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niagara_validate_authoring_support

Probe available Niagara Python and editor APIs to confirm authoring support before creating assets.

Instructions

Probe available Niagara Python/editor APIs before native authoring work.

KB: see knowledge_base/09_NIAGARA_VFX.md#overview Example: niagara_validate_authoring_support()

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It says 'Probe' which suggests a read-only operation, but it doesn't disclose what the probe returns, whether it has side effects, what 'authoring support' means concretely, or what the agent should do with the result. The KB reference is a pointer but not a disclosure of behavior.

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 description is short and front-loaded with the core purpose. The KB reference and example are useful but the example is somewhat redundant for a zero-parameter tool. Still, it's compact and every sentence contributes.

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

Completeness3/5

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

For a zero-parameter probe tool, the description is mostly adequate, but it lacks detail on what the output looks like or how to interpret the results. The output schema exists but isn't shown in the provided context, so the description could have explained what 'authoring support' means. The KB reference partially compensates.

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 tool has zero parameters, so the schema is trivially complete (100% coverage). The description adds context about the purpose of the probe, which is sufficient for a no-arg tool. Baseline 4 for zero-param tools is appropriate.

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 verb ('Probe') and resource ('available Niagara Python/editor APIs') and frames it as a pre-flight check before native authoring work. It is distinguishable from sibling Niagara tools like niagara_create_system or niagara_describe_system, though it doesn't explicitly name a sibling to differentiate from.

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?

The phrase 'before native authoring work' implies when to use it, and the KB reference provides a pointer for deeper context. However, it doesn't explicitly state when NOT to use it or name alternative tools (e.g., niagara_describe_system for inspecting an existing system). The guidance is implied rather than explicit.

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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