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ladybug-tools-mcp

ladybug-tools-mcp

by LoftyTao
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Python
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Get Schema

get_schema

Retrieve parameter schemas for specific tools to get the details needed for calling them. Use after searching to obtain the required input information.

Instructions

Get parameter schemas for specific tools.

Use after searching to get the detail needed to call a tool.

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": {
      "tools": "<tools>"
    },
    "name": "get_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
toolsYesList of tool names to get schemas for
detailNo'brief' for names and descriptions, 'detailed' for parameter schemas as markdown, 'full' for complete JSON schemasdetailed

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of conveying behavioral context. It does present this as a read/inspection operation ('Get', 'Use after searching'), and the output schema partially covers return behavior. However, it does not explicitly state that the tool has no side effects, does not execute the requested tools, or how it behaves if a tool name is invalid.

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 two short sentences with no filler. The main purpose is front-loaded, and the workflow guidance directly follows. Every sentence earns its place.

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 low-complexity introspection tool with an output schema and fully documented parameters, the description is largely sufficient. It gives the workflow context ('after searching') and the goal ('detail needed to call a tool'). The main missing piece is a brief note on side-effect-free behavior, but this is minor for a tool like this.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides 100% coverage with meaningful descriptions for both tools and detail, including the enum meanings. The description adds little parameter-specific value beyond the phrase 'detail needed to call a tool,' so the baseline of 3 applies.

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 clearly identifies the action ('Get') and resource ('parameter schemas for specific tools'), so an agent can quickly understand what the tool does. However, it slightly undersells the output: the detail parameter can return names/descriptions and full JSON schemas, not just parameter schemas. It also doesn't explicitly differentiate from execute, though the workflow hint helps.

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 explicitly says to use this tool 'after searching' and frames it as the step to obtain 'the detail needed to call a tool.' This gives useful sequencing relative to the sibling tools search and execute. It stops short of naming explicit exclusions or when not to use it, so it is clear but not fully exhaustive.

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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