clean_replace

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

No annotations are provided, so the description carries full burden. It discloses the key behavioral detail that JSON null maps to SQL NULL, and implies a new source is created rather than modifying the input. However, it does not specify behavior for unmapped values or case sensitivity.

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, front-loaded with the core purpose, and uses a clear example to illustrate null mapping. Every sentence adds value without any 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?

The tool is relatively simple and an output schema exists, so return values do not need explanation. The description covers the main purpose and the important NULL mapping behavior, but could optionally mention how unmapped values are handled. Overall, it is sufficiently complete for a data cleaning operation.

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 adds meaningful semantics for the 'mapping' parameter with an example and explains null mapping. However, source_id, column, and alias are not explained beyond their names, leaving some parameter semantics to inference.

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 that it creates a new source with column values replaced per mapping, which is a specific verb+resource+operation. This distinguishes it from sibling clean_* tools like clean_filter or clean_impute by specifying the exact transformation (value replacement).

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 provides a clear use case: removing sentinel values like 'NA' or -999 by mapping them to SQL NULL. This implies when to use the tool, but it does not explicitly mention when not to use it or name alternative tools. Still, the context is clear.

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