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Jing-yilin

LinkedIn MCP Server

by Jing-yilin

get_group

Retrieve LinkedIn group details including members, discussions, and metadata. Extracts structured data from group URLs or IDs for analysis and storage.

Instructions

Get LinkedIn group information. Returns cleaned data in TOON format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoLinkedIn group URL
groupIdNoLinkedIn group ID
save_dirNoDirectory to save cleaned JSON data
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'Returns cleaned data in TOON format,' which adds some behavioral context about output formatting. However, it lacks critical details: authentication requirements, rate limits, error handling, or what 'cleaned data' entails. For a tool with no annotations, this is insufficient.

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 concise with two sentences that are front-loaded: the first states the purpose, and the second adds behavioral context. There's no wasted text, but it could be slightly more structured (e.g., separating usage notes).

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?

Given no annotations, no output schema, and 3 parameters, the description is incomplete. It mentions output format but doesn't explain what 'TOON format' is or provide examples. For a tool that returns data, more context on response structure and behavior is needed to be fully helpful to an agent.

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 three parameters (url, groupId, save_dir). The description adds no additional meaning about parameters beyond what's in the schema. It implies parameters are optional (since none are required) but doesn't clarify usage. Baseline 3 is appropriate when schema does the heavy lifting.

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 clearly states the tool's purpose: 'Get LinkedIn group information' specifies the verb (get) and resource (LinkedIn group). It distinguishes from siblings like 'search_groups' by focusing on retrieval of specific group data rather than searching. However, it doesn't explicitly contrast with all siblings, so it's not 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to use 'get_group' versus 'search_groups' or other sibling tools, nor does it specify prerequisites or exclusions. The agent must infer usage from the name alone.

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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