analyze_content

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

With no annotations, the description carries the full burden of behavioral disclosure. It does not state whether the operation is read-only, whether it can accept arbitrary text vs. stored content, or what side effects (if any) occur. The phrase 'analyze web3 content' is a purpose statement, not a behavioral disclosure.

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, front-loaded sentence that clearly communicates the tool's function without any filler or redundant phrasing. It is appropriately sized and well-structured.

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 tool has three optional parameters and no output schema or annotations. The description covers the core purpose but omits important context such as how to choose between text and content_id, what the output structure looks like, and any usage disclaimers. It is minimal but not completely inadequate for a simple analysis tool.

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?

The schema already provides 100% coverage of the three parameters, so the baseline is 3. The description adds some context by mapping 'key insights, sentiment, and topics' to the analysis_type values, but it does not clarify the relationship between 'text' and 'content_id' or when to use each. Thus, it adds marginal value beyond the schema.

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 analyzes web3 content and specifies the output dimensions: key insights, sentiment, and topics. The verb 'analyze' is specific and distinguishes this tool from siblings like 'get_article' or 'search_content', which focus on retrieval rather than analysis.

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 does not mention prerequisites, exclusions, or how it differs from content retrieval tools. The sibling list includes many content-related tools, but the description offers no situational context for choosing analyze_content.

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