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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds corpus scope (what is indexed), which is genuinely useful, but says nothing about result ranking, result shape, or the default limit of 10 — behavior the agent would want to know before calling.

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?

Two short sentences, zero filler, with the capability stated first and the usage trigger second. Ideal front-loading for a search entry point.

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 3-parameter read-only search with no output schema, the agent still lacks any sense of what comes back (snippets, records, IDs) or how to paginate/refine beyond the limit and fields params. The corpus scope is stated but the result contract is not.

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 67%: query documents Hebrew/English input and fields documents the dot-path projection syntax, while limit relies on its name and default/max constraints alone. The description contributes no parameter meaning at all, so this sits at the baseline rather than above it.

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 (search) and enumerates the corpus it covers: pages, past projects, products and guides. That is enough to distinguish it from the point-lookup siblings like get_product and list_projects, though it never names them explicitly.

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?

"Use for any question about what the studio has done or sells" gives a clear positive trigger condition. It stops short of any when-not guidance or explicit routing to get_product/get_project for exact retrieval, so the agent must infer the boundary.

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