Args:
    creator: Filter by creator name (case-insensitive substring match)
    name: Filter by model name (case-insensitive substring match)
    slug: Filter by slug (case-insensitive substring match)
    sort_by: Sort key - 'intelligence', 'price', 'speed', 'ttft', 'coding', 'math'
    limit: Max models to return (default 20)

Returns:
    JSON array of model summaries.

Args:
    identifier: Model id (UUID), slug, or name. Partial matching supported.

Returns:
    JSON object with full model details, or candidates if multiple matches.

Args:
    identifiers: List of model ids, slugs, or names (at least 2).

Returns:
    JSON object with comparison table and per-model details.

Identifies new models, removed models, and field-level changes (pricing, speed,
intelligence scores, etc.). On first run, saves a baseline snapshot and reports
the full model list as "initial baseline".

Args:
    save_new_snapshot: If true (default), save the current data as the new snapshot
                      after diffing. Set false to preview-only.

Returns:
    JSON with structured diff: added, removed, changed models with field-level deltas.

Args:
    modality: One of 'text-to-image', 'image-editing', 'text-to-speech',
              'text-to-video', 'image-to-video'
    top_n: Number of top models to return (default 10)
    include_categories: Include per-category Elo breakdown (text-to-image, text-to-video only)

Returns:
    JSON array of media model rankings.

The upstream endpoint requires submissions for all public CritPt problems in
one request. Each submission should include problem_id, generated_code,
model, and generation_config. This tool can take substantial time because
the upstream grading service runs benchmark evaluation jobs.

Args:
    submissions: Complete list of CritPt submission objects.
    batch_metadata: Optional metadata for the batch.

Returns:
    JSON response with accuracy, timeout rate, and judge/server error counts.

Returns:
    JSON with connectivity status, model count, and any error details.