Suggest Sql Attributes

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds useful context beyond that: candidates are mined from executed and verified queries, bridge tables, and column profiles, and include rules for judging them.

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 two tight sentences with no wasted wording. It front-loads what the tool returns and then names the follow-up save action directly.

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 a read-only candidate generator with an output schema and fully described parameters. The description covers what it produces, where candidates come from, and the next step, though it could more explicitly clarify when to choose it over sibling discovery tools.

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%, and all three parameters have clear descriptions in the input schema. The description does not add any meaning about the term, limit, or datasource parameters beyond what the schema already provides, so the baseline of 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?

The description clearly identifies the resource as candidate SQL attributes and specifies what they include: reusable measures, filters, join patterns. It distinguishes the tool from save_sql_attribute by directing the agent to save good candidates there, though it opens with a noun phrase rather than an explicit verb.

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 implies usage by saying to save the good candidates with save_sql_attribute, which gives a clear follow-up action. However, it does not explicitly state when to call this tool, when not to call it, or how it compares to alternatives like get_modeling_worklist.

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