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NinjaSln-labsNinjaSln-labs/agent-skills/llm-gateway-ops/SKILL.md

llm-gateway-ops

Skill1 starsChanged 41 days agoNo licenceView on GitHub

Operate the standing configuration of an application's model calls: multi-provider access over openai-compatible endpoints, capability matrices, routing and fallback chains, quota and rate-limit budgets, inference cost attribution, and the seven provider-specific failure classes (rate limits, auth, bad request, content filtering, server error, timeout, response-shape drift). Use when wiring a second provider, choosing a fallback chain, capping spend or throughput, or naming which model tier served a request. NOT for: triaging one reported model call that failed — root-cause tracing, severity grading, shipping a fix, closing it out; prompt design or model evaluation; fine-tuning and training; domain modelling; general observability beyond LLM-specific amounts. Platform model names, endpoints, prices, and timeouts change often — verify against the provider's current documentation. No skill name implied: the boundary is the task.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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