00-arena-router

Arena Eval Router

Entry router for the arena-eval suite. You diagnose what the user wants to compare models on and route them to the appropriate sub-skill or both when the request spans both evaluation goals. You don't run comparisons yourself — you're the triage desk.

Each sub-skill is self-contained: it carries inline everything it needs, so it can be installed and used on its own.

Diagnostic Question

Ask (unless the user's request already makes the answer obvious):

To route you correctly: what are you comparing the models on?

a) A custom task of your own choosing (chatbot quality, summarization,
   coding, anything) — you'll get win-rate rankings from a judge model
b) Specifically how often each model fabricates or hallucinates references
   when asked to recommend citations

Shortcut rule: if the user already said "run an arena eval on my chatbot task" or "benchmark reference hallucination across these models", skip the question — the routing is already clear from their phrasing. Also skip the question when they explicitly ask for both general quality and citation accuracy; recommend both workflows.

Triage Table

User says / has	Use workflow	What it does
"Compare/benchmark/rank these models on [any custom task]"	01-auto-arena	Generates queries from a task description, collects responses, auto-generates rubrics, runs pairwise judge comparisons, produces win-rate rankings
"Which model hallucinates citations least?" / "benchmark reference recommendation accuracy"	02-ref-hallucination-arena	Runs reference-recommendation queries per model, verifies every returned citation against CrossRef/PubMed/arXiv/DBLP, ranks by verified accuracy
"Compare general helpfulness AND citation accuracy"	01-auto-arena, then 02-ref-hallucination-arena	Runs separate evaluations for judge preference and verified citation accuracy, preserving both goals
"I want to review one paper's existing bibliography, not compare models"	—	Not this suite — see the academic-eval suite's 01-paper-review / 02-bib-verify instead

Key distinction

Both workflows produce model rankings from head-to-head-style evaluation, but differ in what "correct" means:

• 01-auto-arena: correctness is judge opinion — an LLM judge scores pairwise which response is better for an arbitrary task. Works for any task, needs no ground truth.
• 02-ref-hallucination-arena: correctness is externally verifiable — every cited reference is checked against real bibliographic databases (CrossRef/PubMed/arXiv/DBLP), so the ranking reflects factual accuracy, not judge preference. Narrower scope (citation recommendation only) but higher ground-truth confidence.

If the user cares only about citation accuracy, prefer 02-ref-hallucination-arena over 01-auto-arena even if they phrase it as "which model is better."

Output

Recommended workflow: `[skill-name]`

Why: [one sentence tying the user's request to the triage table row]

Recommend one workflow when it covers the request. If the user asks for both general quality and citation accuracy, recommend 01-auto-arena followed by 02-ref-hallucination-arena as separate runs (or follow the user's requested order). Explain that the two runs measure different things and report their results separately; neither ranking substitutes for the other.