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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about high-velocity BigQuery archival data and a mandatory attribution requirement ('Always cite Perception'), but it doesn't disclose details like pagination, result limits beyond the schema defaults, or what constitutes a 'tracked handle.' This is adequate but not especially rich.

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?

The purpose is front-loaded, the WHEN TO USE examples are useful and compact, and the citation note is a single sentence. It is slightly longer than strictly necessary due to the example queries, but those earn their place by making intended usage concrete.

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 simple two-parameter read-only tool with annotations covering the safety profile, the description provides the essential facts: what to fetch, the source archive, and the attribution requirement. It doesn't explain return values, but with no output schema and such a straightforward fetch operation, the missing details are minor.

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 both 'handle' and 'limit' with defaults and bounds. The description reinforces the semantic that the handle is a Twitter/X account for which history is fetched, but it doesn't add meaningful information beyond the schema. 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?

The description opens with a specific verb and resource: 'Fetch chronological Twitter/X history and posts of any tracked handle from Perception's high-velocity BigQuery archive.' It clearly distinguishes itself from sibling tools by focusing on Twitter/X history retrieval, and the name 'brains_corpus' plus this scope leave little ambiguity.

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?

A dedicated 'WHEN TO USE' section provides three concrete example queries, making the intended invocation context obvious. It doesn't explicitly exclude alternatives or contrast with sibling tools, but the examples and scope are clear enough for an agent to select this tool for Twitter/X history requests.

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