df_export_version_to_file

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

Annotations only state that the tool is non-read-only, non-idempotent, and non-destructive. The description adds important side-effect context: it writes/stores an archive in DataForge while leaving the project data unchanged, and returns a signed download link. This goes beyond the annotation booleans, though it omits details such as link expiry or authentication requirements.

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 compact sentences with no filler. The side-effect warning is front-loaded, and the second sentence efficiently captures both the storage behavior and the output format. Every sentence contributes useful information.

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 tool has a nested options object with 11 undocumented properties and no output schema, yet the description only provides the output format and a side-effect note. The required parameters are clear, but an agent would still need to guess about option semantics and when to use this over related tools. The context is incomplete for the tool's 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?

The schema gives minimal descriptions for project_id and version_id, but the tool description itself adds nothing about parameters. The options object and its 11 nested properties are entirely undocumented, leaving ambiguous fields like use_system_key, save_connection, and encryption_password unexplained. With schema coverage at about 67% and no descriptive compensation, the parameter guidance is inadequate.

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 names a specific action and resource: 'Export a version to a .dfexport.zip archive and return a signed download link.' The archive format and download-link output clearly distinguish this from the git-export sibling and other DataForge tools. The note that nothing changes in DataForge further clarifies the tool's scope.

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 implies the use case: exporting a version as a downloadable file archive. However, it does not explicitly state when to prefer this over df_export_version_to_git or other alternatives, nor does it provide any exclusions. An agent must infer the right choice from the '.dfexport.zip' format and 'signed download link' outcome.

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