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by io.github.MikhailSagalaev
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xray_generate_dorks

Generate targeted Boolean search queries (Google Dorks) to locate engineering leaders, team leads, and hiring managers for a specific company and role across LinkedIn, Telegram, Habr, and GitHub.

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": {
      "company": "<company>"
    },
    "name": "xray_generate_dorks"
  }
}

Input Schema

NameRequiredDescriptionDefault
roleNoRole or job title, e.g. "Senior Go Developer", "DevOps Engineer"
skillsNoRelevant tech skills, e.g. ["Go", "Kafka"]
companyYesCompany name, e.g. "Ozon", "Skyeng", "Acme"

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden and does clarify that the tool generates query strings rather than executing searches directly. It still omits the return format, whether queries are executed externally, and any side-effect or rate-limit considerations.

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 a single, front-loaded sentence with no wasted words. It efficiently communicates the action, output type, target audience, and platforms.

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?

The tool has three parameters with full schema coverage and no annotations or output schema. The description covers purpose and scope but does not describe the expected return shape, such as whether it returns one query or multiple platform-specific dorks.

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 description coverage is 100%, so the schema already documents company, role, and skills parameters thoroughly. The description mentions company, role, and platform scope but adds no syntax or formatting details beyond what the schema provides, making baseline 3 appropriate.

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

Purpose4/5

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

The description states a specific verb and resource: generating targeted Boolean search queries (Google Dorks). It also names the intended targets and platforms, making the purpose clear, but it does not explicitly differentiate itself from siblings such as search_leads or save_search.

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

Usage Guidelines3/5

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

The phrase 'to locate engineering leaders, team leads, and hiring managers for a specific company and role' implies the intended use case. However, there is no explicit guidance on when to choose this tool over alternatives like search_leads, or when not to use it.

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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