df_update_git_connection

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

Annotations already establish that this is a destructive, non-read-only mutation. The description adds a small amount beyond that by saying 'WRITES TO DATAFORGE' and framing the operation as a full 'Replace' rather than a partial update. It does not, however, disclose what is overwritten, whether validation occurs, or what the response is.

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 two short sentences with no wasted words. The write-warning is front-loaded, and the actual action is clear. Every word earns its place.

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?

This is a complex write tool with 8 parameters, nested objects, no output schema, and many related sibling tools, but the description provides only a one-line definition. It is missing guidance on required connection_id, how authentication is supplied, and what 'replacing' means in practice. The annotations and schema carry the bulk of the context, which is not enough for a tool of this complexity.

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?

With schema description coverage at only 13%, the description needed to compensate by explaining key parameters or the overall configuration shape. It does not: 'configuration' is a catch-all with no detail about connection_id, authentication, settings, or repository fields. The sparse schema descriptions for authentication, token, and private_key carry the little parameter meaning that exists.

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 uses a specific verb and resource: 'Replace a saved Git connection's configuration.' This clearly distinguishes it from sibling tools like df_create_git_connection, df_delete_git_connection, and df_test_git_connection. The upfront 'WRITES TO DATAFORGE' also sets expectations that this is a mutation tool.

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 word 'saved' implies this tool is for modifying an existing connection rather than creating one, which provides weak usage context. However, it does not explicitly state when to use this tool versus alternatives like df_create_git_connection or df_test_git_connection, nor does it mention any preconditions or exclusions.

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