eSportCalc FPS Sensitivity & Pro Settings Lab

lookup_pro_player_settings

Retrieve publicly reported mouse DPI, sensitivity, eDPI, cm/360 turn distance, crosshair code, and hardware snapshot for competitive FPS pros.

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": {
      "player_slug": "<player_slug>"
    },
    "name": "lookup_pro_player_settings"
  }
}

Input Schema

Name	Required	Description	Default
`player_slug`	Yes	Pro player slug (e.g. tenz, s1mple, donk, zywoo, aspas, proper)

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 11, 2026

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully signals provenance with "publicly reported," hinting values may be missing or approximate for some pros, and the read-only nature is implicit in "Retrieve." It does not say what happens for an unknown player_slug or whether fields can be null.

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?

A single front-loaded sentence with no filler; the enumerated field list doubles as a compact return-value preview. Nothing could be removed without losing information.

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 one-parameter read tool with no output schema, enumerating the returned fields is exactly the right compensation. The remaining gap is error and missing-data behavior for unrecognized slugs, which is minor but real given the "publicly reported" data source.

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 the single parameter is already documented with concrete slug examples (tenz, s1mple, donk), so the schema does the heavy lifting. The description adds only the scoping phrase "competitive FPS pros," which tells the agent which slugs are valid but nothing about format or matching behavior.

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?

States a specific verb ("Retrieve") and a precisely enumerated resource: DPI, sensitivity, eDPI, cm/360, crosshair code, and hardware for competitive FPS pros. An agent can distinguish this lookup from the sibling convert_fps_sensitivity, but the description never names that sibling, so differentiation is inferred rather than stated.

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 when-to-use sentence, no prerequisite, and no routing to convert_fps_sensitivity for computing derived values. Usage is only implied by the purpose statement itself, leaving the agent to guess whether this tool also performs conversions.

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

All eSportCalc FPS Sensitivity & Pro Settings Lab tools Inspect

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