fusion_docs_search_columns

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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds valuable behavior beyond that: it searches a local snapshot, matches both column names and descriptions, combines words with AND, and warns that live-pod existence verification is needed before execution.

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 well-structured and front-loaded with the core purpose. The example, caveat, and argument explanations all earn their place without excessive verbosity. It remains tightly scannable while conveying meaning.

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 output schema and annotations, the description covers everything necessary: source of data, matching semantics, parameter meanings, and a key caveat about verifying existence on the live pod. There are no material gaps for an agent to call this correctly.

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?

Although input schema description coverage is 0%, the description fully compensates by explaining both parameters: term as AND-combined words or a column-name fragment, and limit as the maximum number of matches returned. This is exactly the semantic detail an agent needs.

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 states a specific action and resource: searching columns across ALL documented tables by name or business meaning. It is clearly differentiated from the live sibling tool fusion_search_columns by emphasizing the local docs snapshot and discovery-focused use case.

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 directs when to use this tool: prefer it over fusion_search_columns for discovery and then verify existence on the pod when executing. It also gives a concrete example of search intent, making the usage context unmistakable.

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