Placed MCP Server

get_company_salary_data

Retrieve salary ranges for any role at a company. Provide company name and position; location is optional for accuracy.

Instructions

Get salary ranges for a specific role at a company.

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_name": "<company_name>",
      "position": "<position>"
    },
    "name": "get_company_salary_data"
  }
}

Input Schema

Name	Required	Description
`company_name`	Yes	Company name
`position`	Yes	Job title/position
`location`	No	Location (optional)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0May 8, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. While it implies a read-only operation ('Get'), it does not mention whether the data is real-time or cached, what permissions are needed, or the format of the salary ranges (e.g., min/max/median). The behavior is only superficially described.

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 sentence with no unnecessary words. It effectively communicates the core purpose and is front-loaded with the key information. Every word earns its place, making it highly concise.

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

Completeness2/5

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

Given the absence of an output schema and annotations, the description is insufficient. It does not specify what 'salary ranges' includes (e.g., percentiles, average), how the data is sourced, or whether the result is a single range or multiple. The tool interacts with a significant domain (salary data), and the description lacks necessary context for the agent.

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%, so the baseline is 3. The description adds no extra meaning beyond what the parameter descriptions already provide (e.g., 'Company name', 'Job title/position', 'Location (optional)'). The description does not clarify how the location parameter affects results or the format of the output.

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 clearly states the verb 'Get' and the object 'salary ranges for a specific role at a company.' It is specific enough to distinguish from the sibling 'get_market_comp' which likely provides market-wide data. However, it does not explicitly differentiate between them, and the scope (single company vs market) is inferred.

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?

The description provides no guidance on when to use this tool versus alternatives like 'get_market_comp'. It does not mention any prerequisites, limitations, or context for usage. The agent is left to infer that this tool is for company-specific data, but no explicit advice is given.

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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