track_changes

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

The annotations declare readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the description doesn't need to re-state safety. It does add valuable behavioral context beyond annotations: webhook/scheduled monitoring support, hosted execution on CrawlForge's servers with email and signed webhooks, a cost of 3 credits, and that repeated compares are expected. It does not discuss rate limits, auth prerequisites, or result-size behavior in depth, so it falls just short of a 5.

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 front-loaded with the primary purpose, then workflow, then differentiation, then cost, then example. No sentence is wasted; it covers a complex tool efficiently in a compact block of text.

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 16 parameters, deep nested objects, and no output schema, the description does a good job covering the operational workflow and the hosted-versus-local distinction. It doesn't explain return shapes (acceptable since no output schema exists, though some hint of result format would help) and omits coverage of less-common operations like get_history, export_history, or create_alert_rule that appear in the schema union. Adequate for most calls but not exhaustive.

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 16 parameters in detail (including nested objects like monitoringOptions, scheduledMonitorOptions, trackingOptions). The description adds a small amount of meaning by naming two specific operations (create_baseline, compare) and the hosted option semantics, but largely repeats what the schema already provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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+resource: monitor a URL for content changes over time, with concrete use cases (competitor pricing, regulation updates, product availability). It explicitly distinguishes itself from the sibling 'scrape' by stating 'Not for a one-off read (scrape)', which is the key differentiator an agent needs.

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 explicit workflow guidance: start with operation:"create_baseline", then periodically use operation:"compare", and notes that repeated compare calls are expected. It also names the alternative for one-off reads ('scrape') and gives exclusion guidance, which is exactly the when-to-use/when-not-to-use clarity that helps an agent select correctly.

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