df_list_versions

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds no extra behavioral context, such as pagination behavior, cache semantics, or output limits, but it is consistent with the annotations.

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, front-loaded sentence with no filler. It is efficiently structured for its brevity, even though that brevity limits the amount of useful guidance it can convey.

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?

With no output schema and 0% parameter descriptions, this one-sentence description is not complete enough for an agent to fully understand the tool. Pagination, cache behavior, return format, and ordering/filtering rules are all left to inference; annotations cover safety but not these operational details.

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%, so the description carries the burden of explaining parameters. It only implies that project_id identifies the target project, and says nothing about page, page_size, or use_cache. Some meaning can be guessed from the parameter names and defaults, but the description does not add value beyond them.

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 the specific verb 'List' and identifies the resource as 'versions of a DataForge project,' making the core purpose clear. It is easily distinguished from sibling tools like df_create_version, df_update_version, and df_delete_version, though it does not explain what a version contains or what output to expect.

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 usage context is implied by the verb 'List': an agent can infer this is the tool for reading a project's version history. However, the description gives no explicit when-to-use guidance, no exclusions, and no mention of alternatives such as export/import version tools or lower-level get tools.

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