save_override

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 behavioral disclosure. It discloses that the correction is permanent, that every future lookup short-circuits to it, that it is user-scoped, that the server fetches the real USDA description, and that the note is the only record of the correction's rationale. This is strong transparency about side effects and persistence.

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 dense but well-structured: core action and trigger first, then parameter rules, then persistence behavior. Each sentence adds necessary information with no filler, and the most important usage guidance is front-loaded.

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?

Despite having no annotations and no output schema, the description covers the tool's purpose, when to use it, what each parameter means, required constraints, and the lasting side effects. An agent has enough information to select and invoke the tool correctly without needing additional context.

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 explain parameters, and it does thoroughly: fdc_id fixes food resolution, grams fixes count mass, phrase must be the exact amount-style phrase used with get_nutrition, and note is the rationale. It even explains why the phrase exactness matters, which is critical for correct invocation.

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 states a specific action ('permanently correct'), a clear resource ('what a phrase means or what a count weighs'), and a scope ('for this user'). It also gives the triggering condition ('lookup's summary flags something as wrong or low-confidence'), which distinguishes it from siblings like get_nutrition, search_foods, and save_recipe.

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?

It explicitly says when to use the tool: when a lookup summary flags something wrong or low-confidence and the user provides the correct answer. It also gives important constraints, such as not supplying your own description and using the exact count phrase for grams. It does not explicitly contrast with alternative sibling tools, but the intended usage context is unmistakable.

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