anki_fields

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 states what the tool does but lacks details on behavioral traits such as error handling, rate limits, authentication needs, or what happens if inputs are invalid. For a tool with 5 parameters and no annotations, this is a significant gap in transparency.

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, efficient sentence in Japanese that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance. Every part of the sentence earns its place by clearly conveying the core function.

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 complexity (5 parameters, no output schema, no annotations), the description is minimally complete. It states what the tool does but lacks context on how it behaves, what it returns, or how to interpret results. Without annotations or an output schema, the description should provide more guidance on usage and outcomes, but it only covers the basic purpose, leaving gaps for an AI agent.

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 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain how 'text' is processed or what 'markers' represent in practice). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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's purpose: 'テキストからAnkiカード用のフィールドデータを生成する' (Generate Anki card field data from text). It specifies the verb ('generate') and resource ('Anki card field data'), making the function unambiguous. However, it doesn't distinguish this tool from its siblings (kanji, lookup, status, tokenize), which appear to be related but serve different purposes.

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 no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or comparisons with sibling tools (e.g., when to use 'anki_fields' vs. 'lookup' or 'kanji'). Usage is implied only by the tool's name and description, with no explicit context for selection.

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