list_regionsThe fleet's probe regions: id, display name, city, country, continent. Use it to name where a check runs from and to pass a valid region to get_monitor_history. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint: true, and the description reinforces this with 'Read-only'. It adds behavioral context by listing the fields returned, which goes beyond the annotation. No information about pagination or ordering is disclosed, but for a simple parameterless list tool this is sufficient.
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 two sentences long, front-loaded with the resource definition and followed by usage guidance. No unnecessary words or repetition; it earns its place.
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 has no parameters and an output schema exists, so the description need not explain return values. It covers purpose, field list, usage context, and connectivity to a sibling tool, making it complete for this simple tool.
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 has zero parameters, so the baseline is 4. The description adds meaningful value by noting that the output can be used to pass a valid `region` to get_monitor_history, linking the semantics of this tool's data to another tool's 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 clearly states the tool lists the fleet's probe regions and enumerates the fields (id, display name, city, country, continent). It distinguishes the resource type from other list_* siblings, so purpose is unambiguous.
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 explicitly explains when to use the tool: to name where a check runs from and to obtain a valid `region` parameter for get_monitor_history. This provides actionable guidance and connects to a specific sibling tool, making usage context clear.
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 resource and action: flow runs, step trends, incidents, incident metrics, monitors, monitor history, org health, org usage, status pages, notification channels, regions, status pages lists, and tags. The get_ vs list_ distinction is consistent and each pair (e.g., get_monitor vs list_monitors) is clearly separated by depth of detail. No two tools appear to serve the same purpose.
All tool names follow the verb_noun pattern with snake_case, using only 'get_' for single-item or aggregate detail and 'list_' for collections. Objects are consistently named (monitor, incident, status_page, org_*). This predictive pattern makes it easy to guess tool behavior from the name.
At 15 tools, this server sits at the upper bound of the well-scoped range, yet every tool fills a clear niche: monitoring details, history, incidents, flow-specific analytics, org-level views, and reference data (regions, tags, channels). No tool feels redundant, and the count is appropriate for a read-only monitoring API.
The read-only surface is remarkably comprehensive, covering monitors, incidents, flow runs, step trends, status pages, notification channels, regions, tags, and org health/usage. The only notable gap is the lack of any mutation tools (e.g., update_monitor, acknowledge_incident) which the descriptions hint at but do not expose, so agents cannot act on the information—only observe.