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

Annotations already declare readOnlyHint=false, destructiveHint=false and idempotentHint=true; the description adds real behavioural content beyond them by stating exactly which date shapes are NOT handled (times, timezones, two-digit years) and that the returned file has every date rewritten. It does not explain that this is a priced job requiring a quote, but the quote_id and accepted_price schema descriptions cover that. The remaining gap is the return payload shape, which the output schema covers.

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?

Front-loaded with the operation, which is good, but the second sentence largely restates the first, re-listing 'detect the date columns, flag dates ... receive the file rewritten as ISO 8601' verbatim. The redundancy pushes length up without adding information; the example requests are the only genuinely additive part of the tail.

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?

With annotations, a populated input schema and an output schema, the description only needs to cover scope and limits, and it does: it states unsupported cases and the ISO 8601 output. What is missing is a note that this submits a priced job tied to a quote, though the schema fields make that discoverable.

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?

Four parameters at 75% description coverage, with the schema already explaining content, quote_id, authorized_by and accepted_price in detail. The description adds no parameter-level meaning at all — nothing about input size limits, delimiter handling, or how quote/authorisation interact with the job. Baseline 3 is appropriate when the schema does the work.

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 concrete verbs and resources: detect date columns in a CSV, report formats, flag day/month vs month/day ambiguity, and return the file rewritten as ISO 8601. The purpose is unambiguous and an agent can tell this is the date-normalisation step rather than a general CSV cleaner. It never names or contrasts a sibling (submit_csv_clean, submit_csv_quality_report, etc.), which is the only reason it does not reach 5.

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?

Explicitly says when to pick it ('before loading a CSV whose dates are in mixed or local formats') and when not to ('dates carry times or timezones, which are not converted, or for two-digit years'). Example requests reinforce the intended call. No alternative tool is named for the excluded cases, so it falls short of the alternatives-plus-exclusions bar.

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