Propagate Column Change

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

Annotations indicate destructive and not readonly, but description adds extensive behavioral details: performs PUT requests for each downstream node, creates a disk snapshot for reversibility, invalidates cache, and explains partial failure handling. This goes well beyond annotations.

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?

Well-structured with front-loaded warning and purpose. Contains necessary detail without being overly verbose. A few sentences could be tightened, but overall efficient.

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 the tool's complexity (5 params, nested object, output schema), the description covers prerequisites, side effects, return values, error handling, and limitations like cache staleness. Very complete.

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 100% with detailed descriptions. The description's 'Args' section adds little beyond the schema, though it reinforces the required nature of changes. Overall, minimal added value for 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 clearly states it's a WRITE operation that updates all downstream columns depending on a source column, with specific use cases like renaming a column or changing data type. This clearly distinguishes it from sibling tools.

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?

Provides explicit context for when to use (after column rename/type change), and important prerequisites (lineage cache, staleness up to 30 min, need to refresh). Lacks explicit 'when not to use' but is otherwise clear.

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