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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive, so the safety profile is covered. The description adds genuinely new behavioral information: results are limited to opted-in and writer-approved public content, telling the agent it cannot surface private or unapproved material. It stops short of disclosing ranking, result caps, or pagination behavior.

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 sentences, front-loaded with the scope-defining statement. The second sentence about ChatGPT deep research and company knowledge is short but is more integration marketing than invocation guidance, slightly diluting the payload.

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 one fully documented parameter and rich annotations, the definition is callable as-is, but it omits any sense of return shape or result limits, and there is no output schema to substitute for that. Adding a sentence on what a result contains and how many come back would close the remaining gap.

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 100% and the single query parameter's description already enumerates what can be searched (shows, writers, projects, genres, formats, accolades, table reads, pitch assets, trailers). The description adds no query syntax, operators, or format guidance beyond the schema, so the 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 (Search) and enumerates the indexed resource types: opted-in public writer profiles, project summaries, and writer-approved public assets. It is clear what the tool returns, though it never contrasts itself with siblings like find_writers or find_projects, leaving the general-vs-structured-search distinction implicit.

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?

Usage is implied through the corpus description (public, opted-in discovery) and the note about ChatGPT deep research / company knowledge, which hints at the intended discovery context. However, there is no explicit when-to-use/when-not guidance and no sibling named as an alternative, so an agent must infer that this is the broad free-text search.

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