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 transparently states what the tool does (extracts readable text, removes ads/navigation), its best-use scenarios (articles, blogs, docs), and its limitations (may not work with JS-rendered or login pages). It also mentions the maxChars parameter for controlling output size. However, it doesn't explicitly state that it is a read-only operation (though implied) or describe error handling, so it's not perfect.

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 structured as a use_case and important_notes, with the purpose stated upfront. It uses bullet points for key notes, making it scannable. Every sentence contributes value—purpose, usage context, and limitations—with no filler. It is concise yet complete.

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?

For a simple two-parameter tool with no output schema, the description covers all necessary information: what it does, when to use it, limitations, and a parameter tip. It explains the tool's behavior and constraints sufficiently for an agent to use it correctly without additional context.

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 100%, so the schema already documents both url and maxChars with clear meanings. The description adds a small usage hint ('Use maxChars to limit returned content length for large pages') but doesn't provide additional semantics beyond what the schema already conveys. This meets the baseline of 3.

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 a specific verb and resource: 'Fetch and extract the main text content from a webpage.' It clearly distinguishes itself from the sibling webSearch (which returns search results) by focusing on reading full content of a specific URL. It also specifies what it extracts (readable article text) and what it removes (ads, navigation), making the purpose unmistakable.

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?

Explicitly provides usage context: 'Use this tool after webSearch to read the full content of a specific URL, or when given a direct URL to analyze.' It also notes limitations (JS-rendered pages, login pages) that guide when to avoid it. While it doesn't explicitly name alternative tools for those cases, the guidance is clear and actionable, earning a 4.

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

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

With no annotations, the description carries the full burden and handles it well. It discloses that no API key is required, that results include title/URL/snippet, that the region parameter affects result localization, and that fetchWebContent should be used for full page content. This gives an agent a realistic picture of behavior and output.

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 well-structured with a use-case block and important notes. It is concise, front-loads the core purpose, and every sentence provides useful operational detail without unnecessary filler.

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?

For a straightforward search tool with no output schema, the description covers what an agent needs: engine, auth requirements, result contents, region behavior, result limits, and the natural next step to fetch full content. No critical operational gap is apparent.

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 100%, so the schema already documents all three parameters. The description adds minimal new meaning: it repeats the region example and reinforces maxResults behavior, but does not substantially extend the schema's parameter documentation. Baseline 3 is appropriate.

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 a specific action ('Search the web using DuckDuckGo') and clearly identifies what the tool does. It also names the intended use cases ('current information, news, documentation, or answers'), making the purpose unambiguous and easy to distinguish from the sibling fetchWebContent.

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 explicitly says when to use the tool and gives a clear follow-up action: use fetchWebContent after getting results. It stops short of explicitly saying when NOT to use this tool versus fetchWebContent, so it misses the top-tier score, but the guidance is otherwise clear.

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