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

Annotations already mark the tool as read-only, idempotent, and non-destructive, so the description adds useful behavioral context rather than replacing the annotations. It adds that content is normalized to readable text and that comparison uses a baseline, plus the per-check cost of $0.03.

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 sentences, front-loaded with the core action and use case, and the price is the only extra detail. Every sentence contributes to an agent's ability to decide whether to call this tool.

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?

An output schema exists, so explaining return values is not required. Nevertheless, for a five-parameter tool with no parameter documentation, the description leaves unclear how baselines are stored or keyed, how focusTerms affects comparison, and what occurs when no baseline is provided.

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 0%, so the description needed to compensate for five undocumented parameters. It only implies url via 'fetch a public webpage' and vaguely refers to a baseline; focusTerms, baselineKey, saveBaseline, and previousContent receive no explanation.

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 operation: fetch a public webpage, normalize its readable text, and compare it with a caller-supplied baseline. This clearly distinguishes it from generic page fetchers and gives it a unique monitoring 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 explicitly says 'Use when an agent needs to fetch a public page and compare it with a previous baseline,' providing a clear trigger condition. However, it does not mention when to prefer semantically similar sibling tools such as semantic_web_diff, so the exclusion guidance is incomplete.

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