# Recipe 06 — The llmsx CLI Lint, query, export and inspect the tree from a shell: the llmsx commands and the hub scripts each one wraps today. ## Goal Do the four everyday operations — lint a file, look up an exact token, export a family from a mirror, show a concept-tree node — from a shell, in a form a script or a CI step can call. `llmsx` is the site's CLI; in this step it is a thin name over the hub scripts, and each command below shows both spellings so the recipe works before `llmsx` ships. ## When not to use it - You are inside Claude Code with the hub MCP connected. The MCP tools ([recipe-03](/examples/recipe-03/), [recipe-05](/examples/recipe-05/)) return structured replies; the CLI prints text. - You want the model passes of the optimizer (`/ldo`). The CLI runs the deterministic passes only; the model and live passes are the skill, not the script. - You are gating a repository. That is [recipe-08](/examples/recipe-08/) — the same lint, wrapped as an Action with the exit code mapped to a failed check. ## Steps Each pair is the `llmsx` form and the hub form it wraps. Run the hub forms from `~/.global-ai-hub` (or `hub/` in this repo) with its `.venv`. **Lint** — the deterministic passes P0–P3, P5–P7, P9 and P14, exit 1 on any High: ``` llmsx lint ./docs/llms.txt --json .venv/bin/python scripts/llms_lint.py check ./docs/llms.txt --json ``` Add `--check-links` for the HEAD probes (N6) and `--kind vocabulary` for a `llms-vocabulary.txt`; `check DIR` walks a split root's sections. **Query, keyword mode** — FTS5 over the facts layer, no embedding: ``` llmsx query code.claude.com "CLAUDE_CODE_SYNC_SKILLS" --mode keyword .venv/bin/python scripts/docset_indexer.py keyword codeclaudecom__codeclaudecom "CLAUDE_CODE_SYNC_SKILLS" --layer facts --mode phrase --top 5 ``` **Export** — a mirror to the family files (`clean → extract → render → export`, no model): ``` llmsx export mirrors/code.claude.com.md PYTHONPATH=scripts .venv/bin/python -m docset_refine all --no-units mirrors/code.claude.com.md ``` writes `code.claude.com.llms/{llms,llms-full,llms-small,llms-facts}.txt` and `manifest.json` with byte and token counts per file. **Tree** — a concept node with its children, slug and aliases: ``` llmsx tree show "llms.txt" .venv/bin/python scripts/concept_tree.py show "llms.txt" ``` ## Expected output `lint --json` prints one result object per file — `{file, kind, grammar, findings: [{pass, attr, severity, line, msg, fixable}], counts}`, the `attr` from the rubric (`I2`, `N6`, `H3`, …) and the `pass` that raised it — and exits 0 when no finding is High. `query` prints one hit per line: type, text, `url#anchor`. `export` prints the manifest's file table. `tree show` prints the node, its `slug`, its `aliases` (which [recipe-12](/examples/recipe-12/) feeds), and its children with their state. A run against this site's own files: ``` $ llmsx lint site/dist/llms.txt site/dist/llms-facts.txt --json | jq -c '.[] | {file, high: .counts.high}' {"file":"site/dist/llms.txt","high":0} {"file":"site/dist/llms-facts.txt","high":0} $ echo $? 0 ``` Zero Highs across every object is the pass condition the CI uses; the exit code carries the same verdict. ## Cost Measured: lint is under a second per file without `--check-links`, plus network time with it (8-way concurrent HEADs, 10 s timeout each). Keyword query is sub-millisecond after the index exists. Export is seconds per hundred pages and spends no model tokens in this step. Tree show is a JSON read. > Runnable in step 4 (playground).