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Agent leaderboards

aa_agents

Query live artificialanalysis.ai leaderboards for coding agents, chatbots, or search APIs; set board, top rows, and refresh to bypass cache.

Instructions

AA agent leaderboards: coding agents, chatbots and search APIs.

Args: board: coding_agents (default), chatbots or search_api. top: rows to return (default 15). refresh: bypass the cache and re-fetch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNo
boardNocoding_agents
refreshNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description must carry the full behavioral burden. It does disclose caching behavior ('refresh: bypass the cache and re-fetch'), which is genuinely useful, but says nothing about auth requirements, rate limits, or that this is a read-only retrieval (implied but unstated). Partial coverage of a no-annotation tool.

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?

Front-loaded one-line summary followed by a compact args block; each line earns its place. The args section is slightly redundant with schema defaults but no sentence is wasted.

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

Completeness3/5

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

No output schema and no annotations exist, so the description is the sole source of information. It covers inputs well but never describes what a returned 'row' contains or the leaderboard structure, leaving the agent unable to anticipate the response shape.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate, and it does: all three parameters are documented, including the valid values for 'board' (coding_agents, chatbots, search_api) which are absent from the schema and not constrained by any enum. Defaults for top and board are restated, which is minor redundancy.

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?

States the resource clearly (agent leaderboards) and enumerates the three content types it covers (coding agents, chatbots, search APIs). An agent understands the deliverable, but the definition never distinguishes itself from close siblings like aa_leaderboard or aa_benchmark_leaderboard, so the boundary is left to inference.

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

Usage Guidelines2/5

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

There is no statement of when to use this tool versus the eleven siblings, several of which (aa_leaderboard, aa_benchmark_leaderboard) sound nearly identical. The only routing clue is the word 'agent' in the description, which the agent must decode on its own.

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