get_org_healthOrg health summary: per-state monitor totals and the worst currently-failing monitors. The one-shot answer to 'what is broken right now?'. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| org | Yes | The org slug this connector is bound to. | |
| worst | Yes | Non-up monitors, newest failure first, capped. | |
| totals | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already indicates this is a safe read operation. The description adds value by explaining the output content (per-state totals and worst failing monitors) and the 'current' snapshot nature, which goes beyond the annotation. The explicit 'Read-only' statement is consistent with the annotation.
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 short sentences, front-loaded with the key summary and immediately followed by the use case. Every word earns its place, and the redundant 'Read-only' is minimal and harmless.
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 simple no-parameter tool with an output schema present, the description is complete: it states what the tool does, what data it returns, and when to use it. There are no significant gaps given the tool's simplicity.
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 there is nothing to explain. The empty schema is fully covered, and the description correctly omits unnecessary parameter details. Baseline 4 is appropriate for a no-parameter tool.
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 identifies the tool as providing an org health summary with per-state monitor totals and the worst currently-failing monitors. This is specific and distinguishes it from sibling tools like list_monitors and get_incident, and the 'one-shot answer' phrase further clarifies its scope.
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 states the use case: 'The one-shot answer to what is broken right now?'. It does not mention alternative tools or exclusions, but the positioning as a summary tool is clear enough to guide appropriate selection.
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.