Provider Probe

Use this skill to investigate model providers behind OpenAI-compatible base URLs.

When to use

Trigger this skill when the user asks to:

• verify whether a provider's claimed model is real
• inspect a baseURL for hidden/mixed model pools
• compare multiple providers for the same claimed model
• determine whether a provider is better suited as primary or fallback
• create a trust/stability report for model routing

Core method

Always use a layered evidence approach:

1. Read provider config or ask for baseURL + apiKey + claimed model id.
2. Call

   /models

   and inspect whether the returned pool contains mixed vendors or suspicious aliases.
3. Check metadata like

   owned_by

   , model naming conventions, and whether one baseURL exposes many unrelated model families.
4. Probe both

   /responses

   and

   /chat/completions

   with minimal prompts.
5. Run short capability tests and repeated stability tests.
6. Summarize with a confidence rating rather than absolute certainty.

Confidence labels

• High confidence real / most likely genuine: stable, coherent endpoint behavior, believable output structure, low ambiguity.
• Medium confidence / likely routed or wrapped: works, but signs suggest aggregation, aliasing, or proxy adaptation.
• Low confidence / unusable now: 404, repeated timeout, incompatible shape, or too little evidence.

Output contract

Always report:

• 当前做到哪了 / what was tested
• 当前阻塞点 / what remains uncertain
• 下一步动作 / recommended next step

For final results, include:

1. Config facts

2. /models

   findings
3. Endpoint compatibility findings
4. Repeated stability findings
5. Capability/format findings
6. Final trust judgment
7. Recommendation: primary / fallback / avoid

Tooling

Prefer the bundled script for deterministic testing:

• scripts/provider_probe.py

Usage:

python3 scripts/provider_probe.py --config /root/.openclaw/openclaw.json --providers ypemc omgteam vpsai --model gpt-5.4

Or probe a custom URL directly:

python3 scripts/provider_probe.py --base-url https://example.com/v1 --api-key sk-xxx --model gpt-5.4

Interpretation heuristics

Treat a provider as a likely aggregation pool when several of these appear together:

• /models

  returns many unrelated model families

• owned_by

  values are mixed or inconsistent
• the claimed model id looks like a routing alias rather than a canonical model id

• /responses

  and

  /chat/completions

  compatibility is uneven or surprising
• behavior is stable enough to work but not coherent enough to look like a single official upstream

Files

• Reference checklist:

  references/provider-probe-checklist.md

• Probe script:

  scripts/provider_probe.py