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get_workflow_guide

Fetch SideFX Houdini workflow guides by topic before building an unfamiliar setup or after two failed attempts, covering build order, common mistakes, and relevant help pages.

Instructions

The server's written guide for a subject: what to build, in what order, which mistakes it exists to prevent, and the shipped help pages to read.

Call this BEFORE designing a setup you have not built this session, and again the moment two attempts at the same symptom have failed. Each guide is distilled from that subject's SideFX manual.

Args: topic: Help scope name or common alias: pyro, fluid (flip, water, whitewater), vellum (cloth), destruction (rbd), mpm (sand, snow), ocean, solaris, tops, model, copy, render, shade, character, crowds, heightfields, copernicus, assets, troubleshooting, dyno. description: What you are trying to build, for the guide's framing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
descriptionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.24.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries full burden and does disclose meaningful behavior: guides are distilled from the SideFX manual and include help pages to read. However it does not state the return shape, that it is a safe read, or pagination/size characteristics.

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?

Front-loads the resource definition, then usage conditions, then arg documentation. Every sentence carries information and the alias list, while long, is directly actionable.

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?

No output schema or annotations exist, so the description must stand alone. It covers purpose, timing, and accepted inputs well; it is only slightly incomplete on return format and size. That is sufficient for an agent to call it correctly.

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%, so the description must compensate. It extensively documents the required 'topic' param by enumerating the accepted help scope names and aliases (pyro, fluid, vellum, ocean, solaris, etc.), which effectively acts as an enum. The optional 'description' param is only lightly explained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (a distilled workflow guide for a subject) and enumerates its content: build order, mistakes it prevents, and shipped help pages. This is distinguishable from siblings like search_help and get_help_page because it is a curated workflow artifact, not a raw page lookup.

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?

Gives explicit triggering conditions: call before designing an unfamiliar setup, and again after two failed attempts at the same symptom. Strong when-to-use guidance, though it does not name alternative tools (e.g. search_help) for adjacent cases.

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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