Generate CSVBox Sheet Functions

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

No annotations are present, so the description carries the full burden. It discloses that the tool does not call the API, omits unmentioned collections rather than returning empty arrays, returns a specific JSON shape, requires ANTHROPIC_API_KEY or OPENAI_API_KEY, and names the error fallback. This is unusually transparent.

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 dense but every sentence earns its place: purpose, non-API behavior, output contract, authentication requirement, error handling, and input shape. The structure front-loads the main purpose before moving to constraints and fallbacks.

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?

Even though there is no output schema, the description provides the return contract, omission behavior, auth prerequisites, and the downstream patch_sheet step. With only two parameters and one required, nothing essential is left for the agent to infer.

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 100%, so the schema already documents both parameters well. The description only restates the input shape as '{ prompt, sheet? }' and adds no new meaning beyond what the schema's per-parameter descriptions provide. Baseline 3 is appropriate.

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?

Uses a specific verb and resource ('Author CSVBox virtual_columns, validation_functions, and data_transforms') and clearly states it returns reviewable JSON rather than calling the CSVBox API. This distinguishes it from patch_sheet, create_sheet, and generate_import_code even before reading schemas.

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?

Establishes a clear workflow: generate functions, review the returned JSON, then apply with patch_sheet. It also says the tool does not call the API and warns about missing API keys, but it does not explicitly contrast itself with generation siblings like generate_sheet_json or generate_import_code.

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