Benchmark & metric search index

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

With no annotations, the description carries the full behavioral burden. It does add real value by disclosing that every hit embeds a 'How to query' hint (the exact follow-up tool call), which is a non-obvious output behavior. It says nothing about result limits, pagination, ordering, or whether the index is read-only, so the disclosure is partial.

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

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

Front-loaded one-line purpose, then the key output affordance, then a scoped Args block. Every sentence earns its place and the concrete 'Artificial Analysis Speech to Speech Index' → aa_media example is high-value rather than filler.

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

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

For a 4-parameter, annotation-free, output-schema-free search tool, the definition covers purpose, filtering dimensions, and hit contents. It leaves minor gaps around result volume, ordering, and pagination, but nothing that would cause an agent to invoke it incorrectly.

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

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

Schema coverage is 0%, so the description must compensate and it largely does: it defines query's matching semantics (AND over key/label/aliases/description/tags), enumerates realistic domain values, explains that tag is a narrower filter than domain, and says verbose surfaces what each thing measures. Only the lack of a tag vocabulary or worked examples keeps it short of complete.

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

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

States a specific verb and resource set: 'Search everything rankable: benchmarks, indexes, derived metrics, arenas.' An agent can tell this is a discovery/search index rather than a leaderboard tool. It does not, however, distinguish itself from the similarly-named sibling aa_search or explain how it relates to aa_benchmark_leaderboard, so sibling differentiation is only partial.

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

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

The Args block implies usage: tokenised AND-match queries, a domain filter, or a narrower tag filter, which tells the agent how to drive the tool. But there is no explicit statement of when to prefer this over aa_search, aa_benchmark_leaderboard, or aa_leaderboard, and no exclusions or prerequisites. Usage is inferable but not guided.

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