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Create a custom noodle

create_noodle

Turn brand guidelines into a noodle: give the brand colour and the noodle to cook it from, and get a stylesheet (tokens for light and dark on [data-brand]), usage and a contrast report. The accent is derived by a colour harmony unless you pass one. Use it whenever the user has brand colours.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseNoThe noodle that gives shape, depth and motion. Choose it with find_noodles. Default mian.
fontNo
nameNoBrand name; becomes the data-brand value.
accentNoSecond brand colour as hex. Omit to derive it.
radiusNo
weightNo
densityNo
harmonyNo
headingNo
primaryYesBrand colour as hex, e.g. "#1f4fd6".
neutralsNokeep = the base noodle’s own page, text and line colours (default).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It does disclose useful traits: the accent is auto-derived by colour harmony unless supplied, and the output artifacts (tokens for light and dark, usage, contrast report) are described. It does not say whether anything is persisted, whether an existing brand of the same name is overwritten, or what the response shape is.

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?

Two sentences, front-loaded with the produced artifacts before the trigger condition, and every clause carries information. Slightly dense with the colour/derivation caveat stacked mid-sentence, but no filler.

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?

With 11 parameters, 45% coverage, no annotations and no output schema, the description should do more. It covers the output payload well enough that an agent knows what it gets back, but it leaves the majority of styling parameters unexplained and omits persistence/side-effect behavior entirely.

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 only 45% across 11 parameters, so the description needs to compensate. It adds real meaning for primary (brand colour as hex), base (noodle drives shape/depth/motion, default mian) and accent (omit to derive via harmony), but font, heading, radius, weight, density and harmony mode are left entirely to the bare schema enums.

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 transformation: brand colour + noodle base in, a stylesheet (light/dark tokens on [data-brand]), usage notes and a contrast report out. That is far more concrete than a name restatement. It partially differentiates from siblings by pointing at find_noodles for choosing the base, but doesn't contrast with get_noodle_css or get_noodle, which sound adjacent.

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?

"Use it whenever the user has brand colours" is a usable trigger condition and it names find_noodles as the prerequisite for picking a base. There is no when-not guidance and no routing away from the near-named siblings (get_noodle, get_noodle_css), so usage is implied rather than fully specified.

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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