send_connection_request

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the action ('send a connection request') and a constraint (message length), but fails to disclose critical traits like rate limits, LinkedIn's connection request policies, whether this requires specific permissions, or what happens on success/failure (e.g., pending status, notifications). For a mutation tool with zero annotation coverage, this is a significant gap.

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 a single, efficient sentence that front-loads the core purpose and includes a key constraint. There is zero waste—every word earns its place by clarifying the tool's function and a practical limitation.

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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral aspects (e.g., LinkedIn's connection limits, response format), error handling, and does not compensate for the absence of structured safety or output details. For a tool that modifies external state, more context is needed.

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 schema already documents both parameters (profile_urn and message). The description adds minimal value beyond the schema by mentioning the message is 'optional' and has a 'max 300 characters' limit, but doesn't explain parameter interactions or provide additional context like URN format examples. Baseline 3 is appropriate when schema does the heavy lifting.

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 specific action ('send a connection request') and target ('to a LinkedIn member'), distinguishing it from siblings like 'send_message' (which sends messages to existing connections). It specifies the resource (LinkedIn member) and includes a key constraint (optional personalized message with max 300 characters).

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 implies usage for initiating connections on LinkedIn, but provides no explicit guidance on when to use this versus alternatives like 'send_message' (for existing connections) or prerequisites (e.g., needing a valid session). It mentions the optional message feature, which hints at context for personalization, but lacks clear when/when-not rules or named alternatives.

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