worldjen-bench

Preamble (run first)

Best-effort update check. Fails silently on network errors or non-marketplace installs. If output starts with UPGRADE_AVAILABLE or JUST_UPGRADED, surface it once to the user and continue with the skill workflow.

{
  for _p in \
    "$HOME/.claude/plugins/marketplaces/worldjen/bin/check-update" \
    "$HOME/.codex/.tmp/plugins/plugins/worldjen/bin/check-update"; do
    if [ -x "$_p" ]; then "$_p" 2>/dev/null && break; fi
  done
} 2>/dev/null || true

WorldJen — Bench

"How does the model perform overall?" Bench runs a full benchmark at scale: many prompts, your chosen dimensions, optionally multiple models compared, executed on a GPU worker queue.

This skill is for Bench run lifecycle. For setting up the GPU worker host that executes runs, use the worldjen-runner skill. For single-clip scoring, use worldjen-score; for prompt-locked ranking, use worldjen-rank.

Auth

Set WORLDJEN_API_KEY (get one at https://www.worldjen.com/settings/api-keys), or pass --api-key.

If worldjen is not installed yet, run pip install worldjen first (or use the worldjen-install skill).

Discover inputs first

Don't invent IDs — list them:

worldjen dimensions list --json
worldjen models list
worldjen runner list

Create a Bench run

worldjen bench create \
  --name "<RUN_NAME>" \
  --dimensions "<DIM1,DIM2>" \
  --runner-id "<RUNNER_ID>" \
  --model-id "<MODEL_ID>"

Optional flags:

• --reference-model-id <REF_MODEL_ID> — compare against another model in the same run
• --reasoning — store the per-dimension reasoning and generated summaries (off by default)
• --run-instructions <JSON_OR_PATH> — runner pipeline options (inline JSON or path to a .json)

Inspect

worldjen bench list --json
worldjen bench list --status running          # filter; also --page / --limit
worldjen bench get <RUN_ID> --json
worldjen bench logs <RUN_ID>
worldjen bench videos <RUN_ID> --json
worldjen bench csv <RUN_ID> -o results.csv    # scorecard
worldjen bench download-videos <RUN_ID> -o ./videos

Compare runs

Fetch both runs as JSON and diff the per-dimension scores. Useful for catching regressions across model checkpoints (v3 → v4 → v5):

worldjen bench get <RUN_ID_A> --json
worldjen bench get <RUN_ID_B> --json

Flag any dimension where the score dropped by your threshold (5pp is a common gate for CI).

SDK alternative

• worldjen.bench.create(...) — enqueue a run on a runner you provisioned; the call returns immediately and the worker handles generation, upload, and scoring.
• worldjen.bench.run_with_pipeline(...) — in-process variant for scripts that already have the model loaded in Python; the SDK drives generation, upload, and (optionally) waits for evaluator scores. There is no CLI equivalent — Python callables don't survive shell arguments.

REST API (no SDK)

The CLI and SDK both wrap /api/v1/bench. Use the X-API-Key header and an Idempotency-Key on POSTs so retries don't double-create.

Confirm before destructive operations

• worldjen bench cancel <RUN_ID> — stops a queued or in-flight run; partial results may be lost
• worldjen bench delete <RUN_ID> — permanently removes the run record and artifacts

Confirm with the user before either.

Stop and ask when needed

• Missing WORLDJEN_API_KEY
• Missing runner ID, model ID, or run ID — list them first
• The user only wants to score a single clip — that's worldjen-score, not a full Bench run

See also

• worldjen-install — install the SDK and CLI
• worldjen-runner — set up the GPU worker host
• worldjen-score — raw per-dimension scores for a single clip
• worldjen-rank — comparative ranking of clips that share a prompt
• worldjen-leaderboard — public leaderboard (no auth)

For examples and troubleshooting, see references/examples.md.