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Query the navigation mesh

navmesh_query
Read-only

Query the navigation mesh used by AI pathfinding to summarize faces, identify faces at positions, test route connectivity, check straight-line walkability, and inspect face groups.

Instructions

Read-only queries with the engine's own path finding (the one AI agents use) on the navigation mesh of the scene open in the editor, or of the running mission (needs the bridge): summary (face count, face ids with their face counts, CRC), at (the face under a position: index, id, island, center, open edges), path (whether two positions are connected, path length against the straight distance, corner points), line (whether a straight move from a position stays on the mesh), group (faces with one id: count and extent). Use mission action=walk to prove a route with a real agent.

Input Schema

NameRequiredDescriptionDefault
idNogroup: face id (face group index).
toNopath/line: end position.
fromNopath/line: start position.
actionNoQuery (default summary).
radiusNopath/line: agent radius in meters (default 0.3).
positionNoat: position to look up.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds meaningful context beyond that: the bridge prerequisite for mission queries and a detailed enumeration of what each action returns. No output schema exists, so this return-value disclosure carries real weight.

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?

It is a single dense, run-on sentence but front-loads the core idea (read-only queries using the engine's own pathfinding) before the action list. Nearly every clause earns its place; only the length makes it slightly heavy.

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 six-parameter, read-only tool with no output schema, the description covers the modes, their outputs, and the bridge prerequisite. It leaves minor gaps such as return format or coordinate conventions, but nothing essential to correct invocation is missing.

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%, so the schema already documents all six parameters. The description still adds value by mapping parameters to actions (at uses position, path/line use from/to/radius, group uses id), which the raw schema does not group this way.

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 (navigation mesh) and enumerates the five query modes with their exact return fields. It clearly distinguishes itself from the mission tool by pointing to 'mission action=walk' for real-agent route proof.

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?

Gives concrete context: queries run on the editor scene or the running mission (needs the bridge), and routes the agent to 'mission action=walk' to prove a route with a real agent. It lacks explicit when-not conditions, but the alternative and its selection criterion are stated.

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