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ingyukoh

MCP Recruiting Agent

by ingyukoh

get_policy

Retrieve official hiring policy text for topics like EEO, screening, data privacy, and AI use. Access clear guidelines to keep recruiting workflows compliant and informed.

Instructions

Get hiring policy text. Topics: eeo, screening, data_privacy, ai_use.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral context on its own. It communicates read-only intent through the verb 'Get', but it does not state whether topics are exact enum values, what happens for invalid topics, whether all topics are available, or any other behavioral constraints. The list of topics gives some context but leaves important behavior unspecified.

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 two short sentences with no filler. It front-loads the core action and then enumerates the relevant topics, making it easy to scan and process.

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

Completeness3/5

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

Given the simple one-parameter shape and the absence of an output schema, the description sufficiently identifies the resource and valid topics. However, it omits confirmation that the topic listing is exhaustive or that values must match exactly, and it provides no detail about the response format or potential error conditions, leaving a few practical gaps.

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?

The schema provides only 'topic' as a string with no description and no enum, so the description adds meaningful value by listing the allowed topics: eeo, screening, data_privacy, and ai_use. This compensates for the 0% schema coverage, though it could be stronger by explicitly stating that these are exact permitted values.

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 uses a specific verb and resource ('Get hiring policy text') and enumerates the available topics, making the tool's function immediately clear. It is clearly distinct from the sibling tools, which all concern jobs or candidates rather than policy content.

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?

There is no explicit guidance about when to use this tool versus alternatives, and no mention of which topics should be selected under which circumstances. The description merely implies the tool is for retrieving policy text, leaving usage decisions entirely to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.