Chainguard Skills

Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use agent-platform-deploy), or managing serving endpoints (use agent-platform-endpoint-management).

Manages GenAI tuning jobs in Agent Platform. Use this to list, get, or cancel ongoing model tuning jobs. Don't use for fine-tuning models (use agent-platform-tuning), deploying models to endpoints (use agent-platform-deploy), or managing serving endpoints (use agent-platform-endpoint-management).

Use this skill when the user wants to author, design, scope, or refine an Agent Skill (a SKILL.md file). Trigger phrases include "build a new skill", "design an agent skill", "scope a SKILL.md", "how should I structure this skill", "write a skill for X", "my skill isn't working well", or any request to improve an existing SKILL.md. Walks the user through an empirical, test-first process — probe the agent for real failures, design only for genuine knowledge gaps, iterate against runnable examples, and verify across models.

Datadog skills for AI agents. Essential monitoring, logging, tracing and observability.

Verify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when:

• Generating SHA-256 integrity manifests for agent plugins or tool packages
• Verifying that installed plugins match their published manifests
• Detecting tampered, modified, or untracked files in agent tool directories
• Auditing dependency pinning and version policies for agent components
• Building provenance chains for agent plugin promotion (dev → staging → production)
• Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"

Run AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok

Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when:

• Implementing self-critique and reflection loops
• Building evaluator-optimizer pipelines for quality-critical generation
• Creating test-driven code refinement workflows
• Designing rubric-based or LLM-as-judge evaluation systems
• Adding iterative improvement to agent outputs (code, reports, analysis)
• Measuring and improving agent response quality

Build voice AI agents with ElevenLabs. Use when creating voice assistants, customer service bots, interactive voice characters, or any real-time voice conversation experience, and when configuring an agent's tools, workflows, or procedures, including creating, editing, compiling, and publishing procedure drafts on an agent branch over the SDKs or REST API.