superset_database_update

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

No annotations are provided, so the description carries the burden. It discloses a critical behavioral consequence: 'changing the URI breaks all datasets and charts using this connection.' It also highlights that confirm_uri_change is REQUIRED when changing sqlalchemy_uri. These are valuable transparency details beyond the basic update operation, though it doesn't cover other potential side effects like permissions or irreversibility.

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 structured as a clean docstring with an initial summary and a flat list of parameters. It is longer than a one-liner but every line serves a purpose—parameter explanations and critical warnings. The front-loaded main sentence makes the tool's purpose immediately clear.

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?

Despite having zero schema coverage, the description fully covers all 9 parameters, including the special verification flag. It also explains the severe impact of URI changes and confirms the minimal required input (database_id). Since an output schema exists, return-value details are not needed. The tool is complex, and this description provides sufficient context for correct invocation.

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 0%, so the description compensates fully. It provides meaningful explanations for all nine parameters, including pragmatic details like 'Whether to show in SQL Lab' and 'Allow CREATE TABLE AS SELECT.' The critical warning about sqlalchemy_uri and the requirement for confirm_uri_change add significant semantic value beyond the raw schema field names.

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 starts with a clear verb-action sentence: 'Update a database connection.' It explicitly names the resource and the operation, and adds scope with 'Pass only the fields you want to change.' This differentiates it from sibling tools like create, delete, and get.

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 implies when to use this tool: when you need to modify an existing database connection, and it requires database_id. It doesn't explicitly mention alternatives or exclusions, but the context and required parameter make the usage unambiguous. It also instructs to pass only changed fields, which is a practical usage guideline.

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