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mcp-for-cascadeur

mcp-for-cascadeur

by Rickcy

app_capabilities

Read-only

Read the actual native build, Python version, license flags, tool names, and enum names without editing, so you can verify the Cascadeur environment and available MCP features.

Instructions

Read actual native build, Python version, license flags, tools and enum names without editing.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "app_capabilities"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.6/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds that the values are "actual" (runtime-truthful), which is real context, but "without editing" merely restates readOnlyHint and nothing is said about the shape or size of the response.

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?

A single front-loaded sentence that lists the payload contents up front. The trailing "without editing" is slightly redundant with the read-only annotation and is the only wasted clause.

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?

With no parameters, no output schema, and full annotation coverage, the description carries the burden of describing return contents, which it does by naming build, Python version, license flags, tools, and enum names. Only the exact response structure and size remain unspecified, a minor gap for a zero-argument read tool.

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 takes zero parameters, so the baseline is 4; the description correctly implies no targeting inputs are needed to retrieve the capabilities snapshot. There is nothing further a parameter description could add.

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 uses a specific verb ("Read") and enumerates the concrete resources returned: native build, Python version, license flags, tools, and enum names. It is distinguishable from app_status and native_tools_list at a high level, though the overlap with api_inspect and native_tools_list is not explicitly addressed.

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 word "actual" hints that this reports live runtime facts rather than static documentation, which suggests it when an agent needs ground truth. There is no explicit when-to-use or when-not-to-use statement, and no mention of app_status, api_inspect, or native_tools_list as alternatives.

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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