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caption_style_save

DestructiveIdempotent

Save the current project's caption look—including presets, overrides, and grouping rules—to the machine's library for reuse in any other project.

Instructions

Save this project's caption look to this machine's library, so any project can load it.

The preset and every override on it are saved, grouping rules included.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	What to call the look in this machine's library: lowercase letters, digits, - and _.
`path`	No	The project directory to act on. Omit it — the usual case — when this server is bound to a project (started as `proofcut -C DIR mcp`, or inside a project; `ping` says which): it then resolves to that one bound project, a relative path resolves against it, and a path outside it is refused by name. Unbound, `path` is the whole address and omitting it refuses rather than guessing.
`replace`	No	Replace a saved look of this name. Unset, a taken name is refused.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.43.0Sep 24, 2026

TDQS

A4.3/5.0

Behavior4/5

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

The description adds machine-local library scope, the fact that the preset plus every override and grouping rule are saved, and that the result can be loaded by any project. These details go beyond the annotations' write/destructive hints and clarify what a save actually captures.

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?

Two brief sentences with the main action and machine-local scope front-loaded. The second sentence earns its place by specifying exactly what is captured, with no filler or redundancy.

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

Completeness5/5

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

For a three-parameter write tool with full schema coverage, rich annotations, and an output schema, the description covers purpose, scope, and saved content. Nothing an agent needs to call it correctly is missing; path/name/replace behaviors are already documented in the schema.

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 coverage is 100%, and the description does not attempt to re-explain name, path, or replace; the schema descriptions already define constraints and defaults. The overrides/grouping-rules note is about save scope, not parameter semantics, so it adds no parameter-level meaning beyond the schema.

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?

The description states a specific verb ('Save') and resource ('this project's caption look') and clarifies the destination ('this machine's library') and purpose ('so any project can load it'). This clearly distinguishes it from sibling caption-style tools without requiring schema inspection.

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?

The description clearly frames when to use the tool: when the current project's caption look should be persisted for reuse across projects. It doesn't explicitly name alternatives or when-not-to-use cases, but the context makes the intended invocation obvious.

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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