verify-llm-metadata

name

verify-llm-metadata

description

Verify and update one LLM provider's llm_db metadata against that provider's public documentation, public model API data, and cached upstream source data, then prepare a PR. Use when asked to audit, check, confirm, validate, fix, or update provider model metadata such as model IDs, endpoints, limits, prices, modalities, capabilities, lifecycle/deprecation status, aliases, release dates, source mappings, or provider docs for this repository.

Verify LLM Metadata

Scope

Verify exactly one provider per run. If the request names zero providers or multiple providers, ask the user for one provider ID before continuing.

Use public provider documentation and public model data only. Do not use private dashboards, paid accounts, leaked docs, or secrets. If an API requires authentication and no user-approved credential is already in scope, use the provider's public docs instead and mark API-backed evidence unavailable.

The normal end state is a pull request containing source-layer changes plus regenerated artifacts. If the user explicitly asks for audit-only output, stop after the report.

Batch Orchestration

Do not ask one agent invocation to verify multiple providers. To audit a queue, run one isolated invocation of this skill per provider.

Use references/provider-sets.json for curated provider queues. The default popular_core set covers the highest-priority popular providers already present in this repo; popular_extended broadens coverage to more widely used labs, routers, and inference platforms.

Preview the batch commands:

python3 .agents/skills/verify-llm-metadata/scripts/provider_verification_loop.py --provider-set popular_core

Execute the batch with one Codex invocation per provider, each in its own worktree:

python3 .agents/skills/verify-llm-metadata/scripts/provider_verification_loop.py --provider-set popular_core --execute

Use --mode audit-only for reports without edits or PRs. Use --provider-set popular_extended, --providers <id> ..., --start-at <id>, or --limit <n> to control the queue.

Workflow

1. Identify the provider ID used by this repo, such as openai, anthropic, google, xai, azure, or another folder/key under priv/llm_db/local or priv/llm_db/snapshot.json.

2. Create or switch to a focused branch unless the user asked for audit-only work.

3. Extract the provider metadata stack:

   python3 .agents/skills/verify-llm-metadata/scripts/extract_provider_metadata.py <provider_id> --repo-root .
   

   Save large output under tmp/ if needed:

   python3 .agents/skills/verify-llm-metadata/scripts/extract_provider_metadata.py <provider_id> --repo-root . --out tmp/<provider_id>-metadata.json
   

   The helper extracts the built snapshot, generated provider registry, local TOML overlays, and raw remote cache when present. On Python versions without TOML support, source TOML entries may contain _parse_error; use the emitted file paths with sed/rg for source-level inspection.

4. Read references/audit-checklist.md before comparing fields or editing files.

5. Inspect the source stack for this provider:

   • configured source module, such as lib/llm_db/sources/<provider>.ex
   • raw remote cache under priv/llm_db/remote/
   • local overrides under priv/llm_db/local/<provider>/
   • generated outputs under priv/llm_db/providers/ and priv/llm_db/snapshot.json

6. If credentials are already available and the user has not forbidden network/API calls, refresh the provider source:

   mix llm_db.pull --source <provider_id>
   

   If the pull is skipped because no key is available, continue with existing cache plus public docs.

7. Search the web for the provider's official public model source. Start from the local provider doc URL when present, then search official domains for:

   • model list or model catalog
   • API reference for list-models/model endpoints
   • pricing page
   • deprecation, lifecycle, changelog, release notes, or model migration pages

Layer Placement

Each finding must include a capture layer:

• remote-cache: Re-run mix llm_db.pull --source <provider_id> when the raw provider API cache is stale or absent. Never hand-edit remote cache files.
• source-transform: Edit lib/llm_db/sources/<provider>.ex when the official API returns a field but the repo drops, misnames, or mis-maps it.
• local-override: Edit sparse TOML under priv/llm_db/local/<provider>/ for curated facts absent from the API but present in official docs, such as lifecycle/deprecation, aliases, pricing pages, and documented provider exclusions.
• enrichment: Edit enrichment/runtime code when the same derived rule applies across many models/providers.
• generated-artifact: Regenerate with mix llm_db.build --install; commit generated artifacts only as build outputs.
• unverified: Do not edit; document what evidence is missing.

For providers backed by a model endpoint, remember that the endpoint may not include docs-only fields. For example, Anthropic's Models API exposes IDs, display names, creation dates, capabilities, and token limits, but lifecycle/deprecation, pricing, aliases, and some docs context can require separate public documentation.

Verify Fields

Check these fields when the provider publishes them:

• Provider metadata: name, doc, base_url, environment variable hints, runtime/endpoint notes.
• Model inventory: local model IDs, documented model IDs, removed or missing models, aliases, provider_model_id.
• Dates and lifecycle: release_date, last_updated, knowledge, deprecated, retired, lifecycle.
• Limits: limits.context, limits.output, embedding dimensions, image/audio constraints when modeled.
• Pricing: cost, pricing.components, currency, per-unit basis, cache/read/write/tool/storage meters.
• Capabilities: chat/text, embeddings, rerank, image, audio, realtime, reasoning, tool calling, JSON/schema support, streaming, caching.
• Modalities: text, image, audio, pdf, video input/output.
• Execution metadata: base URL overrides, path, operation family, transport, and wire protocol.

Output

Start with a concise status line:

Provider: <provider_id> | Result: verified / mismatches found / incomplete evidence

Then include:

• Sources: official URLs used, with access date.
• Summary counts: checked, verified, mismatched, unverified.
• Findings: ordered by severity (P1 wrong model IDs/endpoints/pricing/lifecycle, P2 limits/capabilities/modalities, P3 names/docs/dates/notes), each with capture layer, file path, and action.
• Changes made: source files changed, generated artifacts rebuilt, tests run.
• PR: branch, commit, PR URL, and any known residual uncertainty.
• Evidence notes: quote only short excerpts and paraphrase the rest.

Be explicit when evidence is ambiguous. Use phrases such as not publicly documented, docs conflict, API requires authentication, or provider page does not expose this field.