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Konfiguratorius - PC builder, part prices and compatibility

Estimate gaming performance

estimate_fps
Read-only

Estimate frame rates for a CPU + GPU pairing across popular games at a chosen resolution and quality preset, including 1% lows and which component is the bottleneck.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cpuYesCPU name, e.g. "Ryzen 5 7600".
gpuYesGPU name, e.g. "RTX 4070".
gameNoOne game; omit for a selection.
marketNoCountry market. Defaults to lt.
settingNoQuality preset. Defaults to high.
resolutionNoDefaults to 1080p.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / market / enum
      Previous value: -[
      -  "lt",
      -  "lv",
      -  "ee",
      -  "pl",
      -  "cz",
      -  "sk",
      -  "uk",
      -  "us",
      -  "si"
      -]New value: +[
      +  "lt",
      +  "lv",
      +  "ee",
      +  "pl",
      +  "cz",
      +  "sk",
      +  "uk",
      +  "us",
      +  "si",
      +  "de"
      +]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, and the description adds behavior by specifying what the estimate includes (frame rates, 1% lows, bottleneck). This is a non-mutating estimate tool, so no side-effect disclosure is needed; the description covers the result profile beyond the annotations.

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?

One sentence with no filler; the verb and core object are front-loaded, followed by the key output details and bottleneck. Every phrase carries information, making it easy to scan.

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 read-only estimator with 6 parameters and no output schema, the description names the core inputs and the output components (FPS, 1% lows, bottleneck), which is sufficient for invocation. A slightly more explicit return shape would make it fully complete, but the current text leaves no major selection or invocation gap.

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 baseline is 3. The description mentions CPU+GPU pairing, resolution, and quality preset, but it does not add meaning for game, market, setting, or resolution beyond the schema descriptions.

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 states a specific verb and resource ('Estimate frame rates for a CPU + GPU pairing') and adds useful scope (popular games, resolution, quality preset, 1% lows, bottleneck). This clearly separates it from siblings build_pc and check_compatibility, which are about construction and compatibility rather than performance estimation.

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?

The description clearly implies use when an agent needs estimated gaming performance for a CPU/GPU pairing. It does not explicitly name sibling alternatives or state when not to use them, but the context is unambiguous enough for selection.

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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