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by io.github.social-freak-ltd
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Resolve LinkedIn organization

linkedin_live_organization_resolve_v2
Read-only

Resolve a LinkedIn organization slug to an organization id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesLinkedIn organization slug. Not a person handle.
trimNoIgnored if this tool does not support it.
limitNoIgnored if this tool does not support it.
offsetNoIgnored if this tool does not support it.
contextYesDescribe the user's underlying goal in one sentence — not the tool you are calling.
pageSizeNoIgnored if this tool does not support it.
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
maxResultsNoIgnored if this tool does not support it.
max_resultsNoIgnored if this tool does not support it.
conversation_idNoEcho the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changed
    • addedInput schema / properties / limit
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Ignored if this tool does not support it."
+}
    • addedInput schema / properties / maxResults
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Ignored if this tool does not support it."
+}
    • addedInput schema / properties / max_results
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Ignored if this tool does not support it."
+}
    • addedInput schema / properties / offset
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Ignored if this tool does not support it."
+}
    • addedInput schema / properties / pageSize
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Ignored if this tool does not support it."
+}
    • removedInput schema / properties / slug / pattern
      Removed value: -"^[\\p{L}\\p{N}_.%-]+$"
    • addedInput schema / properties / trim
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Ignored if this tool does not support it."
+}
  2. Changed1 schema field changed
    • changedInput schema / properties / slug / description
      Previous value: -"LinkedIn profile handle or organization slug."New value: +"LinkedIn organization slug. Not a person handle."
  3. Added

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and openWorldHint, so the description does not need to cover mutation safety. It adds the slug-to-id resolution behavior, but does not disclose edge cases such as unresolved slugs, error behavior, or the exact format of the returned id. No contradiction with annotations.

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 sentence with no waste, front-loading the essential transformation and naming both input and output concepts immediately.

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 simple resolver with readOnly annotations and a fully documented schema, the description adequately communicates the contract: slug in, organization id out. It is slightly minimal given the large sibling set, but it does not omit anything critical for an agent to call it correctly.

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 all parameters. The tool description adds no additional parameter-level meaning, and the optional ignored parameters are self-described in the schema. Baseline 3 is appropriate.

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 states a specific verb ('Resolve'), a specific resource ('LinkedIn organization slug'), and the exact input-to-output transformation ('slug to ... organization id'). This clearly distinguishes it from sibling tools that retrieve organization details or search organizations.

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

Usage Guidelines3/5

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

The description implies when to use the tool: when you have a slug and need an organization id. However, it provides no explicit when-not-to-use guidance or pointers to alternatives like linkedin_live_organization_get_v2 or linkedin_live_organizations_search_v2, which would help disambiguate among the many LinkedIn siblings.

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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