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 quality, or migrating community skills into a local library. Do not use when building a novel skill with no external precedent or for quick one-off evaluation (just read the skill directly).
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 skill package". Do not use for creating a new skill from scratch (use skill-creator), trigger-only fixes when the body is fine (use skill-trigger-optimization), porting a skill to a different stack or context (use skill-adaptation), or quick structural audits with no rewrite (use skill-anti-patterns).
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), packaging skills for distribution (use skill-packaging), or improving already-installed skills (use skill-improver).
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 pipelines with state persistence and conditional branching. Do not use for single skill operations (use the skill directly) or exploratory tasks without defined workflow.
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 OpenCode metadata", "build a release bundle", or "package these skills for release". Do not use for installing bundles (use skill-installer), writing new skills (use skill-creator), or documenting skill origin and trust chain (use skill-provenance).
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 design. Does not trigger on ordinary software tasks without model, inference, evaluation, or agent-runtime concerns.
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 to production", "manage model versions", "model stage transitions", "model governance", "model rollback", "model lineage", and "champion/challenger A/B models".