df_export_version_to_git

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

The description adds a key behavioral trait: exporting an unchanged version creates no commit and returns commit_hash=null, which is not captured in annotations. It also repeats the write warning 'WRITES TO DATAFORGE,' which aligns with readOnlyHint=false. However, it does not detail authentication handling, rate limits, or failure modes, so the added value is moderate.

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 four short sentences with no filler. The write warning is front-loaded, followed by the core purpose, then auth guidance, then a key behavioral note. Every sentence earns its place, and the structure is efficient.

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 tool with 10 parameters, nested objects, and no output schema. The description explains the purpose and one auth-related decision but omits return value details (beyond the null commit_hash case), the meaning of options, and the roles of repository_url, branch, and commit_message. An agent would need to inspect the schema heavily, and even then, some semantics remain unclear.

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 40%, the description compensates partially by clarifying that connection_id refers to a saved Git connection and that it is an alternative to the authentication object. This adds meaning beyond the bare schema. Yet it does not explain other required parameters like repository_url, branch, commit_message, or the options object, leaving significant gaps for a low-coverage schema.

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 verb 'Export' and the resource 'a version's configuration' with the destination 'to a Git repository.' It distinguishes this from sibling df_export_version_to_file by explicitly naming Git, and the phrase 'WRITES TO DATAFORGE' signals this is a mutating operation, consistent with the tool's write nature.

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 provides guidance on choosing between connection_id and authentication, which is helpful for parameter selection. However, it does not explicitly state when to use this tool versus alternatives like df_export_version_to_file, nor does it mention any exclusions or prerequisites. The usage context is implied but not explicit.

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