Save Example Query

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

Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, so the write-safety profile is covered. The description adds genuine context beyond that by explaining the downstream effect: verified examples feed get_query_context and get mined by suggest_sql_attributes, which tells an agent why the stored pair's accuracy matters.

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?

Two tightly written sentences, with the core action and its correctness precondition front-loaded and the downstream consequences following. Nothing is redundant with the title or schema.

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?

With four fully documented parameters, complete annotations, and an output schema, the description covers what an agent needs to decide to call it. The only small gap is that the idempotent behavior (what happens on re-saving an identical pair) is not mentioned.

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 every field (question, sql, note, datasource) is documented in the schema itself. The description adds no syntax, format, or constraint detail beyond that, so the baseline 3 applies.

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 verb and resource ('Store a question and SQL pair') along with the qualification that it must be user-confirmed as correct. It also names two downstream consumers, which distinguishes this save tool from siblings like get_context or suggest_sql_attributes that only read or mine examples.

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 condition for use is clear: only save pairs the user has confirmed as correct, which implicitly excludes speculative or unvalidated SQL. There is no explicit 'do not use when' clause or named alternative (e.g., validate_sql for unverified queries), so it stops short of full alternative routing.

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