track_changes

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

Annotations already indicate this is not read-only and is open-world. The description adds the workflow context but does not disclose behavioral traits like what data is stored, authentication needs, or rate limits. No contradiction with annotations.

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 concise (~60 words) and front-loaded with the main purpose. It contains only relevant information, with no wasted words. The structure is clear and easy to parse.

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 the tool's complexity (13 parameters, nested objects, many operations), the description only covers basic usage. It does not explain advanced operations or return values. However, the schema descriptions are thorough, partially compensating. The description is adequate for simple use cases but incomplete for advanced ones.

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 provides a usage example (url + operation) but adds no semantic value beyond the schema's parameter descriptions. The schema already explains each parameter thoroughly.

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 monitors a URL for content changes over time, provides concrete examples like competitor pricing, and distinguishes from sibling scraping tools by emphasizing temporal monitoring. The verb 'monitor' and resource 'URL content changes' are specific.

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 gives explicit workflow guidance: start with 'create_baseline', then use 'compare'. It also mentions support for webhooks and scheduled monitoring. However, it does not explicitly state when not to use this tool or list alternatives beyond the implicit sibling set.

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