One sample per 20-minute monitor sweep. uptime_pct is the share of
sweeps in which every fail point was green (the strictest read);
per_monitor lists only monitors that failed at least once in the
window. History begins at feature deploy and is never extrapolated
backwards — an empty window returns uptime_pct: null, not 100.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses key behavioral traits: 20-minute sweep sampling, metric definitions, that history starts at feature deploy, no backward extrapolation, and null handling for empty windows. This exceeds expectations for a simple status tool.
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 three sentences long, each packed with essential information. It front-loads the sampling rate and clearly explains metrics and edge cases. No redundant 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?
For a tool with no output schema and one parameter, the description covers output semantics and edge cases well. However, it omits explanation of the 'days' parameter, which is needed for full completeness. Despite this, the core behavior is well described.
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 input schema has one parameter (days) with 0% coverage in the description. The description does not mention this parameter at all, leaving its purpose (likely the history window length) unexplained. This is a significant gap given low schema coverage.
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 defines the tool's purpose: it provides historical status data with specific metrics (uptime_pct and per_monitor) sampled every 20 minutes. The resource (status history) and the action (retrieval) are well implied, and the tool is distinct from siblings like lookup or compliance tools.
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 explicit guidance is given on when to use this tool versus alternatives, nor are there any exclusions or prerequisites. The context of siblings includes many unrelated tools, but the description fails to clarify the use case or suggest when not to use it.
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.
Many tools overlap in purpose, such as cross_lens_verify, cross_lens_lookup, profile_entity, and preflight_should_i_act, which all return node verdicts with subtle differences. Sigil verification tools and receipt-related tools also have similar names and require deep reading to distinguish.
The tool names are mostly readable, but the pattern is mixed: some use verb_noun (get_domain, create_subscription) while others use domain prefixes (sigil_*, ghostroute_*, intel_*). Within each domain, naming is consistent, but the overall style lacks uniformity.
With 90 tools, this server is extremely overloaded. Even for a multi-purpose data API, the sheer number overwhelms and makes navigation difficult, far exceeding the typical well-scoped MCP server. The count is an extreme mismatch for the apparent scope.
The tool surface is very comprehensive, covering tracker lookup, cross-lens verification, receipts, compliance, subscriptions, tasks, intel probes, and more. Minor gaps exist, such as no batch cross-lens verification, but core workflows are well covered.