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BACH-AI-Tools

Fresh Linkedin Profile Data MCP Server

Check Search Status

check_search_status

Get the status of a LinkedIn data search request using its request ID. See whether the search is pending, completed, or failed before retrieving results.

Instructions

Get the status of your search using the request_id given in step 1.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYesExample value: dd1b29063de8927b31fa523d36432b61

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.0.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations and no output schema, the description carries the full burden of behavioral disclosure. It only says 'get the status' and does not describe possible status values, whether the call is non-blocking, whether it can be polled, or what a successful response looks like.

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 filler or redundant phrasing. The key action and the required parameter are both mentioned immediately, making it easy to parse.

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?

The tool is simple but lacks an output schema, annotations, and any explanation of the status response. The reference to 'step 1' is vague and unexplained, and the description does not connect this tool to a specific search workflow given the many search-related siblings.

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%, so the schema fully documents request_id with an example. The description adds minor context by noting the ID is 'given in step 1', but it does not add format details or clarify what exactly the status response contains.

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 a specific verb ('get') and resource ('status of your search') and references the request_id used to retrieve that status. However, it does not distinguish itself from the closely named sibling 'check_company_search_status', leaving some ambiguity about which search workflow it applies to.

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 usage by saying the request_id comes from 'step 1', which gives some workflow context. It does not explicitly explain when to use this tool versus alternatives like check_company_search_status, nor does it mention any prerequisites or polling behavior.

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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