result_set_legend_rangeSet the result colorbar legend's min/max range to control how simulation results are displayed; pass null for automatic scaling.
Set the result colorbar (legend) min/max range. Use null for auto.
| Name | Required | Description | Default |
|---|---|---|---|
| max | No | 범례 최대 (null=자동) | |
| min | No | 범례 최소 (null=자동) |
Changes observed during successful MCP inspections.
v4.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds no behavioral context beyond that - it does not say whether results must be loaded, whether the range is per-dataset, or what effect it has on the view.
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 sentences, action and parameter hint, front-loaded with zero filler. Sized correctly for a trivial two-optional-parameter setter.
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 simple idempotent setter with full schema coverage and no output schema, the description is minimally viable. It omits any precondition (results loaded / active dataset) that an agent would need to call it correctly in the results workflow.
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 description coverage is 100% and both params already document 'null=auto' (null=自動), so the description's 'Use null for auto' merely restates the schema. Baseline 3 is appropriate when the schema does all the work.
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 ('Set') and resource ('result colorbar (legend) min/max range'), which is precise enough to separate it from the sibling result_set_colormap. It does not explicitly name that sibling or draw the boundary, so it falls short of a 5.
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 only guidance is 'Use null for auto', which is a parameter note, not a when-to-use cue. Nothing says when to set a manual range versus leaving auto, or how this relates to result_set_colormap / result_set_active_dataset.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.