summarize_content

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

With no annotations provided, the description bears the full burden of behavioral disclosure. It notes the requirement for an LLM provider API key and indicates that the tool uses an LLM for summarization. However, it does not disclose potential rate limits, costs, or failure modes, leaving some behavioral aspects opaque.

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 uses a docstring format with sections (Args, Returns), making it structured but slightly verbose. It front-loads the core purpose but adds extra formatting that could be trimmed. It is not overly long but could be more concise.

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 low schema coverage and absence of annotations, the description provides the essential parameter meanings and return type. It also mentions the critical API key dependency. However, it lacks constraints like maximum content length or edge cases, and the output schema existence lightens the burden but doesn't fully compensate for missing details.

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 0% (no descriptions in input schema), but the description adds meaningful explanations for both parameters: 'content' is the text to summarize, and 'context' is optional guidance with an example ('summarize as bullet points'). This compensates well for the missing schema descriptions.

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 function: 'Summarize content using LLM with optional context.' It specifies a specific verb-resource relationship and distinguishes from the sibling tool 'extract_content' which serves a different purpose.

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 mentions a prerequisite (API key configuration) but provides no guidance on when to use this tool versus alternatives, such as the sibling 'extract_content'. No explicit when-to-use or when-not-to-use guidance is given.

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