summarize_text

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively adds value by warning about costs ('⚠️ COST WARNING: This tool makes an API call to Whissle which may incur costs') and specifying the API provider (Whissle). It also mentions the return type ('TextContent with the summary'), which is helpful context beyond basic functionality.

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 appropriately sized and front-loaded, starting with the core purpose and cost warning. The parameter and return sections are clearly labeled. It could be slightly more concise by integrating the cost warning into the purpose statement, but overall, it avoids unnecessary fluff and each sentence adds value.

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 moderate complexity (3 parameters, no annotations, but with an output schema), the description is fairly complete. It covers purpose, usage warnings, parameters, and returns. The output schema exists, so the description doesn't need to detail return values. However, it lacks information on error handling or rate limits, which could be relevant for an API-based 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?

Schema description coverage is 0%, so the description must compensate. It lists all three parameters (content, model_name, instruction) with brief explanations, adding meaning beyond the bare schema. However, it doesn't provide details like format examples, model options beyond 'openai', or instruction usage scenarios, leaving some gaps in parameter understanding.

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: 'Summarize text using an LLM model.' This specifies the verb (summarize) and resource (text), making it distinct from sibling tools like translate_text or speech_to_text. However, it doesn't explicitly differentiate from potential non-sibling summarization tools, keeping it at a 4 rather than a 5.

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 clear context for when to use the tool: 'Only use when explicitly requested by the user.' This gives explicit guidance on user-driven usage. However, it doesn't mention when not to use it or name specific alternatives among the sibling tools, which prevents a perfect score.

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