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outerwang

robot-motion-mcp

by outerwang

validate_motion

Report the independent-validation status bound to a run's candidate motion path, showing whether a strict validator has passed it or if it remains not run.

Instructions

Report the independent-validation status bound to a run's candidate path. For NEW local runs this is NOT_RUN until a scene-compatible strict validator is registered - planning success is never treated as PASS, and historical verdicts are never transferred to new paths. For frozen research-audit records the recorded verdict is reported verbatim, bound to the recorded path sha256 and input contract. run_id forms: local 'R-*' runs and historical records like 'rm_next_015_fr69b_transfer_expansion/Q1_RRT_E1' or '.../REF_T1_CM2B_P0'.

Input Schema

NameRequiredDescriptionDefault
run_idYes

Output Schema

NameRequiredDescriptionDefault
okYes
run_idYes
sourceNo
detailsNo
task_idNo
model_versionYes
validation_methodNo
validation_statusYes
evidence_referenceNo
candidate_path_hashNo
error_or_incomplete_reasonNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses that NEW runs return NOT_RUN, that planning success is never treated as PASS, and that verdicts are never transferred to new paths. It stops short of explicitly stating read-only/side-effect-free behavior, though 'Report' implies it.

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?

Front-loads the purpose, then layers result semantics and finally the run_id format. Dense but each sentence contributes; minor cost is the slightly run-on clause about sha256 binding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given an output schema exists (return values needn't be described), the description covers purpose, result semantics, and the required parameter's format. An agent has enough to invoke it correctly without further clarification.

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?

The schema provides 0% description coverage for run_id, so the description must compensate. It does, specifying accepted forms: local 'R-*' runs and historical record paths like 'rm_next_015_fr69b_transfer_expansion/Q1_RRT_E1' or '.../REF_T1_CM2B_P0'.

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?

States a specific verb ('Report') and precise resource ('the independent-validation status bound to a run's candidate path'). This clearly separates it from siblings like get_plan_status or get_experiment_report, which concern planning/report state rather than validation verdicts.

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?

Explains the meaning of results in two distinct scenarios (NEW local runs vs. frozen research-audit records), which implies when the output applies. However, it never explicitly routes the agent away from alternatives such as get_plan_status, leaving the when-to-use decision to inference.

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