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The orchestrator brings the plan. The agent brings the tools.
The key insight is small and load-bearing: skillterm does not call a raw LLM API. It drives a headless agent runtime that already has web search, web fetch, bash, and file I/O — the exact tools building a good skill requires.
The agent architecture, in one line
skillterm cli → claude code / codex (headless) → WebSearch · WebFetch · Bash · Read/Write → SKILL.md
Generation is expensive and happens once per tool. Tab-time lookup is cheap and happens forever. The durable artefact — a SKILL.md on disk — is what makes that asymmetry pay off.
One generation, six stages
From request to Tab completion
01
Prepare task
The CLI parses the request ("generate stripe"), sets the working directory to the skills folder, and pins the prompt.
02
Load bootstrap
Two meta-skills — skill-creator and saas-detector — load into the agent context so it knows the SKILL.md format and how to classify a tool.
03
Invoke runtime
Claude Code (or Codex) runs headless. The agent has WebSearch, WebFetch, Bash, and Read/Write available.
04
Agent reasoning
The agent classifies the tool, searches for canonical docs, fetches and parses them, and runs man / --help as needed.
05
Write SKILL.md
The agent writes the file to the skills directory, following the format spec from skill-creator. skillterm captures the result.
06
Tab-time use
Later, pressing Tab on a matching command makes the shell hook call skillterm complete, which serves completions from the SKILL.md.
Under the hood
A workspace of small crates
skillterm is a Rust workspace. The CLI is thin; most behaviour lives in the SKILL.md format and the agent runtime, so the crates stay focused.
skillterm-cli The binary and command surface. skillterm-core Skill parsing and types. skillterm-agent Agent runtimes (Claude Code, Codex). skillterm-shell Shell integration and completions. skillterm-registry Registry client: search, install, publish. See it generate.
The quickstart takes you from install to a working skill in five steps.