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RTK Motion — Motion Capture, Biomechanics, Threat & Fleet Intelligence

get_bvh

BVH skeletal animation for robotic_grappling_training or imitation_learning. 60 fps, 56-joint hierarchy with 3-segment finger chains, latency <500ms. Pay $10 USDC on Base (chain 8453, USDC 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913) to RTK wallet 0x6C11F8a21f7ca922F483Ed21C3b6c2d9B305B10C; pass tx hash as payment_tx. Eth/Solana: /.well-known/x402. Cheaper $0.25 trial sample: call get_trial_bvh.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subjectYesSubject name (e.g. 'subject_1' or 'subject_2')
x_paymentNoPreferred (x402 exact / gasless): base64 X-PAYMENT payload — a signed EIP-3009 transferWithAuthorization for this tool's USDC price to our wallet. Redeemable only by its signer; no gas needed.
payment_txNoUSDC transaction hash. Send $10 USDC on Base to 0x6C11F8a21f7ca922F483Ed21C3b6c2d9B305B10C, then pass tx hash here.
lesson_pathNoLesson path, e.g. 'BJJ/Training/KimuraFromSideControl/Lesson001'. Defaults to first available lesson.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / x_payment
      Added value: +{
      +  "description": "Preferred (x402 exact / gasless): base64 X-PAYMENT payload — a signed EIP-3009 transferWithAuthorization for this tool's USDC price to our wallet. Redeemable only by its signer; no gas needed.",
      +  "type": "string"
      +}
  2. Changed1 schema field changed
    • changedInput schema / properties / payment_tx / description
      Previous value: -"Transaction hash proving payment of $10 USD to the RTK wallet"New value: +"USDC transaction hash. Send $10 USDC on Base to 0x6C11F8a21f7ca922F483Ed21C3b6c2d9B305B10C, then pass tx hash here."
  3. Changed3 schema fields changed
    • removedInput schema / properties / competitor
      Removed value: -{
      -  "description": "Competitor name (e.g. 'Professor' or 'Student')",
      -  "type": "string"
      -}
    • addedInput schema / properties / subject
      Added value: +{
      +  "description": "Subject name (e.g. 'subject_1' or 'subject_2')",
      +  "type": "string"
      +}
    • changedInput schema / required
      Previous value: -[
      -  "competitor"
      -]New value: +[
      +  "subject"
      +]
  4. Changed1 schema field changed
    • changedInput schema / properties / competitor / description
      Previous value: -"Competitor name (e.g. 'Boca' or 'Thane')"New value: +"Competitor name (e.g. 'Professor' or 'Student')"
  5. Changed3 schema fields changed
    • changedInput schema / properties / competitor / description
      Previous value: -"Competitor name — 'Boca' or 'Thane'"New value: +"Competitor name (e.g. 'Boca' or 'Thane')"
    • removedInput schema / properties / competitor / enum
      Removed value: -[
      -  "Boca",
      -  "Thane"
      -]
    • addedInput schema / properties / lesson_path
      Added value: +{
      +  "description": "Lesson path, e.g. 'BJJ/Training/KimuraFromSideControl/Lesson001'. Defaults to first available lesson.",
      +  "type": "string"
      +}
  6. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses performance specs (60 fps, 56-joint hierarchy, latency), payment requirements (USDC amount, chain, wallet, tx hash), and alternative payment methods (x402). It lacks error/failure behavior, but substantial behavioral context is present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but efficient, with each segment covering purpose/specs, payment, or trial alternative. It is front-loaded with the main purpose, though the payment details make it somewhat lengthy.

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?

The tool is complex with payment requirements and multiple parameters. The description thoroughly covers purpose, technical specifications, payment instructions, and alternative access. It doesn't describe the response format, but given the tool's nature, the BVH return is implied. Overall, robust for its complexity.

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?

Schema covers all parameters with descriptions, setting a baseline of 3. The description adds value by linking payment_tx to the $10 USDC payment, explaining x_payment via x402, and mentioning lesson_path defaults, going beyond schema details.

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 'BVH skeletal animation for robotic_grappling_training or imitation_learning', clearly identifying the tool's output and use cases. It also distinguishes itself by referencing the cheaper trial alternative, get_trial_bvh, differentiating from siblings.

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 explicitly names get_trial_bvh as a cheaper trial sample, providing a direct alternative and when-to-use signal. It doesn't compare with other siblings like get_mocap_sample, but the specified use case gives clear context for when this tool is appropriate.

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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