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mperkhou

Career Agent Workbench MCP Server

by mperkhou

get_linkedin_job_raw_payload

Retrieve a bounded public LinkedIn job detail payload by providing a job ID or URL, enabling access to raw job data for matching and analysis.

Instructions

Get one bounded in-memory public LinkedIn detail payload.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_id_or_urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions 'bounded in-memory public', hinting at caching or limits, but does not clarify the behavior, failure modes, authentication requirements, or output structure. The term 'bounded' is ambiguous.

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?

The description is a single, short sentence, making it concise, but the ambiguous phrasing 'bounded in-memory public' reduces clarity. It is not overly verbose, yet it under-specifies important details, leaving the description less effective than it could be.

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 a single parameter and an output schema, the description is too sparse. It offers no context on when to use this over alternatives, what 'raw payload' entails, or any limitations. The presence of sibling tools and output schema does not mitigate the lack of clear purpose and usage guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter, job_id_or_url, is somewhat self-explanatory from its name, but the description does not elaborate on accepted formats (e.g., numeric ID vs full URL) or usage. With 0% schema description coverage, the description should compensate, but it remains silent on parameter semantics.

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 uses the verb 'Get' and identifies the resource as a 'raw payload', clearly indicating its purpose. It distinguishes from sibling tools like get_linkedin_job_details by emphasizing 'raw payload' and 'in-memory', but the term 'bounded' is vague and not fully explained.

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 such as search_linkedin_jobs, get_linkedin_job_details, or find_matching_linkedin_jobs. The description only states what it does, with no context or exclusions.

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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