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 communicates the tool's limitations (daily quota, warm-up, business hours, jitter) and the dry_run mode for testing. This helps the agent understand side effects and constraints. A minor gap is the lack of details on idempotency or error states, but overall strong transparency.

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 extremely concise with only two sentences, yet it packs essential information: the action, optional note, constraints, and dry_run option. It fronts the core verb and resource, making it easy to parse. No unnecessary words or redundancy.

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 lack of output schema and annotations, the description does a good job covering the key aspects: purpose, parameters, constraints, and preview mode. It is complete enough for an agent to understand when and how to call the tool. However, it omits details on the response (e.g., success/failure, request ID) which could enhance completeness for an agent reasoning about outcomes.

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?

The input schema covers 67% of parameters with descriptions (public_id and note). The description adds value by explaining the dry_run parameter's purpose ('preview without sending') which is not described in the schema. It also reinforces the note's purpose as 'personalized note'. The schema already describes the required fields adequately, so the description's contribution is moderate.

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's action: sending a connection request to a LinkedIn member. It distinguishes itself from sibling tools like send_message or accept_invitation by specifying the exact action and optional note. The verb 'send' and resource 'connection request' are specific and 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 mentions important constraints (daily quota, warm-up ramp, business hours, jitter) and the dry_run option for preview, which provides context for when to use the tool. However, it does not explicitly state when to use this tool versus alternatives like send_message or withdraw_invitation, leaving the agent to infer usage via its own knowledge of LinkedIn actions.

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