analyze_change

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

With no annotations, the description carries the full burden. It discloses that the tool sends data to an LLM and returns specific fields, which is useful behavioral context. However, it doesn't state whether the operation is read-only, its side effects, or any rate/authorization requirements.

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 one sentence, clear, and front-loaded with the action and outcome. Every word earns its place without repetition or unnecessary detail.

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?

The tool has no output schema or annotations, but the description compensates by enumerating the expected analysis fields. The input schema is fully described, and the description clarifies the purpose. Missing elements like explicit side-effect disclosure are minor given the tool's analytical nature.

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% for the two parameters (url, diff_text). The description adds no new parameter-level detail beyond what the schema already provides, so the baseline score 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 identifies the action ('send to an LLM') and the resource ('page diff') with a specific output ('business impact analysis'). It distinguishes itself from sibling tools like check_changes by emphasizing LLM-based impact analysis rather than simple diff detection.

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 implies clear usage context: use when you need business impact analysis of a page diff. It doesn't explicitly state when not to use or name alternatives, but the distinct function (analysis vs. monitoring/checking) provides sufficient guidance.

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