rollback_to_snapshot

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

No annotations are provided, so the description carries the full burden, and it does the most important part: 'Alle Änderungen nach diesem Snapshot gehen verloren!' clearly marks this as a destructive, irreversible-in-practice mutation. It does not cover permissions/authorisation needs or whether the rollback can itself be reverted, so it falls short of complete disclosure.

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?

Front-loaded with the purpose and the loss warning in the first three lines; the Args block adds real value. The 'Returns: dict: Informationen über den Rollback' section is redundant given an output schema exists and is the only wasted sentence.

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 single-parameter mutation tool with an output schema (so return values need no prose), the description supplies purpose, destructive consequence, and parameter provenance. Minor gaps remain around authorisation and the state of the snapshot list after rollback, but nothing essential to correct invocation is missing.

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 must compensate, and it does: snapshot_index is defined as the snapshot's index and, critically, its provenance is given (obtained from get_dataset_history()). It does not describe indexing base or ordering, so it is not fully self-sufficient.

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?

States a specific verb and resource ('Stellt einen früheren Dataset-Zustand wieder her') and reinforces it with the 'wie Git-Reset' analogy, which cleanly separates it from the neighbouring take_snapshot (create), get_dataset_history (read history) and save_dataset (persist) tools. An agent can pick this tool without opening any schema.

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?

Gives clear context for use and a prerequisite: the snapshot_index comes from get_dataset_history(), so the agent knows what to call first. It also flags the condition of data loss. It stops short of explicit when-not guidance or naming an alternative tool for undoing the rollback itself.

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