create_datasource

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

No annotations are provided, so the description carries the full behavioral burden. It discloses key side effects: verification of the connection, auto-ingestion of models, environment variable substitution in credentials, and defaults like auto_ingest. It stops short of explaining failure behavior, whether an existing datasource is overwritten, or how connection_string interacts with individual credentials.

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 purpose is front-loaded in the first two sentences, followed by a compact Arg list and a useful invocation example. Every element earns its place: the summary, parameter explanations, constraints, defaults, and example. There is no redundant or filler content.

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?

Given the tool's complexity, the description is nearly complete: all parameters are explained, constraints are noted, and a concrete example is provided. It does not need to explain return values because an output schema exists. Minor gaps remain around credential precedence when connection_string is used alongside individual fields and the exact behavior when auto_ingest is false.

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%, but the description compensates fully by documenting all 12 parameters with additional meaning: supported type values, defaults, an example port, schema mutual exclusivity, and connection_string as an alternative. This goes well beyond the bare input schema and gives an agent what it needs to construct valid arguments.

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: 'Create a database connection, verify it, and auto-ingest models.' This clearly distinguishes it from sibling tools like list_datasources, edit_datasource, and ingest_datasource_models. It also lists supported database types, making the tool's scope unambiguous.

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 conveys when to use the tool: when creating a datasource and optionally ingesting models. It also provides parameter-level usage guidance, such as connection_string being an alternative to individual fields and schemas/schema_name/all_schemas being mutually exclusive. However, it does not explicitly name alternative tools or state when not to use it.

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