add_item

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains that the AI should fill in reading, meaning, JLPT from its own knowledge, and put context into note. It does not mention return values or side effects beyond adding, but the expected behavior is well communicated.

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 paragraph that is front-loaded with purpose and provides detailed guidance without extraneous words. Each sentence adds value, though the structure could be improved with bullet points for clarity.

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 (8 parameters, 2 required) and no annotations, the description is fairly complete. It covers usage scenarios, parameter guidance, and edge cases (e.g., setting progress for known items). Missing details on output schema are acceptable as output schema exists separately.

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 parameter semantics. It adds meaning for reading, meaning, level, note, progress, and kind, covering most parameters except tags. This provides significant value beyond the bare schema.

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 'Add a Japanese grammar point or word', specifying the verb 'Add' and the resource 'Japanese grammar point or word'. It distinguishes itself from sibling tools like get_item by focusing on creation. The purpose is unambiguous and specific.

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 provides clear context for when to use the tool: 'the learner has just encountered' a word. It gives guidelines on handling known vs new items and how to set progress. However, it does not explicitly state when not to use the tool or mention alternatives among siblings, which prevents a higher score.

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