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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered; the description goes further by disclosing what is actually performed (column detection, USPS formatting, missing-field and duplicate reporting, cleaned CSV output). The explicit exclusions — no address verification, no ZIP+4 lookup, no label printing — are exactly the kind of boundary an agent needs before promising a user an outcome.

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: the usage trigger and example utterances come first, then the exclusions. Every clause carries information, though the first sentence is long and dense enough that the list of reported problems and the 'cleaned CSV download' are easy to skim past.

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 10-parameter, fully optional, nested-input tool with an output schema present, the description covers the input modes, the processing behavior, and the boundaries; return values are correctly left to the output schema. The only thing an agent might still wonder about — limits on list size or what happens on unsupported file types — is minor and partly available in the schema.

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 the per-parameter descriptions already carry the detail and a baseline of 3 would be defensible. The description earns an extra point by explaining the two input modes (uploaded file vs typed list) and the automatic behaviors — heading-based column detection and USPS formatting — that the schema alone does not make obvious.

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?

States a specific verb and resource ('check or clean a mailing list') plus the concrete operations: reads a CSV/XLSX or typed list, detects name/street/city/state/ZIP columns, USPS-formats addresses, and reports missing fields and duplicates. It explicitly distinguishes itself from the sibling generate_label_sheet, so an agent can route correctly without opening either schema.

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?

Opens with an explicit trigger ('use this when the user wants to check or clean a mailing list before printing labels') and backs it with three quoted user phrasings. It also names the specific alternative for the adjacent task ('does not print the labels (use generate_label_sheet)'), giving both when-to-use and when-not-to-use.

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