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@llmintel/cli
Advanced tools
Fail your CI build when it references retired or soon-to-be-retired AI models. The LLMIntel lifecycle gate.
Fail your CI build when it references retired or soon-to-be-retired AI models.
llmintel check scans your code/config for referenced model ids (and/or takes explicit ids),
looks up their lifecycle state via the LLMIntel API, and exits
non-zero when any referenced model is retired or past its retirement date — so you migrate on
your schedule, not the provider's shutoff date.
No install required — run it with npx:
npx @llmintel/cli@latest check src config
Or add it as a dev dependency:
npm install --save-dev @llmintel/cli
Create an API key from your dashboard and expose it as an environment variable:
export LLMINTEL_API_KEY="mc_live_..."
# Scan files/directories for referenced model ids and gate on lifecycle state:
llmintel check src config
# Check explicit ids/aliases without scanning:
llmintel check --models "gpt-4o,claude-3-opus-20240229"
# Use a config file:
llmintel check --config llmintel.json
| Flag | Description |
|---|---|
-m, --models <a,b,c> | Explicit model ids/aliases to check (repeatable) |
-c, --config <file> | JSON config: { "models": [...], "paths": [...], "warnDays": 90 } |
--api-url <url> | API base URL (env LLMINTEL_API_URL, default https://llmintel.vercel.app) |
--api-key <key> | API key (env LLMINTEL_API_KEY) |
--warn-days <n> | Warn when a model retires within this many days (default 90) |
--fail-on-warn | Treat warnings (deprecated / retiring soon) as build failures |
--fail-on-unknown | Treat references LLMIntel does not track as build failures |
--no-policy | Ignore your account's central policy; use only the flags above |
--optimize | Also print advisory cheaper/faster model suggestions (paid; never fails the build) |
--json | Machine-readable JSON output |
-q, --quiet | Only print failures |
By default check fails only on retired (or past-due) models — free forever. On a paid plan
you can configure a stricter policy once in your dashboard
and every pipeline picks it up automatically: fail on deprecated/retiring, set the warn
window, and fail on untracked references.
check fetches this policy on each run and uses it as the baseline. Explicit local flags
(--warn-days, --fail-on-unknown) override it; pass --no-policy to ignore it entirely. Free
accounts are always clamped to the retired-only gate regardless of any saved policy.
sync)llmintel sync discovers the models your code references — the same scan as check — and
registers them as your account's watched set server-side. Combined with push alerts
(webhook / Slack / PagerDuty), this gives you "fire and forget" coverage: run sync in CI on
merge to main, and you'll be notified the moment a model you actually use is deprecated or
retired, with no watchlist to curate by hand.
# Replace your watched set with whatever your code references now:
llmintel sync src config
# Preview the diff without writing anything:
llmintel sync src config --dry-run
# Only add models; never remove ones you watch elsewhere:
llmintel sync src config --no-prune
sync requires a paid plan with auto-watch enabled and an API key linked to an account. It prints
the diff of added / removed / unchanged watches plus any unresolved references.
| Code | Meaning |
|---|---|
0 | All referenced models healthy |
1 | One or more errors (retired / past due), or warnings with --fail-on-warn |
2 | Usage / configuration error |
3 | API or network error |
A composite action ships alongside the CLI:
- uses: hivemindunit/llmintel-cli/packages/cli@main
with:
api-key: ${{ secrets.LLMINTEL_API_KEY }}
paths: "src config"
warn-days: "90"
MIT
FAQs
Fail your CI build when it references retired or soon-to-be-retired AI models. The LLMIntel lifecycle gate.
We found that @llmintel/cli demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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