Analyze Figma layout

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds that the tool reports heuristic evidence, confidence, anomalies, and samples, which gives some behavioral context. However, it does not explain what 'adaptive row/column geometry' means, how the heuristic works, or what the output structure looks like. No contradiction with annotations.

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 sentence that is concise and front-loaded with the core action. It lists the key outputs without unnecessary detail. However, it could be slightly more structured by separating the purpose from the output details.

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?

The tool has a complex input schema with 6 parameters, 0% schema description coverage, and no parameter documentation in the description. The output schema exists, so return values are covered, but the description does not explain the analysis methodology, the meaning of 'adaptive', or how the parameters influence the analysis. An agent would struggle to know what values to provide for tolerance, expected_columns, and expected_items_per_row.

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 description coverage is 0%, so the description must compensate for the 6 parameters. It does not explain the meaning of snapshot_id, selector, tolerance, expected_columns, expected_items_per_row, or global. The description mentions 'adaptive row/column geometry' which hints at expected_columns and expected_items_per_row, but it does not clarify how tolerance or selector work. This is a significant gap.

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 states a specific verb ('Detects') and resource ('adaptive row/column geometry') and lists the outputs (heuristic evidence, confidence, anomalies, samples). It is clear about what the tool does, though it does not explicitly distinguish itself from sibling tools like query_nodes or inspect_figma_file.

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 does not mention that this is a read-only analysis tool, nor does it explain when an agent should prefer analyze_figma_layout over query_nodes or inspect_figma_file. The context is implied by the name and description but not stated.

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