content-analyze

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

No annotations are provided, so the description carries the full burden. It discloses that the tool fetches a URL, extracts article text, and returns specific data fields, plus cost. However, it does not mention failure modes (e.g., non-article URLs), rate limits, or authentication requirements. The behavioral picture is decent but incomplete.

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?

Three sentences: first states purpose, second lists output specifics, third gives use cases and cost. No wasted words, front-loaded with essential information. Highly efficient.

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, the description thoroughly enumerates return fields (summary, key points, entities, sentiment, topics, classification, credibility). It covers cost and typical use cases. Missing are constraints (e.g., URL type limitations, content length caps) but for a single-purpose analysis tool, this is quite complete.

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%, so the baseline is 3. The description adds minimal context: it repeats the schema descriptions for 'url' and 'focus' but does not provide additional details beyond examples. The focus parameter's description ('Narrows the analysis') adds slight value, but overall the description does not significantly surpass the schema.

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 it performs AI-powered URL content analysis, fetching a URL and extracting article text to return structured intelligence. It lists specific outputs (summary, key points, entities, sentiment, etc.), which distinguishes it from general web scraping or page fetching tools.

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 use cases ('content intelligence pipelines, research synthesis, or automated brief generation') but does not explicitly contrast with sibling tools like 'readable-content' or 'page-intel', nor does it specify when not to use this tool. The guidance is adequate but lacks exclusions or alternative recommendations.

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