figmad-mcp

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks critical behavioral details: it doesn't specify if this is a read-only analysis or if it modifies the codebase, what permissions or authentication are required, how it handles large codebases (e.g., rate limits or performance), or what the output format looks like (since there's no output schema). For a tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise and front-loaded, consisting of two efficient sentences that directly state the tool's function, supported technologies, and extraction targets. Every word earns its place, with no redundant or vague phrasing. This makes it easy for an agent to quickly grasp the core purpose without unnecessary detail.

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

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

Given the complexity of codebase analysis and the lack of annotations and output schema, the description is incomplete. It explains what the tool does but misses key contextual details: how it accesses the codebase (e.g., from a file system or URL), what the analysis output includes (e.g., structured data or raw text), and any limitations (e.g., supported file types or codebase size). Without this, an agent might struggle to use the tool effectively in real scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't mention any parameters, which is appropriate here—it implies the tool operates without inputs, possibly analyzing a default or contextually provided codebase. Since there are no parameters to explain, the description doesn't need to compensate, and a baseline of 4 is justified for not introducing confusion.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: analyzing a codebase to extract component definitions, props, and design tokens, with specific technology support (React, Vue, Svelte, Angular) and extraction targets (Tailwind config, CSS variables). It distinguishes from siblings like 'get_components' or 'get_variables' by focusing on codebase analysis rather than direct retrieval. However, it doesn't explicitly contrast with 'reconstruct_page' or 'generate_ui', which might involve similar analysis, leaving some room for improvement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a codebase path or access), exclusions (e.g., not for live websites), or compare to siblings like 'get_components' (which might retrieve existing components) or 'reconstruct_page' (which might rebuild UI from code). This lack of context makes it hard for an agent to decide when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.