tigergraph__create_data_source

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

Annotations indicate this is a write operation (readOnlyHint=false, destructiveHint=false), but the description adds no additional behavioral context beyond the schema's hints—no mention of idempotency, potential side effects, or authorization requirements. While the description mentions server rejection, it doesn't cover failure modes or partial states. With annotations already covering safety profile, the description adds some value (server rejection behavior), but not rich depth.

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 a single, information-dense sentence that front-loads the core purpose and lists supported sources efficiently. It could be slightly more structured, but it is concise and avoids 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?

For a tool with no output schema and complex type-specific configuration, the description, combined with the schema's parameter details, provides sufficient guidance for invocation. It includes cross-references to sibling tools for further detail, covering the main gap (type-specific keys) without overloading the description. The only minor omission is a concrete example, but that is delegated appropriately.

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 schema already provides detailed descriptions for all parameters, including type-specific config keys and profile guidance. The description adds minimal extra value beyond reinforcing the need to call get_data_source_types. Baseline of 3 is appropriate since schema carries the load.

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 clearly states the action (create a new data source) and the resource (data source), and enumerates the supported sources (S3, GCS, Azure Blob, Snowflake, etc.). It distinguishes itself from sibling tools like update_data_source and get_data_source_types, and even references the latter for guidance.

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 explicitly instructs to call 'get_data_source_types' first if unsure about required keys, providing a clear alternative for usage. It also hints at behavior on server rejection (response includes required keys), giving practical guidance.

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