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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says the tool 'returns readings for each word,' but does not explain whether it returns the full annotated text, how unknown words are handled, or what output format the default implies. This is a meaningful gap for a transformation tool with no annotation 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 two sentences with no filler. It front-loads the core action (adding furigana) and immediately gives the input/output relationship. Every sentence earns its place and the structure is easy for an agent to parse quickly.

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?

The description is adequate for a simple tool given the fully documented schema, but with no output schema it leaves the return shape somewhat ambiguous: does it return annotated text, a list of word-readings, or something else? It also does not mention default behavior for grade or output_format, though the schema covers those defaults implicitly. This is a clear but not severe completeness gap.

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 baseline is 3. The description does not add parameter-specific semantics beyond what the schema already provides, but it also does not need to compensate for undocumented parameters. The overall function description aligns with the text parameter, though it adds little for grade or output_format.

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 function with a specific verb and resource: it adds furigana (hiragana readings) to Japanese text. It also clarifies the expected input type (kanji-kana mixed text) and the output (readings for each word), making the purpose unambiguous even without siblings to differentiate from.

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 usage context: use this tool when you have Japanese kanji-kana mixed text and need furigana readings. There are no sibling tools and no explicit exclusions, but the input condition is stated directly enough for an agent to determine when to invoke it.

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