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

Annotations already provide safety info (readOnlyHint, idempotentHint, etc.). Description adds useful context like 'Returns the latest rows (newest-first)' and explains the free-text filter via `q`. No contradictions. However, it could mention pagination or error handling but overall sufficient.

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?

Three sentences, each earning its place: purpose, usage guidance, and parameter info. No extraneous text. Front-loaded with key information.

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?

Given no output schema, the description only vaguely states 'returns the latest rows'. It doesn't specify return format, error handling, or rate limits. However, the tool is simple and annotations cover safety. For completeness, mention of output structure would be helpful, so a 3 is appropriate.

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%, so baseline is 3. Description adds value by explaining that `q` is a free-text filter across all columns and lists dataset enum values. Examples further clarify usage. This goes beyond the raw schema.

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 clearly states it retrieves 'recent records' from a specific source (Montreal open dataset) and lists exact datasets (311, crime, permits). It distinguishes itself from the sibling tool 'montreal_query' by stating 'for full control use montreal_query', so the agent knows when to use which.

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?

Explicitly tells the agent to 'PREFER OVER WEB SEARCH' for certain queries, and contrasts with 'montreal_query' for full control. This provides clear guidance on when to use this tool versus alternatives.

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