run_query

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

No annotations are present, so the description carries the burden of behavioral disclosure. It usefully discloses return formats (TSV for MySQL, JSON for MongoDB) and the schema-qualification requirement, but it does not mention whether writes are permitted, authentication needs, or error behavior. This is adequate but not comprehensive for a raw-query tool.

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 compact and well-structured: it states the core purpose first, then gives dialect-specific requirements and output formats. Every sentence contributes necessary information without redundancy.

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 no output schema, the description appropriately explains return formats. It also covers the main complexity of the tool, the two query dialects and their syntax constraints. It does not cover side effects or how the server type is determined, but this is a minor gap for a query-execution tool.

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%, so the baseline is 3. The description adds meaningful value by explaining what kinds of query text are valid and what the required syntax looks like for each dialect, going beyond the schema's generic 'SQL or MongoDB query text'.

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 names a specific action (run a query) and a specific resource (a database server), and immediately distinguishes the two supported dialects: MySQL and MongoDB. Its scope is clearly different from sibling metadata tools like list_databases, get_schemas, and get_tables.

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 gives concrete conditions for both dialects: MySQL queries must start with 'use <schema>;' or use schema-qualified names, and MongoDB queries use db.collection.find()/aggregate() style. It does not explicitly name alternatives or exclusion criteria, but the context is clear enough for an agent to know when this tool is appropriate.

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