score_url

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 explains the return type (0-100 score plus a list of penalties, benefits, and recommendations) and the underlying purpose (evaluating AI-readability). It implies a safe read-only operation ('Get') and adds context about the score's meaning. It could mention URL accessibility or error handling, but the core behavior is well disclosed.

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 clean sentences. The first sentence front-loads the core purpose and output, the second immediately gives the usage context. No filler or redundancy—every sentence earns its place.

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 single-parameter tool with no output schema, the description covers essential aspects: what it does, what it returns, and when to use it. It explains the return structure in enough detail for an agent to understand the output. It doesn't address error cases (e.g., invalid/unreachable URLs) or prerequisites, but given the low complexity, the description is nearly 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?

The schema already provides full coverage for the only parameter: 'url' is described as 'The URL to score.' The description adds minimal extra meaning beyond confirming the URL is what gets scored, and it doesn't specify format restrictions or examples. Since schema coverage is 100%, a baseline of 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 clearly states the tool's function: 'Get the AIO (AI-readability) score for any URL.' It specifies the resource (URL) and the action (get score), and distinguishes itself from siblings like read_url by focusing solely on scoring. It also previews the output (0-100 score plus penalties/benefits/recommendations), 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?

The description provides clear usage context: 'Use this to evaluate source quality before relying on it.' This tells the agent when to invoke the tool. While it doesn't explicitly name alternatives or exclusions, the context differentiates it from read_url or read_and_score by implying that scoring alone is sufficient for quality evaluation. A minor gap is not mentioning when not to use it, hence 4.

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