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outerwang

robot-motion-mcp

by outerwang

get_plan_status

Query a motion-planning run by run_id to check execution, path result, and validation status, including persistent outcomes across service restarts.

Instructions

Query a real planning run (run_id from start_motion_plan) with three separate dimensions: execution_status (PENDING/RUNNING/COMPLETED/FAILED/TIMEOUT/UNKNOWN - COMPLETED means the tool finished, not that a path was found), plan_result (PATH_FOUND/NO_CANDIDATE_WITHIN_BUDGET/ERROR/NOT_AVAILABLE) and validation_status. Status survives service restarts via persistent records; unverifiable outcomes are reported as UNKNOWN, never silently converted.

Input Schema

NameRequiredDescriptionDefault
run_idYes

Output Schema

NameRequiredDescriptionDefault
okYes
run_idYes
detailsYes
task_idNo
warningsNo
plan_resultNo
execution_statusYes
validation_statusNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries full behavioral burden and does unusually well: it discloses persistence across service restarts and that unverifiable outcomes surface as UNKNOWN rather than being silently converted. It omits whether the call blocks, whether polling is expected, and cost/latency, which matter for a status-query tool.

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-loaded with verb, resource, and the three query dimensions, and every clause earns its place — the COMPLETED clarification prevents a real misinterpretation. The dense parenthetical enum lists make it slightly heavy to parse but are not wasteful.

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 one-parameter status reader with an output schema, this is nearly sufficient: status semantics, persistence, and UNKNOWN handling are all covered. The remaining gap is operational — whether an agent should poll and how quickly a run transitions — which is left implicit.

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 coverage is 0%, so the description must compensate for the single run_id parameter; it does add provenance (obtained from start_motion_plan) but not format or validation rules. Much of the semantic detail it provides is about return-value enums, which the output schema already covers.

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 (Query) and resource (a planning run keyed by run_id) and names the sibling that produces the id (start_motion_plan), which immediately separates it from list_tasks and get_task_info. It also enumerates the three result dimensions, so an agent knows exactly what it will learn.

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 reference to 'run_id from start_motion_plan' establishes the calling context: use this after starting a plan. It gives no explicit exclusions (e.g., when to use list_tasks or get_task_info instead) and no polling guidance, so it stops short of full when/when-not guidance.

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