smooth

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

With no annotations, the description bears full transparency burden. It states that a new column is created and lists parameters, but does not disclose side effects (e.g., whether data is modified in place), error conditions, or any destructive potential. It provides adequate but not comprehensive behavioral detail.

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 short and front-loaded with the core action. The argument list is clean and easy to scan. It earns its keep without extra verbiage, though it could add a sentence on parameter semantics without harming conciseness.

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 six parameters, various methods, and sibling tools for similar operations, the description is too sparse. It does not explain return format beyond a success message, nor does it guide method selection or window size. The output schema exists but is not referenced.

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 coverage is 0%, so description must compensate. It explains method and window with defaults, but the four required parameters (data_book, data_sheet, x_col, y_col) are left entirely to the schema, which itself has no descriptions. The agent lacks meaning for over half the 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 uses a specific verb ('Smooth') and resource ('a curve into a new column'), clearly defining the action. It lists available methods (savitzky_golay, adjacent, binomial), distinguishing it from sibling tools like differentiate or interpolate by stating exactly what it does.

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 guidance is given on when to use smoothing versus alternatives like moving average or other processing tools. The description lacks context such as 'use this to reduce noise' or 'not suitable for sharp features', leaving the agent to infer usage from the name alone.

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