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

Annotations already provide readOnlyHint=true, and the description adds meaningful behavior beyond that: it is answered by generating a read-only SQL query, returns columns and rows rather than prose, and has a 500-character input limit. This is useful operational context not present in the schema or annotations.

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?

Four sentences, each carrying distinct information: scope and examples, execution/output behavior, routing to an alternative, and an input limit. The examples replace lengthy prose and make the description efficient without being bloated.

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-string-parameter tool with a readOnly annotation and no output schema, the description covers what to ask, when to use it instead of search_connections, what kind of result to expect (columns and rows), and the input length limit. No critical information for correct invocation is missing.

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 baseline is 3; the description adds value by giving concrete example questions and the under-500-characters constraint. This meaningfully helps the agent craft a valid free-form question beyond the schema's brief 'plain English' note.

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 'Ask a free-form question about the user's LinkedIn connections' and enumerates the exact query categories it covers with concrete examples: aggregates, rankings, date ranges, location filters, and combined conditions. The phrase 'that the other tools can't express' and the explicit contrast with search_connections clearly distinguish it from siblings.

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 routes simple lookups away from this tool: 'Prefer search_connections for a simple name/company/title lookup — it is faster.' It also defines the usage space positively with categories and multi-condition examples, giving the agent a clear decision rule.

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