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prepare_case

Generates case geometry, RDF, MCN and RAO files and validates a fresh mesh before the motion solve. Call again with the plan token once a human confirms the plan.

Instructions

Generate geometry/RDF/MCN/RAO and check a fresh mesh before the motion solve.

If planning requires confirmation, call again with that plan's token only after human agreement. Measured mesh warnings require another review before start_case.

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": {
      "config": "<config>"
    },
    "name": "prepare_case"
  }
}

Input Schema

NameRequiredDescriptionDefault
configYes
confirmation_tokenNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose two non-obvious behaviors: a confirmation-token gate requiring human agreement, and that measured mesh warnings force another review pass. It does not disclose side effects such as files written, idempotency of a re-run, or what a second call without a token does.

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?

Three short sentences, front-loaded with the action and followed by the two conditional guards. Nothing is padded, though the unexpanded acronyms cost the reader a little parsing effort.

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

Completeness2/5

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

An output schema exists, so return values need not be described. But for a tool whose only required argument is a large multi-branch config (geometry discriminated union, mechanics, environment), the description offers no orientation to the config structure or which submode to pick — a significant gap at this complexity.

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 description coverage is 0%, so the description must compensate. The phrase 'that plan's token' usefully explains confirmation_token, but the sole required parameter, config, is a deeply nested CaseConfig with dozens of fields and gets no explanation at all.

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 first sentence names a concrete verb (generate) and enumerates the pipeline artifacts (geometry/RDF/MCN/RAO) plus the mesh check, so the agent knows this is a preparation-stage tool. It is distinguishable from siblings like build_geometry or start_case, though the acronyms are never expanded and require domain fluency.

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?

It establishes sequencing ('before the motion solve', 'before start_case') and describes the confirmation retry path, which is real usage guidance. However, it never says when to call this instead of the closely named siblings plan_case, generate_inputs, or build_geometry, leaving the agent to infer the boundary.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.