search_evidence

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds useful context about cost ('$0.00 free') and scope ('bounded public StackBench benchmark and failure evidence'), but it does not disclose additional behavioral traits such as rate limits, query interpretation, or result format; the output schema helps fill the return-format gap.

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?

The entire description is one efficient sentence with no wasted words. It front-loads the action and scope, then states the usage condition. Every phrase earns its place.

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 simple two-parameter search tool with a rich annotation set and an output schema, the description is largely sufficient: it states scope, cost, and when to use it. The main gap is parameter-level instruction, but given the simple schema and available output schema, the overall context is adequate for correct invocation.

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 description coverage is 0%, so the description must compensate, but it does not explain query semantics or limit behavior. 'Query' is implicitly a search term, but there is no guidance on how to phrase queries or how 'limit' affects results. The two parameters remain mostly self-explanatory only by their names, not by meaningful description.

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?

The description names a specific verb ('search'), a specific resource ('bounded public StackBench benchmark and failure evidence'), and the intended use ('evidence-only requests'). It clearly distinguishes this tool from the deployment/prediction/configuration siblings.

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 description explicitly states 'use this for evidence-only requests,' giving the agent a clear condition for when to select this tool. It does not name alternatives or explicitly exclude other cases, but the usage context is clear from the sibling tool names.

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