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send_connection_request

Send LinkedIn connection requests to users via profile URLs, optionally including personalized messages to increase acceptance rates.

Instructions

Send a LinkedIn connection request to a user, with an optional personalised note (max 300 characters).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profile_urlYesLinkedIn profile URL of the person to connect with
noteNoOptional personalised message to include with the request (max 300 chars)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the action is to 'send a connection request' but lacks critical behavioral details: it does not specify if this is a one-time action, potential rate limits, success/failure conditions, or what happens if a request already exists. The description is minimal and misses key operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It is front-loaded with the core action and includes only essential details (optional note with limit). Every part earns its place, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a write operation (sending a connection request) with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits (e.g., idempotency, error handling), expected outcomes, or integration context. For a mutation tool, this minimal description does not provide sufficient context for reliable agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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_url and note) fully. The description adds marginal value by reiterating the note's optionality and character limit, but does not provide additional semantics beyond what the schema specifies. Baseline score of 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

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 LinkedIn connection request') and the resource ('to a user'), distinguishing it from sibling tools like get_connections or get_profile. It explicitly mentions the optional personalized note with character limit, making the purpose unambiguous and distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., authentication, LinkedIn account status), nor does it differentiate from similar actions like messaging or other connection-related tools. Usage context is implied but not explicitly stated.

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

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