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

With no annotations, the description carries the burden of behavioral disclosure. It clearly explains that the data is a before/after diff from the index's own requests and cannot be reconstructed from public sources. This is meaningful provenance information beyond the schema.

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 compact, front-loaded with the core 'what changed' purpose, and every sentence adds value: the uniqueness explanation and concrete use cases are both useful. No filler or repetition.

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 description covers the output semantics well for a tool with no output schema: domains, flip day, and robots.txt/edge distinction. The only minor gap is that 'a specific AI crawler' is mentioned but the input schema has no crawler parameter, leaving some ambiguity about how the agent selects which crawler's changes are returned.

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 days, host, and limit. The description adds no new parameter-level details, which is fine because the baseline of 3 applies when the schema covers all parameters.

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 exactly what the tool does: it reports domains that recently started or stopped blocking a specific AI crawler, when the flip was observed, and whether the change was in robots.txt or at the edge. This is specific enough to distinguish it from sibling tools focused on static readiness or blocking state.

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 use cases: answering 'who just blocked/unblocked ChatGPT, Claude, Perplexity...' and watching a single domain over time. It does not explicitly name alternatives or exclusions, but the intended context is clear.

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