origin_diagnose_worksheet

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

With no annotations, the description fully discloses behavior: it reports per-column statistics, lists specific issue types with severities (error, warning, info), explains the high_missing_threshold parameter, and clarifies that 'passed' is false when any error-severity issue is found. This provides comprehensive insight into tool behavior beyond a generic quality check.

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 and well-structured: a one-sentence purpose statement followed by a list of outputs and key parameter explanation. Every sentence adds value with no redundancy or fluff.

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?

Given the presence of an output schema, the description does not need to detail return values. It covers the main behavior, issue categories, and threshold parameter. However, it omits how the columns parameter interacts (e.g., if omitted, checks all columns), which is a minor gap for a tool with optional parameters.

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 add meaning. It explains high_missing_threshold (missing fraction that triggers a warning) but does not describe the other three parameters (columns, book_name, sheet_name), leaving their purpose and constraints to inference. While the parameter names are somewhat self-explanatory, the description should explicitly state how they identify the worksheet and filter columns.

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 lists specific outputs like per-column dtype, missing count/fraction, unique count, and structured issues with severity levels. This distinguishes it from sibling tools like origin_read_worksheet (which reads data) and origin_run_analysis (which performs analysis), making its role as a diagnostic step clear.

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 provides clear context by stating 'before plotting or analysis,' implying when to use it. However, it does not explicitly exclude use cases or mention alternative tools for specific scenarios. The context is sufficient to guide typical use but lacks explicit when-not guidance.

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