origin_diagnose_worksheet

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

With no annotations provided, the description fully discloses the tool's behavior: it reports per-column stats and structured issues at three severity levels (error, warning, info), explains the high_missing_threshold parameter, and clarifies the 'passed' flag. The tool is likely read-only, and the description transparently describes its diagnostic output.

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 concise (two sentences) and front-loaded with the purpose. Every sentence adds value without redundancy.

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?

The tool has an output schema, so return values are covered. However, the description omits explanations for three of four input parameters (book_name, sheet_name, columns), which is a significant gap for completeness.

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?

The schema description coverage is 0%, so the description must compensate. It only describes one parameter (high_missing_threshold) explicitly. The other three parameters (book_name, sheet_name, columns) are not described, leaving their meaning and usage unclear.

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's purpose: 'Check worksheet data quality before plotting or analysis.' It details the specific reports (per-column dtype, missing count/fraction, unique count) and structured issues, which distinguishes it from other tools like origin_read_worksheet or origin_plot.

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 it should be used before plotting or analysis, but does not explicitly state when not to use it or provide alternatives. The context is clear, but exclusions are missing.

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