forget_preferences

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

No annotations are provided, so the description carries the full burden of disclosing behavior. It states that the learned model is wiped and that the summary returns to cold-start default, which is a meaningful side effect. However, it does not explicitly warn about irreversibility or data loss beyond the term 'wipe', nor does it mention any authorization requirements. The disclosure is adequate but not comprehensive.

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 concise sentence that front-loads the core action ('Wipe the learned model') and then qualifies the optional scope. There is no redundant information or fluff; every clause 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?

For a tool with one optional parameter and no output schema, the description covers the essential action, the optional parameter's effect, and a key side effect (summary reset). Given the simplicity of the tool, this is nearly complete. The only minor omission is an explicit statement about permanence, but 'wipe' strongly implies it, so the gap is small.

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 coverage is 100% and the parameter description in the schema already documents 'forget_history' clearly. The description adds minimal extra meaning by linking it to 'sets/history' in prose. This meets the baseline of 3 for high schema coverage, with no significant additional clarification provided.

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 'wipe' on the resource 'learned model' and clarifies an optional scope (sets/history). It clearly distinguishes from siblings like learn_preferences (which adds) and preference_summary (which reads) without naming them explicitly, but the intent is unambiguous.

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?

There is no explicit guidance on when to use this tool versus alternatives. The description implies a reset action but does not state when it is appropriate, when it should be avoided, or what prerequisites exist. The mention of 'optionally also sets/history' gives a condition but not a full usage context.

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