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

Annotations declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, establishing this as a non-destructive, idempotent job. The description adds the bounded signal processing limits (8 channels, 4096 samples/channel), which is useful operational context. However, it doesn't disclose pricing, job status behavior, or result format beyond 'differences and rule results'—gaps that matter for a job-submitting tool in a marketplace context.

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 extremely concise and well-structured using labeled sections (Problem, Input, Result, Limits). Every sentence serves a purpose and the information is front-loaded with the core comparison operation.

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 complexity (nested request object, job submission mechanics, pricing constraints) and the presence of an output schema, the description covers the core comparison logic and limits but omits critical operational details like pricing behavior, job lifecycle, and how to use the idempotency key. The output schema presumably covers return values, so that omission is acceptable.

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 all four parameters (schema_version, request, idempotency_key, max_total_price) are undocumented in both schema and description. The description mentions 'JSON with reference, reconstruction, rules' which hints at the request object contents, but doesn't map these to the actual parameter structure or explain idempotency_key and max_total_price requirements.

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 uses a structured Problem/Input/Result/Limits format that clearly states the verb (compare/validate) and resource (reconstruction vs reference against acceptance rules). It distinguishes itself reasonably from siblings like wave_validate_spectral_criteria_v1 by focusing on reconstruction quality rather than spectral criteria, though it doesn't explicitly name alternatives.

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 through its problem statement (comparing a reconstruction with a reference), but provides no explicit guidance on when to use this tool versus related validation tools like wave_validate_spectral_criteria_v1 or wave_verify_wave_pipeline_v1. There are no when-not or alternative conditions stated.

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