Skip to main content
Glama

runtime_tree

Read-only

Inspect the live scene tree of a running Godot game, including nodes created at runtime. Use returned paths or object IDs with runtime_inspect for debugging.

Instructions

The live scene tree of a running game, including nodes created at runtime. Returns: nested nodes with name, type (script class_name or path when scripted), path, object_id and visibility. Use the path or object_id with runtime_inspect.

Input Schema

NameRequiredDescriptionDefault
pathNoOnly this subtree, e.g. '/root/Main/Enemies'
max_depthNoLevels below the start to include (default 8)
session_idNoSession from runtime_run. Required only when several games run.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine value beyond that: it discloses that runtime-created nodes are included and enumerates the returned fields (name, type, path, object_id, visibility), which matters because there is no output schema. It does not address depth/pagination behavior of large trees, which is a minor gap.

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?

Three tight sentences with no filler: purpose and scope first, return shape second, next-step handoff third. Every sentence carries information and the key details are front-loaded.

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?

With no output schema, the description takes on the burden of explaining return values and does so concretely (field list plus type semantics for scripted nodes). Combined with a fully documented 3-parameter schema, it is close to complete; only tree-size/depth handling and the session-ambiguity condition in prose are missing.

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 description coverage is 100%, so the schema already documents path, max_depth, and session_id including the default depth and the session condition. The description only echoes 'path or object_id' usage, adding nothing beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource and scope: 'the live scene tree of a running game, including nodes created at runtime,' which distinguishes it from sibling tree/state tools and clarifies it reflects runtime-created nodes, not just authored ones. It lacks an explicit verb, but the resource and scope are unambiguous enough for an agent to select it correctly.

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?

'Use the path or object_id with runtime_inspect' establishes the follow-up workflow with a specific sibling, which is useful routing. However, it does not say when to prefer this tool over alternatives like scene_state or runtime_status, and the session_id precondition ('required only when several games run') sits in the schema rather than being surfaced as usage context.

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