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

Annotations already declare destructiveHint=false, idempotentHint=true, openWorldHint=false, and readOnlyHint=false. The description adds genuinely useful behavior beyond that: local-software-only evidence scope and a 65536 request-byte limit. However, it never discloses that this is a paid job submission (max_total_price) or what the readOnly=false/idempotent semantics mean in practice, so disclosure is partial.

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 Problem/Input/Result/Limits labeling is efficient and front-loaded, with no filler sentences. The trailing ellipsis ('maximum l1 error....') is slightly untidy but does not undermine the structure.

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?

An output schema exists, so return values need not be detailed, yet the description does sketch them anyway. Given a nested, open request object and a job-wrapper schema, the definition is adequate but omits the payment/job-creation context an agent needs to invoke it correctly.

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% and the request object is fully opaque, so the description must compensate. It partially does by naming inner request fields (observed/expected probabilities, maximum l1 error), but it leaves schema_version, idempotency_key, and max_total_price unexplained, so the four-parameter surface is only partially illuminated.

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 names a specific verb (Compare) and resource (bounded simulation result vs. supplied expectations and anomaly rules) and states the outcome (anomaly verdict). It distinguishes the tool conceptually from compare-style and workflow-diagnosis siblings, though it never names an alternative explicitly.

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?

There is no explicit when-to-use or when-not guidance, and no routing to alternatives despite several overlapping siblings (quantum_simulation_result_compare_v1, diagnose_quantum_workflow, quantum_failed_workflow_diagnosis_v1). Usage is only weakly implied by the 'Problem:' framing.

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