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unreal_snapshot

Read-only

Record a baseline snapshot of selected actors for later diffing in Unreal Editor, without saving files or modifying the scene. Snapshots are temporary and expire after 15 minutes.

Instructions

Record a selected-actor baseline for later diff; no files, cloud, saves or edits.

Exact selection only, not the entire scene. Keeps at most 32 snapshots, 2 MiB total, for 15 minutes in this MCP process. Restarting the server clears all snapshot IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actor_pathsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

The description goes well beyond the annotations. It discloses the ephemeral nature ('15 minutes in this MCP process'), the storage limits ('at most 32 snapshots, 2 MiB total'), the invalidation behavior ('Restarting the server clears all snapshot IDs'), and the non-persistent side effects ('no files, cloud, saves or edits'). This is rich behavioral context that the annotations (readOnlyHint=true, destructiveHint=false) do not provide. No contradiction with annotations.

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?

The description is compact and front-loaded. The first sentence states the core purpose and the key negative constraints. The second sentence adds the selection scope. The third sentence packs the retention limits and invalidation behavior. Every sentence earns its place; no filler or repetition.

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?

For a tool with one parameter, an output schema, and annotations covering the safety profile, the description is complete. It covers what the tool does, its scope, its limits, and its lifecycle. The only minor gap is the exact path format, but the schema's minLength/maxLength and the description's 'exact selection' provide enough for an agent to invoke it correctly. The output schema presumably documents the return value, so the description needn't explain it.

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 description coverage is 0%, so the description must compensate. The description explains the meaning of the parameter indirectly: 'selected-actor baseline' and 'Exact selection only' clarify that actor_paths is a precise list of actors to snapshot, not a scene-wide filter. It also implies the maxItems=20 constraint by emphasizing 'exact selection only'. However, it doesn't explicitly describe the format of the paths (e.g., full path vs. name), which would be needed for full compensation.

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?

The description states a specific verb ('Record'), a specific resource ('selected-actor baseline'), and its purpose ('for later diff'). It also explicitly distinguishes itself from scene-wide operations ('Exact selection only, not the entire scene'), which differentiates it from sibling tools like unreal_diff and unreal_capture. The negative constraints ('no files, cloud, saves or edits') further clarify what the tool does not do.

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 description clearly implies when to use this tool: when you need a baseline of selected actors for later diffing. It explicitly states the selection scope ('Exact selection only, not the entire scene'), which is a key usage constraint. However, it does not explicitly name alternative tools or state when NOT to use it (e.g., 'use unreal_diff to compare, use unreal_capture for full scene capture'), so it falls short of a 5.

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