Linked API

endorse_person_skill

Endorses one skill by name on a 1st-degree connection's profile. Skill names are in the profile owner's language, regardless of your LinkedIn language. An already-endorsed skill counts as success and is never removed. Every success, including an existing endorsement, counts toward the stEndorsements limit. Use endorse_person_skills to select skills with patterns or endorse all skills. If this workflow is still running, do not retry this tool; retrying can count the same skill toward the stEndorsements limit again.

Linked API actions are queued into a cloud-browser workflow and may take several minutes. The server returns immediately after starting the workflow with {status: 'pending'|'running', pendingReason, workflowId, operationName, message}. To retrieve the final result, call get_workflow_result with the returned workflowId and operationName — it will long-poll until completion or the request budget elapses, then return either the final result or another in-progress snapshot. Do not retry the original tool while a workflow is still running; that creates duplicate queued work.

A pending workflow carries pendingReason: 'queued' means it is waiting its turn behind other work on the same account and will start within minutes. 'outsideWorkingHours' means the account has configured working hours and the workflow is parked until they reopen — possibly the next working day. In that case get_workflow_result returns immediately instead of polling, message states when the window opens, and you should report that to the user rather than looping.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "personUrl": "<personUrl>",
      "skillName": "<skillName>"
    },
    "name": "endorse_person_skill"
  }
}

Input Schema

Name	Required	Description	Default
`personUrl`	Yes	Public or hashed LinkedIn URL of your 1st-degree connection.
`skillName`	Yes	Exact skill name in the profile owner's language, up to 200 characters. Letter case and extra spaces are ignored. This is not a pattern.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 29, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Goes well beyond the readOnlyHint=false / openWorldHint=true annotations: it discloses that an existing endorsement counts as success and is never removed, that every success consumes the stEndorsements limit, and that the call is queued into a cloud-browser workflow returning a pending snapshot. Deduction only because the length of the shared workflow boilerplate dilutes the tool-specific behavioral facts rather than adding more of them.

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

Conciseness4/5

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

Tool-specific behavior is front-loaded in the first paragraph, with the generic async-workflow and pendingReason explanation following. That second half is largely reusable boilerplate duplicated across the server's tools, so it costs length without adding this tool's uniqueness, but nothing in it is irrelevant.

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

Completeness5/5

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

With no output schema, the description correctly covers the return shape (status/pendingReason/workflowId/operationName/message) and the exact follow-up call, get_workflow_result, needed to obtain the final result. An agent has everything required to invoke and then complete this operation.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3; the description earns a step above by clarifying that skillName is an exact name in the profile owner's language and explicitly is not a pattern, which is the key semantic distinction from endorse_person_skills. It does not add anything about personUrl beyond the schema.

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?

States a specific verb and resource (endorse one skill by name on a 1st-degree connection's profile) and immediately scopes it against the sibling endorse_person_skills, which handles patterns or all skills. An agent can pick between the two without opening either schema.

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

Usage Guidelines5/5

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

Explicitly names the alternative tool and the condition that selects it, plus an explicit prohibition on retrying while a workflow is running and an explanation of what to do instead. The only thing not covered is a precondition check on the personUrl, but conversion-path guidance is unusually thorough.

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

All Linked API tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.