Inspect a skill package before installation
Review skill metadata, referenced files, and executable or external-action behavior without running it.
Browse reusable instructions for your AI tools. Copy and customize a prompt, or download a skill for a supported agent.

Review skill metadata, referenced files, and executable or external-action behavior without running it.
Review code changes for real bugs, edge cases, and actionable improvements.
Organize an OpenClaw workspace around clear, reusable instructions and discoverable skills.
Diagnose why an OpenClaw skill is missing, overridden, or not being discovered.
Map a repository for Codex before starting a substantial change.
Give Claude Code a focused review workflow for an existing diff.
Get a focused review of correctness, maintainability, and edge cases, grounded in your code.
Map a product workflow into predictable endpoints, validation rules, and error responses.
Build a useful map of a repository and identify where a specific change belongs.
Investigate failures with evidence, ranked hypotheses, and a minimal regression-tested fix.
Plan a migration with compatibility checks, verification, and a recovery path.
Specify a coding task with repository context, acceptance criteria, and a verifiable finish line.
Give ChatGPT useful background, a specific goal, and an output format in one tidy prompt.
Preserve the coding agent's explicit AAS skill selection as a validated stack and optional evidence.
Discover AAS skills for an explicit task and compare their complete instructions without installing them.
Review AAS stack manifests, preview plans and selection evidence in Workbench without applying changes.
Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
Use when you need to address review or issue comments on an open GitHub Pull Request using the gh CLI.
Create custom AI subagents with proper plugin structure, persona generation, and companion routing skills.
Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) in an explicitly authorized workspace.
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
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Explore all resourcesResource formats: Prompts are ready to copy into a conversation. Skills install into the compatible agent shown on their page.
How it worksInclude the instructions, intended platforms, author, and license. Submissions are reviewed before publication.