get_tokens

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

No annotations are provided, so the description must disclose behavioral traits. It only states 'Extract' (implying read-only) and 'returns structured token data', but lacks details on permissions, side effects, rate limits, or output format specifics.

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?

Two sentences with no redundant words. The first sentence front-loads the verb and resource, making the purpose immediately clear.

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?

For a simple extraction tool with 2 well-described parameters, the description is adequate but lacks output schema details and any behavioral guarantees. Given no annotations, more context (e.g., return format) would improve completeness.

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?

Schema coverage is 100%, so baseline is 3. The description adds value by contextualizing the output for code generation and explicitly listing the token categories (colors, typography, spacing) that align with the enum, reinforcing parameter meaning beyond the schema.

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 verb 'Extract', the resource 'design tokens (colors, typography, spacing) from a Penpot file', and the purpose 'for use in code generation'. It distinguishes itself from sibling tools like get_components by focusing on token extraction.

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 implies usage for code generation but does not explicitly state when to use this tool versus alternatives (e.g., get_components, get_design_context). No when-not-to-use or prerequisite guidance is provided.

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