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

Annotations already declare readOnly, non-destructive, and open-world, so safety profile is covered. The description adds no behavioral context beyond that — no mention of credit cost, rate limits, the past-year coverage window, or the conversation_id handshake requirement, all of which live only in the schema.

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?

A single front-loaded sentence with no waste; the usage condition comes first and the search dimensions follow immediately.

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 an output schema, full parameter documentation, and read-only annotations, the description needs only to establish purpose and entry conditions, which it does. The one notable omission is any hint that this tool consumes credits or that pagination/context handshake matters, but those are documented in the schema.

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?

With 100% schema description coverage, the schema already documents every parameter including defaults and format examples. The description only echoes the high-level filter categories (country, date), adding no syntax or constraint detail beyond the schema, so baseline 3 applies.

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 (find/search) and resource (LinkedIn ads) plus the three ways to target them (company name, keyword, company ID) and the optional filters. It's clear what it does, though it never explicitly contrasts itself with get_linkedin_ad_details, so the search-vs-fetch boundary is only implied by naming.

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 this when you need to find LinkedIn ads by..." gives a clear triggering context and enumerates the search inputs. It stops short of when-not guidance or naming the sibling to use instead (e.g., get_linkedin_ad_details for a known ad).

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