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Comradery64

open-greenhouse-mcp

by Comradery64

bulk_tag

Tag multiple candidates at once by passing candidate IDs and a tag name. Automatically creates the tag if it doesn't exist, saving time on repetitive tagging tasks.

Instructions

Tag multiple candidates in one call. Write operation — rate-limited.

Users say "tag all the candidates from the hiring event." Pass candidate_ids from search or pipeline tools and a tag_name (created automatically if new). Processes sequentially with rate-limit delays.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tag_nameYesTag name to apply — created on-the-fly if it doesn't exist
candidate_idsYesCandidate IDs to tag — get from list_candidates or search

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that it is a write operation, is rate-limited, processes sequentially with delays, and auto-creates tags if new. This is strong behavioral disclosure beyond the schema, though it does not cover error handling or edge cases.

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 three sentences, front-loaded with the core action, then adds a practical usage example and rate-limit behavior. No wasted words; every sentence contributes useful context.

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?

For a simple 2-parameter tool with an output schema, the description covers the essential safety profile (write, rate-limited), usage context, and parameter sources. It could be more explicit about alternatives, but overall it is complete enough for an agent to select and invoke correctly.

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% and already explains both parameters, including the auto-creation of tags. The description adds minimal new semantic value by mentioning 'from search or pipeline tools,' but this largely duplicates the schema's 'get from list_candidates or search.' Baseline 3 is appropriate.

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 opens with 'Tag multiple candidates in one call,' which clearly states the verb, resource, and batch scope. It distinguishes itself from single-candidate tagging siblings like add_tag_to_candidate by emphasizing 'multiple' and 'bulk' behavior.

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

Usage Guidelines4/5

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

The description provides concrete usage context: 'Users say "tag all the candidates from the hiring event"' and instructs to pass candidate_ids from search or pipeline tools. It implicitly differentiates from single-tag tools but does not explicitly state when not to use it or name alternatives.

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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