load_csv

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

With no annotations, the description carries the full burden. It discloses key side-effects: the loaded dataframe becomes the current active dataframe and the name defaults to the filename. It does not cover error handling or file limitations, but the provided behavioral context is valuable and accurate.

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 front-loaded with the core action, followed by necessary workflow context. All three sentences add value with no redundancy or filler.

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 description places the tool within the overall pipeline ('first step', 'quality_report') and mentions the active-dataframe side-effect, which is critical for using sibling tools. Since an output schema exists, return-value details are not required, though encoding or large-file behavior could enhance 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?

Schema description coverage is 0%, so the description must compensate. It explains the 'name' parameter's default behavior, but 'separator' is entirely undocumented and 'file_path' is only implicit. For a loader with three parameters, this is insufficient.

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 ('Load') and resource ('CSV file'), clearly distinguishing this from sibling loaders like load_excel and load_parquet. It also states its role as the first step in a pipeline, which differentiates it from other data operations.

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 explicitly says 'Always the first step in any pipeline' and advises running quality_report immediately after loading. It does not explicitly contrast with load_excel/load_parquet, but the clear 'CSV' scope and pipeline ordering provide strong usage guidance.

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