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Workforce-Cloud-Tech

Recruit CRM MCP Server

Get Job Details

get_job_details
Read-only

Fetch full details for up to 10 Recruit CRM jobs by slug. Get complete job records, with partial failures reported in an errors array.

Instructions

Fetches full details for up to 10 Recruit CRM jobs in parallel by slug. Suitable for retrieving specific job records after slug resolution from search_jobs. Returns full Recruit CRM job payloads with partial results: failures are reported in the errors array with status_code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_slugsYesJob slugs to fetch. Max 10 per call. Duplicates are ignored.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobsYes
errorsYes
failed_countYes
requested_countYes
successful_countYes
Behavior5/5

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

While annotations already mark it as non-destructive/read-only, the description adds critical behavioral details: parallel fetching, partial results with an errors array, and status_code reporting for failures. This goes beyond the annotations and gives the agent an accurate model of success/failure behavior.

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?

Two sentences achieve high information density without waste. The first sentence states the core function and limits; the second adds the use case, result behavior, and error reporting. Information is front-loaded and every clause earns its place.

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

Completeness5/5

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

For a single-parameter read tool with an output schema, the description is complete: it explains the input (slugs), the workflow prerequisite (search_jobs), the parallelism and size limits, and the partial-failure semantics. No gap remains for an agent to safely invoke the tool.

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?

The schema provides 100% coverage of the single parameter (job_slugs) with constraints and duplicate-ignoring behavior. The description adds only contextual linkage to search_jobs, but no additional parameter-specific semantics beyond what the schema already offers. Baseline of 3 is appropriate given high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb ('fetches') and resource ('full details for up to 10 Recruit CRM jobs in parallel by slug'). It distinguishes from sibling search tools by specifying the exact entry point (slug) and scope (full details, specific records), making its purpose unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Suitable for retrieving specific job records after slug resolution from search_jobs', providing clear when-to-use context and pointing to the prerequisite tool. It also communicates the capacity limit (up to 10), helping agents decide when to batch or paginate.

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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