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AlexZai007

figma-unlimited-mcp

by AlexZai007

Build the demo board

create_demo_board

Build a complete architecture review board in one call, including system diagram, lifecycle, runbook, service catalog, and config snippets. Use it to showcase server capabilities or verify a fresh installation.

Instructions

Build a complete architecture review board in one call: a system architecture diagram, a request lifecycle, an incident runbook, a service catalog table, config snippets, review stickies and a legend — about 200 nodes, in well under a second.

Use it to show what this server can do, or to check that a fresh install actually works. Pass mode "clean" to remove it again; everything it creates is tagged, so nothing else on the board is touched.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo"build" creates the board, "clean" removes a previous run.build
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses key behavioral traits: creates ~200 nodes in under a second, tags everything it creates, touches nothing else on the board, and supports a clean mode to remove previous runs. This is substantial behavioral information, though it stops short of specifying return values or edge cases like repeated builds without clean.

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?

The description is concise and well-structured. The first sentence front-loads the purpose, the middle lists contents, and the second paragraph covers usage and cleanup. Every sentence adds value with no redundancy or fluff.

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?

Given the tool's complexity (composite board with ~200 nodes), the description is thorough: it covers what gets created, the performance, use cases, cleanup, and safety. No output schema exists, but the description does not need to explain return values as this is a build/clean operation rather than a query.

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?

Schema coverage is 100% for the single mode parameter. The description adds semantic value by explaining what 'clean' does: "Pass mode 'clean' to remove it again." It also implies the default 'build' behavior. This enriches the schema's enum/description.

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 and resource: "Build a complete architecture review board in one call." It enumerates the board's contents (system architecture diagram, request lifecycle, etc.) and explicitly distinguishes this from sibling tools that create individual elements by highlighting the composite nature and ~200 nodes.

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 gives clear usage context: "Use it to show what this server can do, or to check that a fresh install actually works." It also explains the cleanup mode with "Pass mode 'clean' to remove it again." It does not explicitly exclude alternatives, but the demo/smoke-test purpose is clear from context.

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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