ai.summarize

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

With no annotations, the description carries full burden. It mentions 'Backed by an upstream LLM,' hinting at potential latency or cost, and outlines output structure but does not disclose error handling, rate limits, or behaviors for inaccessible webpages. This is adequate but not thorough.

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?

Two sentences: first states purpose, second lists outputs and backend. Front-loaded, no wasted words, efficient for quick comprehension.

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 no output schema and no annotations, the description covers core output elements (summary, key points, etc.) and the LLM backend. It is reasonably complete for a straightforward summarization tool, though it could mention handling of restricted pages or parameter interactions.

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 50% (only instruction has a description). The description compensates by explaining the url parameter is for a webpage URL, and instruction is described as 'Optional steering hint.' However, the hint is vague and could be more specific about how steering works.

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 'Summarize a webpage' and lists specific return items (summary, key points, title, audience, reading time), making the tool's exact purpose unambiguous. It distinguishes from siblings like ai.extract or ai.describe-image by focusing on summarization of webpages.

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?

No guidance is provided on when to use this tool versus alternatives like ai.extract. The description lacks any when-to-use or when-not-to-use instructions, leaving the agent without context for selection.

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