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

With no annotations, the description carries the full burden. It mentions pricing (pay per call or subscription), which is a behavioral trait, but does not disclose other traits like synchronous execution, rate limits, or error handling.

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, with one sentence dedicated to the tool's purpose and another to pricing. It front-loads the core functionality, though pricing details could be relegated to annotations.

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 tool's complexity (analyzing multiple aspects) and lack of output schema, the description does not explain what results to expect (e.g., format, structure). This leaves the agent uncertain about how to handle the output.

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 coverage is 100% (one parameter with description). The tool description adds meaning by listing the analysis types (summary, sentiment, etc.) but does not elaborate on each parameter beyond what the schema already provides.

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 explicitly states that the tool analyzes text for summary, sentiment, entities, topics, and classification. This clearly defines the verb and resource, and distinguishes it from siblings like sentiment_over_time which focuses only on sentiment over time.

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 its siblings. It only mentions pricing, not usage context or exclusions. Siblings like extract_content or research_topic might overlap in purpose but are not compared.

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