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 disclose the return format and the extractive nature, but it does not explain how importance is determined, whether the output is stable, or any limitations regarding text length or language. Some behavioral context is added, but gaps remain.

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 two sentences with no wasted words. It front-loads the core purpose ('Extractive summarization') and immediately follows with the key output format. This is concise 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?

Given the tool's simplicity (2 parameters, no output schema, no annotations), the description provides the essential purpose and return shape, which is largely sufficient. However, it misses explicit parameter explanations and usage guidance, preventing a perfect score.

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. However, it only mentions 'most important sentences' and the return fields, but does not explain the roles of 'text' or 'max_sentences'. The schema provides only names and a default, so the description adds no meaningful parameter semantics.

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 states 'Extractive summarization — picks most important sentences,' which clearly defines the tool's purpose with a specific verb ('picks') and resource (sentences). It distinguishes from sibling tools like analyze_sentiment and extract_keywords by specifying extractive summarization as the unique function.

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 implies the tool is for generating summaries by selecting important sentences, but it does not provide explicit guidance on when to use this tool over alternatives or when not to use it. No exclusions or alternative recommendations are mentioned, leaving the usage context implicit.

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