Food log

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

Although annotations already declare `readOnlyHint: true` and `destructiveHint: false`, the description adds valuable behavioral context: it explains the decryption happens locally (privacy implication), that the tool returns an optional `coverage` block with semantics for interpreting incomplete history, and warns against misreporting data extent. This goes well beyond the annotation hints, adding nuanced behavior about pagination and coverage.

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 well-structured with clear paragraph breaks: it starts with the core purpose, then details the data structure, and concludes with the important `coverage` guidance. Every sentence contributes practical value—there is no filler or repetition. The guidance on interpreting `coverage` is critical and front-loaded after the core purpose.

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?

Given the tool's complexity (nested structure with optional nutrition data, variable coverage), the description is thorough. It explains the data shape enough for an agent to sum or estimate, covers the `coverage` block semantics, and addresses pagination with `more_available`. Although there is an output schema, the description clarifies nuances not obvious from the schema alone.

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 description explicitly mentions `limit_days` as a way to cap the returned days, which adds semantics beyond the schema (which only lists it as an optional integer). However, the other two parameters (`fresh` and `limit`) are not described in the text. Since schema coverage is 0%, the description should ideally cover all parameters, but the primary parameter (`limit_days`) is addressed, earning a 4.

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 opens with an unambiguous statement of purpose: 'Decrypt recent daily food-intake logs locally (newest first).' The verb 'decrypt' plus the specific resource ('food-intake logs') makes the tool's function immediately clear. It distinguishes itself from siblings like get_notes and get_weight_trend by focusing on the food-log domain.

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 explicitly states 'Owner's own days only,' which is a clear scoping constraint. It also provides explicit instructions on how to use the 'coverage' block: quote `coverage.days_covered` for averages, watch for `window_satisfied: false`, and re-read with a larger limit when `more_available` is true. This level of operational guidance is exceptional.

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