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benmonopoli

Greenhouse MCP

by benmonopoli

batch_read_resumes

Download and extract full resume text for multiple candidate IDs, using each candidate's most recent resume to reveal career trajectory, scope, and skills missing from structured data.

Instructions

Download and extract resume text for a list of candidates. Read-only.

Use after narrowing candidates with other sourcing tools. Pass candidate_ids from search_pipeline_candidates or scan_all_candidates. Uses each candidate's most recent resume across all their applications. Full resume text reveals career trajectory, scope of work, and skills that structured data doesn't capture.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
candidate_idsYesCandidate IDs to fetch resumes for
max_candidatesNoMaximum resumes to download

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose two meaningful traits: the operation is 'Read-only' and it selects each candidate's most recent resume across all applications. It does not cover rate limits, permissions, or failure behavior for large batches, so it stops short of full disclosure.

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?

Four short sentences, front-loaded with the verb and read-only note, then usage, then behavior. The final sentence justifies why the tool is worth calling rather than padding.

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

Completeness4/5

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

An output schema exists, so return values need no explanation, and the description covers purpose, preconditions, and resume-selection semantics. It omits auth/permission requirements and any limits on batch size behavior, a minor gap for a batch download tool with no annotations.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds real meaning beyond the schema by stating where candidate_ids should originate (search_pipeline_candidates or scan_all_candidates), which guides correct invocation. It says nothing extra about max_candidates, which the schema already documents.

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?

States a specific verb pair (download and extract) and resource (resume text) scoped to 'a list of candidates,' which distinguishes it from the singular read_candidate_resume sibling. An agent can tell what it produces without opening the schema.

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?

Explicitly says to use it 'after narrowing candidates with other sourcing tools' and names the two siblings that produce valid candidate_ids (search_pipeline_candidates, scan_all_candidates). This is a clear precondition plus a routing rule, not vague guidance.

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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