linkedin_get_connectionsList your LinkedIn connections (1st-degree). Returns name, headline, profile URL, and public identifier for each connection. Supports cursor-based pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of connections to return per page (1–100, default 50). | |
| cursor | No | Pagination cursor from a previous response. Omit for the first page. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly=true, idempotent=true, openWorld=true, and destructive=false, so the safety profile is covered. The description adds genuinely useful context beyond that: the exact fields returned (name, headline, profile URL, public identifier) and the cursor-based pagination model. It stops short of noting rate limits or auth requirements, but it clearly exceeds the annotation baseline.
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?
Three short sentences with zero filler: what it does, what it returns, and how pagination works. The most important information (the resource and its 1st-degree scope) is front-loaded.
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?
There is no output schema, but the description compensates by listing the returned fields and explaining the cursor-based pagination, so an agent knows what comes back and how to page. Combined with annotations covering the safety profile, this is nearly complete for a simple list tool; only error or empty-result behavior is unspecified.
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 both parameters (limit, cursor) are already fully documented in the schema. The description reinforces the cursor-pagination concept, which is minor added value, but adds no syntax or defaults beyond what the schema states. Baseline 3 is appropriate when the 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?
States a specific verb and resource ('List your LinkedIn connections') and scopes it precisely to 1st-degree connections, which distinguishes it from sibling tools like linkedin_get_shared_connections and linkedin_list_connection_requests. It does not explicitly name an alternative tool, but the 1st-degree qualifier makes the resource 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?
Usage is implied by the description (retrieve your own connection list), and the sibling set makes the intent fairly clear. However, there is no explicit when-to-use guidance or contrast with alternatives such as linkedin_search_people or linkedin_get_shared_connections, leaving routing to inference.
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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