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Houdini MCP

Houdini MCP

by beatreichenbach
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_shelf_tool_script

Read a Houdini shelf tool’s script, help text, and imports to inspect or customize its behavior.

Instructions

Read the script a shelf tool runs, plus its help and imports.

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": {
      "tool_name": "<tool_name>"
    },
    "name": "get_shelf_tool_script"
  }
}

Input Schema

NameRequiredDescriptionDefault
tool_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden. It discloses the content of the return payload (script, help, imports), which is genuinely useful, but says nothing about what happens with an unknown tool_name, whether the shelf context matters, or whether the call has any side effects beyond the implied read.

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 with no filler, and the primary output is named first. It is close to optimally sized for the amount of content it conveys, though it could spend one more clause on the parameter.

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

Completeness3/5

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

For a one-parameter read tool with no output schema, describing the returned values is the right move and it does so. It still leaves the agent guessing about identifier format and failure behavior, which are the two things needed to invoke it correctly.

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

Parameters2/5

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

Schema coverage is 0% and the single parameter tool_name is undocumented in both schema and description. The critical ambiguity is whether it is a bare tool name or a shelf/tool qualifier, which matters given shelves can hold tools with identical names.

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 (Read) and a specific resource (the script a shelf tool runs), and adds the secondary return payloads (help and imports). That is enough to distinguish it from run_shelf_tool, which executes rather than inspects, without naming it.

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 verb 'Read' signals inspection rather than execution, so an agent can infer this is the tool to use before deciding whether to run something. There is no explicit when-to-use, no stated alternative, and no prerequisites such as needing a valid shelf context.

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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