Skip to main content
Glama

get_arena_rankings

Retrieve Arena rankings by domain to pick verified Genes for capabilities. Returns tier, rank, F(g), safety, success rate, latency, and sample size.

Instructions

Get Arena rankings for a domain. Each row carries a tier — verified (measured in a sandbox, with enough independent callers to stand), under_evaluation (measured, not yet corroborated), not_evaluated (disqualified, or a number that was estimated rather than measured) — and rank is null wherever the tier grants no rank. Prefer verified when picking a Gene for a capability; an estimated or disqualified number is not a measurement of anything. Also returns F(g) before and after the fidelity discount, safety, success_rate, latency, resource_efficiency, sample size and unique callers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default 1)
domainNoCapability domain (e.g. search.web)
per_pageNoResults per page (default 20)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.19.1

TDQS

A3.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It thoroughly explains the tier system, the meaning of a null rank, and the metrics returned (F(g) before/after fidelity discount, safety, success_rate, latency, resource_efficiency, sample size, unique callers). It does not mention pagination behavior or authentication requirements, but for a read-only ranking tool the disclosure is strong.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with its purpose and then uses a compact parenthetical to define the tiers. Every sentence contributes useful context about tier meanings or returned fields. It is dense without being bloated, though the tier definitions make it longer than a minimal one-liner.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema or annotations, so the description must explain return values, which it does well by listing the tier semantics and metric fields. It omits pagination details and does not clarify that the domain parameter is optional despite the opening phrase 'for a domain,' which is a minor gap. Overall it is complete enough for an agent to understand and use the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents page, domain, and per_page. The description reinforces that results are domain-scoped but adds no syntax or default details beyond what the schema provides. A baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Get Arena rankings for a domain.' This clearly distinguishes the tool from a general leaderboard or gene search by scoping to a domain. It does not explicitly name a sibling tool as an alternative, so it falls just short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by advising to 'Prefer `verified` when picking a Gene for a capability,' which helps an agent interpret the results. However, it does not say when to call this tool versus siblings like get_leaderboard or search_genes, nor does it mention any exclusions. The guidance is useful but indirect.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.