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mcp-for-cascadeur

mcp-for-cascadeur

by Rickcy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

selection_set

Destructive

Replace selected objects using exact IDs or unambiguous names; pass an empty list to clear the current selection.

Instructions

Replace selected objects by exact IDs or unambiguous names; an empty list clears selection.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "objects": "<objects>"
    },
    "name": "selection_set"
  }
}

Input Schema

NameRequiredDescriptionDefault
objectsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already flag destructiveHint=true and readOnlyHint=false, and the description usefully sharpens that by clarifying the previous selection is *replaced* and that an empty list clears the selection entirely. That empty-list-clears behavior is a concrete, non-obvious effect not derivable from the annotations or schema.

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?

One front-loaded sentence with the mutation verb first, then the accepted input forms, then the edge case. Every clause earns its place and nothing is padded.

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

Completeness4/5

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

For a single-parameter mutation with annotations and no output schema, the description covers the essential semantics including the destructive edge case. Minor gaps remain around ambiguity resolution and the item limit, but nothing an agent needs to call it correctly is missing.

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 coverage is 0% — the schema only says 'array of strings, max 500'. The description compensates by specifying that entries may be exact IDs or unambiguous names and that the empty case means clear. It still leaves 'unambiguous' undefined (what happens on ambiguity, and the 500 cap) unexplained.

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?

States a specific verb and resource ('Replace selected objects') plus the accepted identifier forms, so an agent immediately knows this mutates the current selection. It does not name the obvious counterpart (selection_get) to contrast read vs. write, so sibling differentiation is left implicit.

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?

Usage is only implied: the description makes clear this is how you set a selection, but it never says when to choose it over alternatives (e.g., use selection_get to inspect first) or what prerequisites exist. Adequate but no explicit when/when-not guidance.

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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