origin_run_analysis

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

With no annotations, the description carries the full burden. It discloses that include_output=True is for analyses creating worksheets and mentions backward compatibility for aliases. However, it does not explain key behaviors such as synchronous vs asynchronous execution, data mutation, permissions, or error handling, which are important for agent decision-making.

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 three sentences, front-loaded with the core purpose, then a key usage note, then clarification about schema naming. Every sentence serves a purpose without 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 complexity of 8 parameters, an output schema, and the existence of sibling tools, the description covers the main purpose and key usage pattern. It could be more complete by explaining the return format or prerequisites, but the output schema likely fills some gaps. Overall, it is adequate for a tool with good schema coverage.

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 input schema has 100% coverage with each parameter described. The description adds significant value by providing concrete examples for the options parameter (e.g., polynomial_fit uses order, smooth uses method and points) and explaining the recalculate sub-option. This extra context helps the agent understand how to set analysis-specific parameters.

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 a supported Origin analysis and returns structured metrics or output rows. It provides specific details about using include_output with output_sheet for worksheet-creating analyses, and distinguishes this tool from siblings by focusing on analysis execution versus other operations like plotting or reading worksheets.

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 gives guidance on when to use include_output=True with output_sheet, and mentions that aliases are accepted for backward compatibility. However, it does not explicitly state when not to use this tool or provide alternatives from the sibling list, leaving some ambiguity about best practices.

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