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100Hires MCP Server

100Hires MCP Server

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by 100Hires
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TypeScript
Remote

hires_get_ai_score

Retrieve the structured AI score for an application, including per-criterion scores, justifications, and follow-up questions. Returns null if the application is not yet scored.

Instructions

Get the structured AI score for an application, including per-criterion scores, justifications, and follow-up questions. Returns null score if the application has not been AI-scored.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "hires_get_ai_score"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesApplication ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.3

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses a key edge case (returns null if not AI-scored) and describes the response components. It does not explicitly state read-only semantics, authentication needs, or error conditions, but 'get' implies read-only and the null behavior adds meaningful insight.

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 concise sentences that front-load the main purpose and add a critical behavioral note. No redundant information or filler.

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 simple, single-parameter getter with no output schema, the description adequately explains what the tool returns (per-criterion scores, justifications, follow-up questions) and the null fallback case. It covers the essential behavior without unnecessary detail.

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% for the single parameter (id) with description 'Application ID.' The tool description adds no additional parameter semantics, so the baseline score of 3 applies.

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?

Description clearly states the tool retrieves a structured AI score for an application, listing specific components (per-criterion scores, justifications, follow-up questions). It distinguishes itself from general application getters like hires_get_application by focusing on the AI score specifically.

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?

Provides clear context: use this to get the AI score of an application. The null-score note implies the tool is for applications that have been AI-scored, but it does not explicitly mention alternatives or when not to use it. Lacks explicit exclusions but the purpose is evident.

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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