clean_drop_columns

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

With no annotations provided, the description carries the burden and does well by disclosing that the original is preserved, the new source is auto-named, and the return includes deltas and a replayable Recipe. It does not cover edge cases like missing columns, but the key behavioral traits are 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 compact and front-loaded: the first sentence states the core behavior, and the second details return values. Every sentence earns its place without redundant 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 is reasonably complete for a moderate-complexity transformation tool: it covers the non-destructive behavior, naming scheme, and return values. Given an output schema exists, this is sufficient, though it could add details on error handling or column existence checks.

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 the description must compensate. It explains that `columns` are the named columns to drop and clarifies the `alias` behavior (auto-naming `{source}_v{N}` unless alias is given). This adds meaningful semantics beyond the bare parameter names.

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's function: it drops named columns and creates a new source, distinct from siblings like clean_drop_duplicates and clean_rename. It also specifies the non-destructive nature ('Original is preserved') and the result type.

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?

Usage is implied rather than explicitly stated—the tool is for dropping columns, and preserving the original offers context. However, it does not name alternative tools or provide when-not-to-use guidance, so the agent must infer the right context from the purpose.

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