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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety and repeatability profile is fully covered without description help. The description adds the workflow context of a follow-up fetch and sketches the return record, which is useful but partly redundant given an output schema exists. It says nothing about result volume, ranking, rate limits, or what an empty result set looks like, so it adds only modest value above structured fields.

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, front-loaded with the verb and resource, then the result shape, then the follow-up and the alternative — a sensible information order with no filler. The phrase "in the shape ChatGPT deep research and company knowledge use" is the one wordy stretch and leans on external context to convey meaning. Everything else 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 one-parameter read-only search with full schema coverage, complete annotations, and an output schema, the description supplies what the structured fields cannot: the result record shape, the fetch follow-up, and the search_library contrast. Gaps around pagination and result limits are mitigated by the presence of an output schema. Only the absence of any result-count or ranking context keeps it from a 5.

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?

There is one required parameter with 100% schema description coverage ("What to look for."), so the schema already carries the semantics and a baseline of 3 applies. The description never elaborates on the query — no guidance on phrasing, natural-language vs keyword, or the 300-character cap implied by the schema. Nothing is added beyond the schema for the single input.

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 pairs a specific verb with a specific resource ("Search AI Blocks") and characterizes the result shape (id, title, url), which lets an agent picture the output before calling. It also names the nearest sibling, search_library, and states the difference, so the tool is distinguishable from an otherwise near-identical alternative. The only drag is the vague framing phrase "the shape ChatGPT deep research and company knowledge use," which describes a style rather than a capability.

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?

"Read one with fetch" gives an explicit next-step pointer to a named sibling, and the closing sentence contrasts this tool with search_library (filters and one-line summaries). What's missing is an explicit rule for when the plain search is preferable — the agent must infer that filter-free lookup means this tool rather than search_library. That inference is easy but not stated outright.

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