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splatcraft

splatcraft

Official
by sandraschi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Rust
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Splat Probe Local Engines

splat_probe_local_engines

Probes the host system to detect available local 3D Gaussian splatting training backends, helping agents decide if local RTX training can run.

Instructions

Probes the host system (e.g. RTX 4090) for local 3DGS training backends.

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": "splat_probe_local_engines"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. "Probes" implies a read-only, non-destructive inspection, but it does not confirm that, nor does it mention whether detection is fast or may take time, what happens on a machine with no GPU, or what "backends" are actually enumerated.

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?

A single front-loaded sentence with no filler, and the parenthetical example does real work by pinning down the otherwise vague term "backend". Every word 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?

The tool is trivial to invoke (no inputs) and an output schema exists to describe the detected backends, so the description needn't enumerate return values. What is missing is the relationship to splat_train_local, which is the main reason an agent would call this at all.

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 there is no parameter semantics to mis-specify; the baseline for a parameterless tool applies. Nothing in the description conflicts with the empty, closed input schema.

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 (probes) and a precise target (the host system, for local 3DGS training backends), with a concrete example (RTX 4090) that clarifies what a "backend" means. It implicitly distinguishes itself from splat_train_local (discovery vs. execution), but never names a sibling to contrast with.

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: an agent can infer it should run this to check hardware availability before invoking splat_train_local, but the description never states that sequencing or any precondition. No when-not-to-use guidance or alternatives are offered.

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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