content_analyze

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

The description adds value beyond annotations by stating that the tool uses Gemini's structured output for reliable JSON responses and allows custom output_schema. It is transparent about behavior without contradicting the readOnlyHint and openWorldHint annotations.

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 concise, consisting of three short sentences that front-load the core purpose and then provide key usage details. Every sentence adds necessary information without redundancy.

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 of six parameters, no required fields, and the presence of a default output schema, the description adequately covers all essential aspects: content source selection, instruction flexibility, output customization, and thinking level. It is complete for an AI agent to use correctly.

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?

With 100% schema description coverage, the description still adds significant value by clarifying that content sources are mutually exclusive and explaining the purpose of output_schema and thinking_level, enhancing understanding beyond the schema alone.

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: analyze content from file, URL, or text with any instruction. It distinguishes from sibling tools like content_batch_analyze by focusing on single-item analysis and custom instructions.

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 explicitly instructs to provide exactly one of file_path, url, or text, and explains how to customize output with output_schema. It does not explicitly mention when not to use the tool, but the instructions are clear enough for typical use.

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