Apply multiple Unreal Engine console variables in one call by passing a JSON object string of name-value pairs, returning per-variable errors.
Apply many cvars in one call. JSON shape: {"name":"value", ...}
Returns: { applied, requested, errors: [{name, error}] }
| Name | Required | Description | Default |
|---|---|---|---|
| cvars | Yes | JSON object string {"cvar":"value", ...} |
Changes observed during successful MCP inspections.
v1.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, idempotentHint=true and readOnlyHint=false, so the mutation profile is covered structurally. The description adds genuine context beyond that by disclosing the return payload with a per-cvar 'errors' array, implying partial application (some cvars may fail while others succeed) rather than an all-or-nothing atomic write. That is a meaningful behavioral trait not present in the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two terse segments: the action and scope first, then the return shape. No filler, no restated verbosity, and the highest-value information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter bulk-write tool with annotations covering safety and no output schema, the description supplies both the input shape and the return shape. The only soft gap is that atomicity is left to inference from the errors array rather than stated outright, and no preconditions (e.g. valid cvar names) are given.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and there is a single required parameter, so the schema already documents 'cvars' fully. The description's JSON shape hint {"name":"value", ...} repeats the schema's own description almost verbatim, adding no new syntax or constraint detail. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Apply many cvars') plus the distinguishing scope ('in one call'), which separates it from the single-value set_cvar sibling in the list. It does not name that sibling explicitly, so differentiation requires the agent to infer it from 'many'. Still, the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'in one call' implies the batch use case versus set_cvar, but there is no explicit when-to-use or when-not-to-use statement and no named alternative. Usage is left to inference rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.