Language.Analyze Entities

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

No annotations are provided, so the description carries the full burden. It does disclose a genuine behavioral trait, that calls incur Cloud Natural Language API cost, which is useful for an agent deciding whether to call. It says nothing about input length limits, language support, or latency, and with an output schema present the return shape is already covered.

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?

Two short sentences, front-loaded with the operation and followed by the cost caveat. No waste, though the second sentence could be folded in for even tighter structure.

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?

Output schema covers return values, and the cost note adds real value. But for a tool whose only parameter is completely undocumented in the schema, the description leaves the agent without enough information to prepare a correct call.

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% for the single required 'text' parameter, so the schema gives no meaning at all. The description does not compensate — it never says what form the text should take (ad copy, landing page, raw snippet), whether there are length limits, or what languages are supported.

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 and resource ('Extract salient entities') and scopes it to ad content, which distinguishes it from siblings like language.analyze_sentiment and language.detect_language. Not fully 5 because it doesn't explicitly contrast with those siblings by name.

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 phrase 'from ad content' implies the intended use case, and the cost warning implicitly discourages frivolous calls. However, there is no explicit when-to-use vs. analyze_sentiment guidance and no stated exclusions.

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