Skill: andyrenxu7255/provider-probe (version 1.0.1)

--- name: provider-probe description: | Probe and verify whether an OpenAI-compatible baseURL is a real single-model endpoint or a multi-model aggregation pool. Use when auditing model providers, checking /models output, comparing completions vs responses support, validating claimed model IDs like gpt-5.4, or producing a provider trust/stability report for OpenClaw routing decisions. --- # 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: ```bash python3 scripts/provider_probe.py --config /root/.openclaw/openclaw.json --providers ypemc omgteam vpsai --model gpt-5.4 ``` Or probe a custom URL directly: ```bash 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`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)