run_query

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

With no annotations, the description carries the burden and does well: it declares read-only semantics, a hard 200-row cap, and that the response includes elapsed time and the exact SQL executed. It omits failure modes, timeouts, and whether the 200-row cap is silent truncation, which keeps it short of a 5.

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?

Three tight sentences: the operation first, then dialect/table-name rules, then return shape. Every sentence carries information an agent needs to construct a valid call, with no restatement of the tool name or filler.

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?

No output schema exists, and the description compensates by stating the return payload (up to 200 rows, timing, exact SQL). Combined with the dialect and cross-source join notes, an agent has everything needed to call this correctly without further context.

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 0% and the single 'sql' param has no schema description, so the description must compensate, and it does: it constrains the accepted statement types (SELECT, WITH, SHOW, DESCRIBE, EXPLAIN), names the dialect (Spark SQL), and specifies DATABASE.table qualification. What's missing is any guidance on parameterization or quoting of literals.

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?

States a specific verb and resource ('Run a read-only SQL query in Zetaris') and immediately scopes it with the allowed statement kinds. That verb-plus-statement-list framing separates it from discovery siblings like list_tables and describe_table without needing their schemas.

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?

It gives clear context for when this tool applies: read-only statements only, Spark SQL dialect, and cross-source joins are permitted. It never explicitly routes the agent away to list_databases/describe_table for schema discovery, so the alternatives are left implicit.

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