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Betaflight MCP

Betaflight MCP

by bvandevliet
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TypeScript
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get_feedforward_averaging

Retrieves the feedforward averaging setting that averages stick input samples to smooth RC link quantization.

Instructions

Get feedforward_averaging: Averages stick input samples before FF calculation to smooth out RC link quantization. OFF = no averaging (snappiest); 4_POINT = heaviest smoothing. [UINT8, default: 2_POINT]

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0-alpha

TDQS

A4.2/5.0
Behavior4/5

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

Discloses behavioral context: smoothing effect, possible settings (OFF, 4_POINT, default 2_POINT), and the trade-off between snappiness and smoothing. No annotations exist, so the description provides useful transparency beyond the name.

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?

Extremely concise: three short segments covering purpose, effect description, value enumeration, and default. Front-loaded with the action and purpose. No unnecessary words.

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 parameter-free getter with no output schema or annotations, the description covers purpose, effect, values, and default. It doesn't specify the exact return format, but the options are clearly listed, making it functionally complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist, and schema coverage is 100% trivial. The description adds value by explaining the meaning and options of the returned value, which is effectively the 'parameter' being queried.

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?

Clearly states the tool retrieves the feedforward averaging setting, explains its purpose (smoothing RC link quantization), and lists possible values with effects. Distinguishes from sibling tools by focusing on this specific parameter.

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?

Describes the effect of each value (snappiest vs. heaviest smoothing) but does not explicitly guide when to use this tool over other get_feedforward_* siblings or when to choose a particular value.

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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