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Rd Preset Save

rd_preset_save

Save custom generation settings as a named preset in presets.json for reuse in future generations.

Instructions

Save a named generation preset (any rd_generate kwargs) to presets.json.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
settingsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden. 'Save ... to presets.json' indicates persistence, but it does not disclose overwrite behavior for duplicate names, return value, failure modes, or any side effects beyond writing a file. For a mutation tool with zero annotation coverage, this is a significant transparency gap.

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 sentence with no filler. Every word contributes meaning, and the core action and destination are front-loaded.

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 simple save tool, the core parameters and destination are sufficiently covered, and an output schema exists. But with no annotations and no mention of overwrite semantics, side effects, or the relationship to rd_preset_apply, the description leaves an agent to infer important behavior.

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?

Schema description coverage is 0%, so the description must compensate. It does add the key semantic that 'settings' consists of 'any rd_generate kwargs', which is valuable. However, 'name' is only described as 'named' with no format or uniqueness constraints, so compensation is partial.

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 action ('Save'), a specific resource ('a named generation preset'), and a destination ('presets.json'). This clearly differentiates it from sibling tools like rd_preset_list, rd_preset_apply, and rd_preset_delete without needing to inspect their schemas.

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?

The usage is implied: save a preset when you want to persist rd_generate kwargs. However, it gives no explicit when-to-use guidance, no exclusions, and does not mention that saved presets can later be loaded via rd_preset_apply.

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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