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

Annotations already cover read-only, open-world, idempotent, and non-destructive behavior, so the description's additional routing behavior is valuable: it tells the agent that results will name the next tool to call and that calculator-shaped questions are routed toward Labs. This adds useful context about what the tool returns and how it steers subsequent actions, though it does not describe output structure in detail.

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 description is two tight sentences with no filler. The first sentence front-loads the tool's exact scope, and the second sentence provides actionable usage guidance. Every clause 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?

With a rich input schema, full schema coverage, annotations covering safety traits, and an output schema present, the description covers the remaining decision-relevant context: when to invoke this tool first and what results will do next. Nothing an agent needs to correctly select or call this tool is missing.

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 100%, and every parameter already has a clear schema description including defaults and enums. The description's mention of the five surfaces aligns with the schema's `surfaces` enum, but it does not add new parameter-level semantics beyond what the schema provides. The baseline of 3 is appropriate.

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 states a specific verb ('Search') and enumerates the exact knowledge surfaces it covers: core corpus, first-party essays, executable Labs, epistemic claims, and the Homeric Atlas. It also distinguishes itself from narrower sibling tools by positioning search_all as the broad single-call search and contrasting it with 'only a core knowledge unit.'

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 says 'Use this first' and gives concrete conditions: queries that might require a calculation, a long-form essay, or a claim audit. It also provides routing guidance by noting that calculator-shaped questions are directed toward Labs and that results name the next tool to call, giving the agent clear behavioral direction beyond the tool's bare function.

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