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BACH-AI-Tools

LinkedIn Api8 MCP Server

get_given_recommendations

Retrieve all recommendations given by a LinkedIn profile. Use the start parameter to paginate through results, incrementing by 100 until you reach the total count.

Instructions

To scrape all recommendations from a profile, increase the start value to +100 for each request until you reach the total recommendations count. You can find the total recommendations count in the response

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesExample value: ryanroslansky
startNoExample value: 0
Behavior3/5

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

Discloses pagination behavior and the presence of a total count in responses. Does not mention error handling, rate limits, or consequences of invalid input. With no annotations, the description carries full burden but remains incomplete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence conveying purpose and usage. However, it is somewhat run-on and could be split for clarity. Front-loaded with action but slightly verbose.

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?

No output schema exists, so description should explain the response structure. It only mentions 'total recommendations count' but omits details about returned data, fields, or error formats. Insufficient for an agent to parse results.

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% with example values. The description adds context on how to use the 'start' parameter for pagination, but does not clarify data types or constraints beyond the schema examples.

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?

Description clearly states the tool scrapes recommendations from a profile and explains pagination. However, it does not explicitly differentiate from sibling 'get_received_recommendations', which might imply a different direction of recommendations.

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?

Provides specific pagination instructions on how to iterate through results. However, it lacks guidance on when not to use this tool or mention of alternative methods, such as using 'get_received_recommendations' if the direction varies.

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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