Find external skills from public registries, GitHub repos, and official skill collections, then evaluate them for quality, licensing, and fitness for adoption. Use when looking for existing skills before building from scratch, evaluating external skill…
Improve an existing skill package — tighten routing, sharpen procedure, add or prune support layers, upgrade packaging. Use when the user says "improve this skill", "this skill is weak/vague/bloated", "harden this SKILL.md", or "add evals/references to this…
Install a skill package into the local agent client from a GitHub repository, local folder, or archive. Use when the user says "install this skill", "add skill from GitHub", or "list available skills". Do not use for creating new skills (use skill-creator),…
Orchestrate multi-skill pipelines through the CLI. Use when "run the creation pipeline", "execute the improvement workflow", "resume my pipeline", or when chaining multiple skills with decision points. Supports Creation, Improvement, and Library Management…
Bundle one or more completed skill folders into versioned distributable archives with manifests, integrity checksums, and OpenCode metadata. Use when a user says "package this skill", "bundle for distribution", "prepare a versioned release", "generate…
Polish and finalize an AI agent prompt file by refining structure, wording, and clarity to match proven best practices while preserving the original intent and markdown frontmatter.
Integrate LLM capabilities into applications with explicit runtime boundaries, structured schemas, cost controls, and evaluation plans. Triggers on tasks involving model inference APIs, prompt engineering systems, LLM toolchain setup, or AI agent runtime…
Register, version, and govern MLflow models through a full lifecycle from training-run artifact to production stage with validation gates, alias-based deployment routing, lineage tracking, and CI/CD automation. Triggers on "register a model", "promote model…