Browse published AI skills maintained by d-o-hub. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
52Repository stars across indexed skills
193Repository forks
0Average repository stars per indexed skill
4Repository stars may repeat across skills from the same repository.
Execute and troubleshoot memory-cli commands for episode management, pattern analysis, and storage operations. Use this skill when running CLI commands, debugging CLI issues, explaining command usage, or guidin...
Analyze gaps between implementation plans and actual codebase implementation for the Rust self-learning memory project
Log execution steps during episode execution for detailed tracking and learning. Use when recording tool usage, decision points, errors, or milestones during task execution.
General-purpose agent for researching complex questions, searching for code, and executing multi-step tasks. Use when you need to perform comprehensive searches across codebase, find files that are not obvious...
Diagnose, fix, and optimize GitHub Actions workflows for Rust projects. Use when setting up CI/CD, troubleshooting workflow failures, optimizing build times with caching, or ensuring best practices for testing,...
Complex research requiring deeper analysis, multi-step reasoning, and sophisticated source evaluation for technical, academic, or specialized domain queries needing expert-level analysis, high-stakes decisions,...
STRICT GitHub release gatekeeper. Blocks premature releases (from develop, incomplete CI). Verifies PR merged to main + ALL CI passed before allowing tag/release. Triggers on "release", "tag", "publish", "deplo...
Break down complex tasks into atomic, actionable goals with clear dependencies and success criteria. Use when planning multi-step projects, coordinating agents, or decomposing complex requests.
Systematic approach to diagnosing and fixing failing tests in Rust projects. Use when tests fail and you need to diagnose root causes, fix async/await issues, handle race conditions, or resolve database connect...
Comprehensive async/tokio testing patterns for episodic memory operations. Use when writing tests for async functions, time-based operations, concurrent tasks, or tokio runtime management.
Synchronize memories between Turso (durable) and redb (cache) storage layers. Use when cache appears stale, after failures, or during periodic maintenance.
Maintain high code quality through formatting, linting, and static analysis using rustfmt, clippy, and cargo audit. Use to ensure consistent code style and catch common mistakes.
Systematic approach to implementing new features in the Rust memory system following project conventions. Use when adding new functionality with proper testing and documentation.
Complete and score a learning episode to extract patterns and update heuristics. Use when finalizing a task to enable pattern extraction and future learning.
Retrieve relevant episodic context from memory for informed decision-making. Use when you need past episodes, patterns, or solutions to similar tasks.
Find and document file locations in the codebase. Use this when you need to locate implementation files, tests, configurations, or any code artifacts by feature or topic. Works with Grep, Glob, and LS tools.
Advanced test optimization with cargo-nextest, property testing, and performance benchmarking. Use when optimizing test execution speed, implementing property-based tests, or analyzing test performance.
Domain-specific testing patterns for episodic memory operations. Use when testing episode lifecycle, pattern extraction, reward scoring, or memory retrieval.
Diagnose, fix, and optimize GitHub Actions workflows for Rust projects. Use when setting up CI/CD, troubleshooting workflow failures, optimizing build times, or ensuring best practices.
Maintain high code quality through formatting, linting, and static analysis. Use to ensure consistent code style, catch common mistakes, and verify adherence to coding standards.
Perform comprehensive Rust code quality reviews against best practices for async Rust, error handling, testing, and project structure
Coordinate multiple specialized Skills and Task Agents through parallel, sequential, swarm, hybrid, or iterative execution strategies. CRITICAL - Skills use Skill tool (rust-code-quality, architecture-validatio...
Systematic debugging approach for Rust async code with Tokio, Turso, and redb. Use when diagnosing runtime issues, performance problems, async deadlocks, database connection issues, or panics.
Execute iterative refinement workflows with validation loops until quality criteria are met. Use for test-fix cycles, code quality improvement, performance optimization, or any task requiring repeated action-va...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.