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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context by specifying return values (cosine similarity and Euclidean distance) and providing interpretation thresholds (>0.95 very similar, <0.80 structurally different). It also reveals the 'physics-based fingerprints' technique, giving insight into how the comparison works beyond the schema.

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 compact and well-structured: first sentence states purpose and output, second sentence lists use cases, and third sentence provides thresholds. There is no redundant information, and the most important details are front-loaded.

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 is simple (3 params, no output schema), but the description covers purpose, return format, use cases, and numeric interpretation. It is fully sufficient for an agent to select and invoke the tool, especially with the supportive annotations. No critical behavioral aspects are unexplained.

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%, and each parameter has a basic description: 'First data item to compare', 'Second data item to compare (same type as data_a)', and encoder_type with an enum and 'Omit to auto-detect.' The description itself does not add further parameter detail, but the schema is already adequate. Baseline 3 is appropriate.

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 function: 'Compare two data items for structural similarity using physics-based fingerprints' and lists what it returns (cosine similarity and Euclidean distance). This distinguishes it from sibling tools like waveguard_fingerprint (which likely generates fingerprints) and waveguard_scan (which analyzes a single item).

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 explicitly says 'Use for duplicate detection, behavioral matching, drift analysis, or checking if two tokens/wallets/contracts are structurally similar.' This provides concrete use cases. It does not mention when not to use it or alternative tools, but the use-case list is clear and actionable.

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