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

Annotations only mark readOnlyHint: true, but the description goes much further: it guarantees no write/create/modify, states that plan-to-change requests are refused, discloses auto-target behavior and the ambiguous_db edge case, and tells the agent it returns rows plus compiled SQL. This is rich, non-contradictory behavioral disclosure well beyond structured hints.

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?

Four sentences, all value-dense and front-loaded with the core purpose and safety guarantee. Each sentence delivers a distinct piece of actionable information — behavior, exception, db targeting, return format — without repetition. It is concise but not under-specified.

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 description is fully self-contained for a read-only natural-language query tool. It covers the safety contract, failure cases (ambiguous_db, no db, now database), model selection, and the exact return output (rows + compiled SQL). Given the lack of an output schema, this description effectively compensates by disclosing the return shape.

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 schema coverage is 100%, the description adds meaningful semantic context: `db` can be omitted to auto-target the only database, but with several it returns candidate IDs; `model`'s 'best' presets require specific account conditions; 'unique' is the default for nlqdb to choose. This goes beyond the schema's basic parameter docs, clarifying real usage nuances.

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 uses a specific verb+resource pattern: 'Read-only natural-language query over your agent's memory — SELECT / aggregate / JOIN over existing data.' It clearly distinguishes this from sibling nlqdb_query and from a generic list/connect tool by emphasizing it never writes. The tool's intent is immediately transparent.

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?

Explicit guidance is given: 'a request whose plan would change data is refused (use nlqdb_query for that), so this tool is safe to mark always allow.' It also explains when to pass `db` vs. auto-targeting and touches on ambiguous-database behavior. This leaves little ambiguity about when to use this tool versus alternatives.

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