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Jing-yilin

LinkedIn MCP Server

by Jing-yilin

search_groups

Find LinkedIn groups by keywords, retrieve cleaned data in TOON format, and save results to specified directories for analysis.

Instructions

Search LinkedIn groups. Returns cleaned data in TOON format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchYesKeywords to search
pageNoPage number
save_dirNoDirectory to save cleaned JSON data
max_itemsNoMaximum results (default: 10)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions that data is 'cleaned' and returned in 'TOON format', which adds some behavioral context beyond basic search functionality. However, it lacks details on permissions, rate limits, pagination behavior (beyond the 'page' parameter), or what 'cleaned' entails, leaving gaps for a tool with no annotation coverage.

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, efficient sentence with zero waste. It front-loads the core purpose and includes key output details, making it appropriately sized and easy to parse.

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

Completeness3/5

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

Given no annotations and no output schema, the description is minimal but covers the basic purpose and output format. It lacks details on behavioral traits, error handling, or comprehensive usage guidelines, which are needed for a search tool with multiple parameters. It's adequate but has clear gaps in completeness.

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 fully documents all parameters. The description does not add any meaning beyond the schema, such as explaining the 'TOON format' in relation to parameters or providing usage examples. Baseline 3 is appropriate as the schema handles 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 verb ('Search') and resource ('LinkedIn groups'), and specifies the output format ('TOON format'). It distinguishes from siblings by focusing on groups rather than companies, jobs, posts, or profiles, though it doesn't explicitly contrast with other search tools like search_companies or search_profiles.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, context for searching groups, or differentiate from sibling tools like get_group (which might fetch a specific group) or other search tools. Usage is implied by the name but not explicitly stated.

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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