List LinkedIn connections

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the bar is lower. The description adds significant behavioral detail beyond that: pagination mechanics (scroll-paginated until count met, stops growing, internal cap), how the query filter is applied locally, the total count source behavior, and the per-entry fields including 'connected at' timestamp. This goes well beyond the structured hints.

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 description is dense but efficient—about 5 sentences covering all important aspects. It is front-loaded with the core purpose and sorted order, then details parameters and output. Could be slightly more concise (e.g., merging some clauses) but every sentence adds value without fluff.

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 tool with only 2 optional parameters and no output schema, the description covers all necessary context: purpose, sorting, pagination, parameter semantics, output fields, total count source, and read-only nature. An agent can confidently call it and interpret results without needing additional external knowledge.

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 0%, so the description must fully explain both parameters. It does: count is given a default (50), maximum (200), and describes pagination; query is defined as a case-insensitive substring filter applied locally to name and headline. This fully compensates for the lack of schema descriptions.

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 the tool lists the signed-in member's 1st-degree connections with a specific sort order (most recently added first). This distinguishes it from siblings like linkedin_send_connection_request (mutating) and linkedin_scrape_profile (single profile), leaving no ambiguity about what it does.

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 explains when to use it (listing connections) and clarifies that the query filter is local, not LinkedIn's search, which warns against misuse for large lists. However, it does not explicitly point to alternative tools for actions like sending requests or scraping profiles, though the sibling names make that implicit. Slight gap in explicit exclusions.

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