telemetry
Verified-crawler traffic observed at crawlcheck.io itself: which named agents arrived, how many claims were confirmed against operator ranges, how many were forged.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Verified-crawler traffic observed at crawlcheck.io itself: which named agents arrived, how many claims were confirmed against operator ranges, how many were forged.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is fully carried by structured data. The description adds the substantive nature of the payload (agent names, claim confirmations, forgery counts), which is useful, but it does not disclose the aggregation window, snapshot freshness, or whether 'forged' counts are estimates.
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?
A single sentence with the resource scoped up front and the three content categories listed compactly. It is efficient and front-loaded, though the colon-list structure reads slightly like a clipped note rather than a polished definition.
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?
With no parameters and no output schema, the description must carry the entire burden of telling the agent what it gets back, and it does list the three data categories. However, it omits the time window, update cadence, and scope limits (e.g., is 'at crawlcheck.io itself' a fixed self-sample?) that an agent needs to interpret the counts correctly.
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?
The tool takes zero parameters, so per the rubric this is a baseline 4. Nothing in the description adds parameter meaning, but none is needed.
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 data resource (verified-crawler traffic at crawlcheck.io) and enumerates its contents: named agents, confirmed claims against operator ranges, and forged claims. It contrasts implicitly with siblings like verify_crawler_log, but there is no verb or framing ('report') to signal that this is a self-telemetry summary rather than a query tool.
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?
No when-to-use guidance is given, and no alternative is named. An agent cannot tell from the description when telemetry is preferable to public_counts, corpus_state, or verify_crawler_log, all of which plausibly overlap in subject matter.
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.