data_quality_report

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by listing specific quality check categories, but does not disclose behavior like performance impact or error handling. Given the strong annotation coverage, the description provides adequate additional 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?

A single, front-loaded sentence that efficiently communicates the tool's purpose and scope. No unnecessary words, and it includes the key verb 'run', resource 'Odoo model', and constraints 'read-only' and specific check types.

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?

Despite having an output schema, the description fails to explain how to use the five parameters effectively or what to expect from the checks. For a tool with no schema parameter descriptions, this is insufficient for an agent to craft correct invocations.

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 the description must compensate. It mentions 'one Odoo model' but does not explain parameters like 'checks' (what string values?), 'instance', 'key_fields', or 'sample_limit'. Users lack guidance on configuring these parameters beyond their names.

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 runs read-only data-quality checks on one Odoo model, listing specific check types (duplicates, missing values, etc.). It distinguishes itself from sibling tools like 'aggregate_records' or 'diagnose_access' by focusing on data quality and read-only operation.

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?

No explicit guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. While the purpose implies usage for data quality checks, a mention of when not to use it (e.g., for write operations) would improve clarity.

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