log_note

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

With no annotations, the description must carry the behavioral burden. It indicates a write operation ('기록한다' = records) and clarifies that observations are left as-is, but does not disclose return behavior, permissions, or mutability. It is not misleading, but incomplete.

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 two sentences, front-loaded with the purpose and followed by clarifying examples. No wasted words; every part 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?

While the output schema covers return values, the description lacks essential context about the 'name' parameter referring to an existing plant and when to use this vs log_watering. It is adequate for a simple note logger but has clear gaps in the broader tool ecosystem.

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%, and the description only provides context for the 'note' parameter via examples. The 'name' parameter is not explained as the plant identifier, and 'noted_on' is completely unaddressed. The description fails to compensate for the lack of schema documentation.

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 clearly states the tool records plant state changes, with explicit examples of observation content. It distinguishes itself from sibling tools like log_watering by focusing on observational notes rather than watering events.

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?

Usage is implied through the examples and context (plant observations vs watering), but no explicit when-to-use or alternative tool references are provided. The description lacks direct guidance on when to choose this over log_watering.

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