Compass OS: Career

update linkedin

update_linkedin

DestructiveIdempotent

Save a new LinkedIn headline (at most 220 characters), About (at most 2600), or both, as Compass OS's saved copy that audit_linkedin scores, for the user to paste into LinkedIn. Use it to make audit_linkedin's fixes; for the Compass OS profile's own headline use update_profile, and for LinkedIn drafts in Brand studio use create_draft. Write only facts from the profile: every claim is checked against it, and unbacked ones are counted in the reply. It asks the user first, replaces only the part given, and never posts to LinkedIn. Returns the new audit score. Once it's saved, undo can put it back within 24 hours.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "update_linkedin"
  }
}

Input Schema

Name	Required	Description	Default
`about`	No	The new LinkedIn About section, at most 2600 characters; leave empty to keep the saved one
`headline`	No	The new LinkedIn headline, at most 220 characters; leave empty to keep the saved one

Output Schema

Name	Required	Description
`text`	Yes	The answer, or what was done, in plain words for the user: the same text as content
`undo`	No	On a saved write: its undo handle, for undo within 24 hours
`widget`	No	The card the host draws with it, e.g. "pipeline"; "confirm" means a write waits for the user's Yes and nothing is saved yet

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 5, 2026

addedOutput schema / properties / undo

Added value: +{
+  "description": "On a saved write: its undo handle, for undo within 24 hours",
+  "type": "string"
+}

Changed3 schema fields changedNov 4, 2026

addedInput schema / properties / about / description

Added value: +"The new LinkedIn About section, at most 2600 characters; leave empty to keep the saved one"

addedInput schema / properties / headline / description

Added value: +"The new LinkedIn headline, at most 220 characters; leave empty to keep the saved one"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": false,
+  "properties": {
+    "text": {
+      "description": "The answer, or what was done, in plain words for the user: the same text as content",
+      "type": "string"
+    },
+    "widget": {
+      "description": "The card the host draws with it, e.g. \"pipeline\"; \"confirm\" means a write waits for the user's Yes and nothing is saved yet",
+      "type": "string"
+    }
+  },
+  "required": [
+    "text"
+  ],
+  "type": "object"
+}

First observedNov 4, 2026

TDQS

A4.3/5.0

Behavior4/5

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

The annotations declare destructiveHint=true, idempotentHint=true, and openWorldHint=false, but the description adds substantial context beyond them: it asks the user for confirmation first, replaces only the part supplied, fact-checks claims against the profile and counts unbacked ones, returns the new audit score, and is undoable for 24 hours. The only gap is that it doesn't explain what 'destructive' means in practice when overwriting the previous saved copy.

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?

Purpose and character limits are front-loaded, then alternatives, then behavior. Four dense sentences carry a lot of information, though the character caps duplicate the schema and could be trimmed to tighten the opening.

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

Completeness4/5

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

For a two-optional-parameter write with an output schema, the definition covers confirmation, partial replacement, fact-checking, side-effect scope, return value, and reversibility window, so an agent has enough to call it correctly. The only missing piece is what specifically gets overwritten when a previously saved copy exists.

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 coverage is 100% and the schema already documents both fields, including the 220/2600 character caps and 'leave empty to keep the saved one.' The description's character limits and partial-update phrasing therefore restate rather than extend the schema, so the baseline of 3 applies.

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 names a specific verb and resource ('Save a new LinkedIn headline ... or both, as Compass OS's saved copy') and immediately clarifies scope against siblings: 'for the Compass OS profile's own headline use update_profile, and for LinkedIn drafts in Brand studio use create_draft.' An agent can distinguish it from audit_linkedin, update_profile, and create_draft without opening any 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?

It states when to use it ('Use it to make audit_linkedin's fixes') and names the two most confusable alternatives with the exact condition that selects each. It also states a negative behavior ('never posts to LinkedIn'), removing the most likely misuse.

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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