get_site_health
Uptime/health summary for a site: status, response time, TLS/domain checks, open incidents.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| site | Yes |
Uptime/health summary for a site: status, response time, TLS/domain checks, open incidents.
| Name | Required | Description | Default |
|---|---|---|---|
| site | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the transparency burden. It does state that the tool returns a summary with several health components, and the get prefix implies a read-only operation, but it does not mention data freshness, failure behavior, permissions, or whether checks are live or historical.
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 a single compact sentence with a front-loaded purpose and a scannable list of included health components. Every word adds useful information, with no redundancy.
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 one-parameter tool with no output schema, the description gives a reasonable high-level overview and return contents. However, it omits the required site identifier format and does not distinguish itself from verify_site, so an agent cannot fully invoke it correctly without additional inference.
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 description coverage is 0%, and the description only says 'for a site', which essentially restates the property name. The description does not clarify whether site should be a domain, URL, site ID, or other identifier, leaving the single required parameter ambiguous.
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 a specific verb and resource: retrieving an uptime/health summary for a site. It lists concrete contents (status, response time, TLS/domain checks, open incidents) that separate it from the analytics-focused sibling 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?
The description implies the use case: whenever a site's health summary is needed. However, it does not explicitly state when not to use the tool or which alternative to prefer, especially given verify_site may also perform site-related checks.
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 or analytical view: site management (add/list/verify) is cleanly separated from analytics (stats, timeseries, visitors, realtime, bot report, breakdown, health). Even the traffic-related getters differ clearly by granularity and intent, so an agent is unlikely to confuse them.
The naming follows a consistent verb_noun pattern: add_site, list_sites, verify_site, and all analytics tools use get_<noun>. This makes the toolset predictable and easy to navigate.
Ten tools is well-scoped for an analytics product, covering both site administration and multiple data views without redundancy or bloat. Each tool earns its place in the API surface.
The core site lifecycle is covered (add, list, verify), and the analytics side is thorough with stats, timeseries, breakdown, realtime, visitors, bot reports, and health. Minor gaps exist, such as no remove/update site or deeper filtering options, but agents can complete typical workflows without dead ends.