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Glama

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

by io.rtkmotion

get_robotarget

Multi-robot joint trajectories (NPZ) for sim_to_real_retargeting or imitation_learning. Platforms: Unitree G1 (43 DOF: 29 body + 14 hand), Unitree H1 (19 DOF), Apptronik Apollo (32 DOF) — specify via robot= param. MoveIt/ROS and Isaac Sim compatible, 60 fps, latency <500ms. Pay $15 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_robotarget.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
robotNoTarget robot platform: 'g1' (Unitree, 43 DOF = 29 body + 14 hand), 'h1' (Unitree, 19 DOF), or 'apollo' (Apptronik, 32 DOF). Defaults to 'g1'. Future platforms appear in the lesson's files.robotarget.robots list.
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 $15 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. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / robot / description
      Previous value: -"Target robot platform: 'g1' (Unitree, 24 DOF) or 'h1' (Unitree, 19 DOF). Defaults to 'g1'. Future platforms appear in the lesson's files.robotarget.robots list."New value: +"Target robot platform: 'g1' (Unitree, 43 DOF = 29 body + 14 hand), 'h1' (Unitree, 19 DOF), or 'apollo' (Apptronik, 32 DOF). Defaults to 'g1'. Future platforms appear in the lesson's files.robotarget.robots list."
  2. 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"
+}
  3. Changed2 schema fields changed
    • changedInput schema / properties / payment_tx / description
      Previous value: -"Transaction hash proving payment of $15 USD to the RTK wallet"New value: +"USDC transaction hash. Send $15 USDC on Base to 0x6C11F8a21f7ca922F483Ed21C3b6c2d9B305B10C, then pass tx hash here."
    • changedInput schema / properties / robot / description
      Previous value: -"Target robot platform (e.g. 'g1'). Defaults to 'g1'. Must be one of the platforms listed in the lesson's files.robotarget.robots."New value: +"Target robot platform: 'g1' (Unitree, 24 DOF) or 'h1' (Unitree, 19 DOF). Defaults to 'g1'. Future platforms appear in the lesson's files.robotarget.robots list."
  4. Changed1 schema field changed
    • addedInput schema / properties / robot
      Added value: +{
+  "description": "Target robot platform (e.g. 'g1'). Defaults to 'g1'. Must be one of the platforms listed in the lesson's files.robotarget.robots.",
+  "type": "string"
+}
  5. 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"
+]
  6. 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')"
  7. Added

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly discloses payment requirements (amount, chain, token, wallet, transaction hash), compatibility (MoveIt/ROS, Isaac Sim), performance (60 fps, latency <500ms), and DOF counts per robot. This is exemplary transparency for a paid retrieval tool.

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 dense yet well-structured, leading with purpose, then platforms, compatibility, performance, and payment details. Each sentence carries critical information without redundancy, making it efficient and easy to parse.

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?

Despite lacking an output schema, the description provides sufficient expectations: NPZ format, platform selection, performance metrics, and payment flow. It does not describe the exact delivery response (e.g., download link vs inline data), but the operational context is largely complete for an agent to decide whether and how to invoke the tool.

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 coverage is 100%, but the description adds meaning beyond the schema by explicitly instructing how to use the robot parameter ('specify via robot= param') and payment_tx parameter ('pass tx hash as payment_tx'). It also mentions future platforms in a file path, offering extra context not present in the schema.

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 opens with what the tool returns ('Multi-robot joint trajectories (NPZ)') and its intended use cases ('sim_to_real_retargeting or imitation_learning'). It distinguishes itself from siblings by listing supported platforms and pointing to the cheaper trial alternative, get_trial_robotarget.

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?

It clearly states the use cases and gives an explicit alternative for a cheaper trial: 'Cheaper $0.25 trial sample: call get_trial_robotarget.' It does not enumerate all sibling exclusions, but the context of when to use this tool vs the trial is clear.

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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TDQS

A4.1/5.0
Disambiguation4/5

Most tools are clearly separated by domain and tier (profile/sample/full), but get_mocap_sample and get_trial_bvh both return 5-second BVH samples and could be misselected. The rehab sample/profile tools are also close in evaluation purpose, though descriptions do help distinguish them.

Naming Consistency5/5

The data-access tools consistently follow get_<domain>_<variant>, and the only navigation tools are browse_catalog and search_catalog, which also use a predictable verb_noun pattern. There is no mixing of naming styles or inconsistent verb forms.

Tool Count3/5

With 21 tools, the set is borderline heavy for a data marketplace, especially since many tools are trial/sample/profile variants of the same paid products. The broad multi-domain scope justifies some size, but several variants could be consolidated without much loss of clarity.

Completeness4/5

The tools cover catalog browsing/searching, free profiles and samples, and paid full products across motion capture, rehab biomechanics, and threat/fleet intelligence. Minor gaps exist, such as no video trial and no generic fetch-any-catalog-item tool, but agents can work around these with the existing sample tools.

Resources