send_linkedin_message

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. While it states the tool sends a message, it doesn't describe what happens after sending (e.g., delivery confirmation, error handling), whether there are rate limits, authentication requirements beyond the listed parameters, or what constitutes a valid 'existing thread'. For a messaging 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 perfectly structured and concise: a clear purpose statement, followed by organized Args and Returns sections. Every sentence earns its place, with no redundant information. The front-loaded purpose statement immediately communicates the tool's function.

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 (7 required parameters, messaging operation) and the presence of an output schema (implied by 'Has output schema: true'), the description is moderately complete. The parameter documentation is thorough, but behavioral aspects are under-specified. The output schema existence means the description doesn't need to detail return values, but other operational context 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?

With 0% schema description coverage for all 7 required parameters, the description provides excellent compensation by listing all parameters with brief explanations in the Args section. Each parameter gets a clear label and basic semantic meaning (e.g., 'Message content to send', 'LinkedIn user ID of the recipient'). This adds substantial value beyond the bare schema.

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 LinkedIn message') and target ('to an existing thread'), providing a specific verb+resource combination. It distinguishes this from sibling tools like 'send_new_email' or 'send_email_reply' by specifying the LinkedIn platform context. However, it doesn't explicitly differentiate from potential similar messaging tools that might exist in the sibling list.

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 'to an existing thread' which provides some context about when to use it (not for starting new conversations), but offers no guidance on when to choose this tool versus alternatives like 'send_email_reply' or 'send_new_email'. There are no explicit when-not-to-use instructions or prerequisite information about required account connections.

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