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origin_diagnose_worksheet

Checks worksheet data quality for missing values, duplicates, and non-numeric columns, reporting issues before plotting or analysis.

Instructions

Check worksheet data quality before plotting or analysis.

Reports per-column dtype, missing count/fraction, and unique count, plus structured issues: empty_worksheet and all_null_column (error), high_missing and duplicate_columns (warning), non_numeric_column and constant_column (info). high_missing_threshold is the missing fraction (0-1) that triggers a high_missing warning. "passed" is false when any error-severity issue is found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
columnsNoColumn names or zero-based column indexes selected for this operation.
book_nameNoOrigin workbook name. Omit to use the active workbook or the tool default.
sheet_nameNoOrigin worksheet name. Omit to use the active sheet or the tool default.
high_missing_thresholdNoMissing-value fraction from 0 through 1 that triggers a high_missing warning.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description fully discloses expected outputs: column stats, issue list with severities, and 'passed' flag. It details threshold behavior and issue triggers, though it could mention read-only nature explicitly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with a front-loaded purpose statement. Every sentence adds information—no redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists, the description adequately covers behavior and expected results. It could mention that the tool is read-only, but overall it is complete for a diagnostic tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline 3. The description adds value by explaining high_missing_threshold range and the meaning of 'passed' false, going beyond the schema's basic parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool checks worksheet data quality before plotting or analysis, listing specific reports (dtype, missing, unique) and issue types. This distinguishes it from sibling tools like origin_read_worksheet and origin_plot.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to use 'before plotting or analysis', providing clear context. However, it does not mention when not to use or list alternatives, though no sibling tool has similar purpose.

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

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