changes_sinceOnly what changed since your last call: prefixes added or removed, upstreams failed or recovered, records edited. Send back the cursor from the previous result; it advances only on a real change, and the data refreshes every 6h. Example: since='0'.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Events per page, default 100. | |
| since | No | Cursor from the last result, or an ISO date. Omit for all retained. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds valuable non-obvious behavior: the cursor advances only on real change and data refreshes every 6h. 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?
Three short sentences, each carrying distinct information: the scope of changes, the cursor contract, and an example. No filler or repetition of the parameter schema.
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's behavior, input, and refresh model are described well enough to call it correctly even without an output schema. A minor gap is that the description implicitly relies on the response containing a new cursor, but it does not explicitly confirm the response shape.
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 adds extra meaning beyond the schema by explaining how the cursor behaves (advances only on real change) and giving a concrete example for the 'since' parameter.
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 names a specific operation ('Only what changed since your last call') and lists concrete change types (prefixes, upstreams, records), making the tool's purpose unambiguous. It clearly distinguishes from sibling listing tools like list_crawlers and lookup_crawler.
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?
It gives direct usage guidance: send back the cursor from the previous result, and shows an example (since='0'). It does not explicitly state when to prefer this over the sibling whats_changed, but the cursor-based incremental pattern is clearly conveyed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct action: classifying user-agent strings, verifying IP addresses, listing, looking up, generating robots.txt, and checking data freshness. The explicit cross-reference between classify_user_agent and is_verified_crawler_ip clarifies rather than blurs their boundaries.
Almost all tool names follow a predictable snake_case verb_noun pattern such as classify_user_agent, list_crawlers, and lookup_crawler. whats_changed deviates slightly from the verb_noun style but remains consistent in lowercase snake_case, so the naming is mostly coherent.
Six tools is a well-scoped set for a crawler index service. Each tool covers a distinct need without overlapping or unnecessary additions.
The tool surface covers the full workflow for understanding and managing crawler data: discovery, identification via UA or IP, detail lookup, robots.txt generation, and freshness monitoring. No obvious dead ends or missing operations for the stated purpose.