Query Rapid7 Data

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered without description support. The description adds meaningful behavioral context beyond annotations: the SQL dialect is DuckDB, the data originates from Rapid7 InsightVM Bulk Export Parquet files, and arbitrary SQL filtering/aggregation/joining is allowed. It does not mention query limits or performance caveats, but the annotation coverage lowers the burden.

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 long, but every section earns its place: the first sentence states the core capability, the table and field listings are directly needed for constructing valid SQL, and the examples illustrate expected usage. It is well-structured with clear headings and front-loaded purpose.

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?

For a SQL-query tool, the description is complete: it names the database, enumerates every table and key field, explains that DuckDB SQL is supported, and provides concrete examples. The presence of an output schema means return-value documentation is unnecessary, and the annotations cover the tool's read-only, idempotent nature.

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 the schema already describes the single 'sql' parameter, the description dramatically expands its meaning by listing all valid tables, their key columns, and four concrete example queries. This tells the agent exactly what kinds of SQL statements are acceptable and what data surfaces exist, going far beyond the schema's one-line description.

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 opens with a specific action and resource: 'Execute a SQL query against the Rapid7 database.' It then enumerates the exact queryable tables and their key fields, which clearly distinguishes this tool from siblings that load, export, or manage Rapid7 data. The purpose is unmistakable and fully scoped.

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 clearly states when to use the tool: 'Use this tool to query any of the above tables,' and shows realistic analytic examples. However, it does not explicitly name sibling tools or state when not to use it, leaving some alternative-selection reasoning to the agent. The context is strong but not fully explicit.

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