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

Annotations already cover the safe read-only, idempotent, non-destructive profile. The description adds valuable behavioral context beyond annotations by stating results are ranked, accent-insensitive, and search across titles, summaries, topics, and bodies. No contradiction with annotations exists.

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 carry the key behavioral facts, usage guidance, and a pointer to the next step without any filler. The most important information is front-loaded in the first sentence.

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 annotation set, 100% schema coverage, and an output schema, the description covers everything an agent needs to select and invoke this tool correctly. It states the search scope, the intended use case, and the natural follow-up tool.

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%, so the schema already documents query, limit, and locale clearly. The description reinforces the broad scope of the query field but does not add new parameter semantics beyond what the schema provides, which matches the baseline score.

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 opens with a specific verb and resource: 'full-text search over every first-party essay', including which fields are searched. This clearly distinguishes it from sibling tools like get_article and list_articles because it is a ranked search operation, not a retrieval or listing tool.

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 to use this tool when long-form analysis about a topic is needed and gives a follow-up action with get_article for the complete essay. It does not explicitly state when not to use it or directly contrast it with the generic search sibling, so it stops short of a perfect 5.

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