extract_tokens_from_figma_variables

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 the tool parses and extracts tokens but doesn't describe what 'extract' entails (e.g., format of output, whether it transforms data, error handling, or performance considerations). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior beyond the basic purpose.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action ('parse' and 'extract'), making it easy to scan and understand quickly. Every part of the sentence contributes essential information.

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 tool's moderate complexity (parsing JSON to extract tokens), no annotations, and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose and input but lacks details on output format, error cases, or how it differs from siblings. For a tool with no structured behavioral data, it should provide more context to be fully helpful.

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 100% description coverage, clearly documenting the 'variables' parameter as 'Figma Variables REST API JSON export as a string'. The description adds no additional semantic context beyond this (e.g., example JSON structure, validation rules, or common pitfalls). With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.

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 specific action ('parse' and 'extract'), the resource ('Figma variables export JSON'), and the output ('design tokens'). It distinguishes itself from siblings like 'extract_tokens_from_css' or 'extract_tokens_from_json' by specifying the Figma source format, making the purpose unambiguous and well-differentiated.

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 Figma variables data), exclusions (e.g., not for CSS files), or comparisons to siblings like 'extract_tokens_from_json' (which might handle generic JSON). Without such context, the agent must infer usage from the tool name alone.

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