send_connection_request

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: it's a write operation (implied by 'Send'), mentions success status returns, warns about unofficial API usage and bot detection risks, and notes LinkedIn's rate limits. This covers critical aspects like mutation, authentication needs (implied by API), and usage constraints, though it could add more on error handling or response format details.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a structured 'Args' section for parameters, return info, and a WARNING block for critical context. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 the tool's complexity (a write operation with API risks), no annotations, 0% schema coverage, but an output schema present, the description is largely complete. It covers purpose, parameters, returns, and warnings, but could improve by mentioning prerequisites (e.g., authentication status) or linking to sibling tools like 'get_invitations' for managing requests. The output schema handles return values, so that gap is mitigated.

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 0%, so the description must compensate. It adds meaningful semantics: 'profile_id' is explained as 'LinkedIn profile public ID' with an example ('john-doe'), and 'message' is clarified as optional with a character limit (~300) and purpose ('personalized message'). This goes beyond the schema's basic types, though it doesn't detail format constraints (e.g., URL-safe IDs) or validation rules.

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 action ('Send a connection request') and target resource ('to a LinkedIn profile'), with specific verb+resource pairing. It distinguishes this from sibling tools like 'send_message' (for messaging existing connections) or 'reply_invitation' (for responding to incoming requests), making the purpose unambiguous.

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 provides clear context for when to use this tool (sending connection requests) and includes a WARNING about LinkedIn's bot detection and rate limits, which implicitly guides responsible usage. However, it does not explicitly state when NOT to use it or name specific alternatives among siblings (e.g., 'send_message' for existing connections), keeping it from a perfect score.

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