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Social Fetch

by io.github.social-freak-ltd
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Get LinkedIn activity

linkedin_live_activity_get_v2
Read-only

Get a LinkedIn activity by id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
activityIdYesLinkedIn activity ID.
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. Changed6 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."
+}
    • addedInput schema / properties / trim
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "number"
+    },
+    {
+      "type": "boolean"
+    }
+  ],
+  "description": "Ignored if this tool does not support it."
+}
  2. Added

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds no further behavioral context—no mention of return format, potential errors, rate limits, or any caveats. Since the description carries little beyond the annotations, it earns a low score.

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?

The description is a single concise sentence with no fluff, front-loading the action and resource. It is appropriately short for a simple get-by-id tool, though it could afford a bit more detail without becoming verbose. It earns a 4 for efficiency and clarity.

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?

For a tool with 10 parameters, no output schema, and numerous sibling tools, the description is severely under-specified. It doesn't explain how to obtain an activity ID, what the response contains, or any operational context. Given the complexity and lack of output schema, the description leaves the agent with many unknowns.

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 baseline is 3. The description itself adds no parameter-level detail, and while several schema descriptions are generic placeholders ('Ignored if this tool does not support it'), the description does not compensate for those gaps. It neither enhances nor detracts from the schema, so it stays at baseline.

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

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear action ('Get') and resource ('a LinkedIn activity by id'), which distinguishes it from sibling tools like linkedin_live_activity_comments_v2 and linkedin_live_activity_reactions_v2. However, it doesn't define what an 'activity' is (e.g., a post, a comment), leaving some ambiguity, so it falls short of a perfect 5.

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?

There is no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing an activity ID, nor does it contrast with any of the many sibling LinkedIn tools. The implied use case (have an activity ID, want its details) is not explicit, leaving the agent to infer.

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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