system logs to detect anomalies, patterns, errors, and performance issues

Analyzes source code for refactoring opportunities, design smells, and improvement suggestions

Builds, explains, and tests regular expressions with step-by-step breakdowns

Guides users through creating, testing, and publishing new skills with proper SKILL.md format and best practices

Generates, explains, optimizes, and migrates SQL queries across multiple database dialects

Generates unit, integration, and property-based tests for source code in multiple languages

Extracts, cleans, and structures content from web pages by URL or HTML input

Retrieves relevant knowledge from project documentation, code comments, and README files

Breaks down complex objectives into atomic subtasks, identifies dependencies, and produces an execution plan