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

With no annotations, the description carries the full burden and does well: it discloses the fallback chain per language, the available engine values, and that forcing an unavailable engine raises an actionable install hint rather than being silently ignored. It does not describe return format, but an output schema exists.

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?

Front-loaded with the core purpose, followed by compact, language-specific engine guidance. The content earns its place, though the formatting with line breaks inside a JSON string is slightly awkward.

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 three simple parameters, an output schema, and no annotations, the description covers purpose, engine behavior, language dispatch, and error behavior adequately. Return values need not be explained because an output schema is present.

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 compensate. It adds substantial meaning for `lang` by explaining Chinese/English/other language dispatch, and for `engine` by listing accepted values and describing forced-engine error behavior. `text` is self-evident from its name.

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?

States a specific verb+resource: 'Named entity recognition with exact spans.' This is clearly distinct from siblings like pos_tag or tokenize, though it does not explicitly name or contrast with those alternatives.

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?

Provides clear guidance on engine selection per language (Chinese: stanza recommended, jieba fallback; English: spaCy then stanza; other: stanza) and notes forced engine behavior. However, it does not say when to use this tool versus sibling tools such as pos_tag or openie_triples.

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