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validate_state_tree

Destructive

Compile a StateTree asset in memory and report its errors and warnings without saving, so you can verify it before a saved compile.

Instructions

Compile a StateTree asset in memory and report its errors and warnings without saving: valid, compiled, error_count, warning_count and the messages. It still marks the package dirty and refreshes the compiled data in memory; compile_state_tree compiles and saves.

Returns: { tree_path, valid, compiled, error_count, warning_count, message_count, saved, errors: [{severity, message}], warnings: [{severity, message}], note }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tree_pathYesAsset path of the StateTree, e.g. "/Game/AI/ST_Guard".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.0
    • changedInput schema / properties / tree_path / description
      Previous value: -"Asset path."New value: +"Asset path of the StateTree, e.g. \"/Game/AI/ST_Guard\"."
  2. First observedv1.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations declare destructiveHint=true and readOnlyHint=false, and the description explains why by disclosing that it still marks the package dirty and refreshes compiled data in memory despite not saving. That is real side-effect context beyond the annotations, though it does not address idempotency or whether repeat calls recompile from scratch.

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?

The core behavior and the sibling distinction are front-loaded in the first sentence, and the return-shape block is justified because there is no output schema. It is slightly dense, but every clause (dirty package, in-memory refresh, comparator tool) earns its place.

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?

With no output schema, the description supplies the full return shape (tree_path, valid, compiled, error_count, warning_count, message_count, saved, errors, warnings, note), which is exactly what an agent needs. Side effects and the sibling boundary are covered, leaving nothing material missing for a one-parameter tool.

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 100% and the single tree_path parameter is fully documented in the schema with an example path, so the description adds nothing here. Baseline 3 is appropriate when the schema carries the parameter burden.

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+resource (compile a StateTree asset in memory and report errors/warnings) and explicitly names the sibling it is not (compile_state_tree compiles and saves). An agent can distinguish it from the sibling without opening either schema.

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 'without saving' qualifier and the direct contrast with compile_state_tree give clear context for when to pick this over the saving variant. It stops short of an explicit 'use this when you only need diagnostics' rule or exclusion of other validation tools, so it is strong but not fully prescriptive.

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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