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Found 3,129 Skills
User-facing NemoClaw guidance for installing, configuring, operating, securing, monitoring, and troubleshooting NemoClaw sandboxes. Use when users ask about NemoClaw quickstarts, OpenClaw and OpenShell relationships, local inference, remote GPU deployment, sandbox lifecycle, network policy, security posture, agent skills, command reference, or issue triage instructions.
Build high-quality Agent Skills for Claude following official Anthropic best practices. Covers SKILL.md structure, frontmatter, description writing, progressive disclosure, testing, patterns, troubleshooting, and distribution across all surfaces (Claude.ai, Claude Code, API, Agent SDK). Use when creating new skills, reviewing skill quality, debugging skill triggering, structuring skill directories, writing skill descriptions, or improving existing skills. Triggers on "build a skill", "create a skill", "skill structure", "SKILL.md", "skill best practices", "skill not triggering", "skill quality".
Use when you need to discover existing skills from GitHub repositories.
Review and analyze a skill against best practices for length, intent scope, and trigger patterns
Create and contribute skills to the communal knowledge base. Use when creating new skills, updating existing skills, or contributing learnings back to the repository.
Creates, updates, and manages Agent Skills following the Claude Code style. Use this skill when the user wants to add a new capability, create a new skill, or modify an existing skill.
Guide for creating effective agent skills. Use PROACTIVELY when creating new skills or refactoring bloated ones. Teaches progressive disclosure, 200-line rule, and 3-tier loading system.
Design and refactor Agent Skills with concise, high-signal instructions and explicit trigger metadata. Use when creating a new skill, revising SKILL.md/README.md structure, or improving skill discoverability and portability.
Generate professional Agent Skills for Claude Code and other AI agents. Creates complete skill packages with SKILL.md, references, scripts, and templates. Use when creating new skills, generating custom slash commands, or building reusable AI capabilities. Validates against Agent Skills specification.
Evaluates and optimizes agent skills using a DSPy-powered GEPA (Generate/Evaluate/Propose/Apply) loop. Loads scenario YAML files as DSPy datasets, scores outputs with pattern-matching metrics, and optimizes prompts via BootstrapFewShot or MIPROv2 teleprompters. Also generates new scenario YAML files from skill descriptions.
Reusable template for authoring new Agent Skills with clear triggers, workflow, and I/O contracts.
Open standards and governance rules for Agent Skills. It is used for creation, modification, refactoring, migration, audit and maintenance of skills, and provides platform-independent structural standards, frontmatter specifications, progressive disclosure and quality gates.