cloud_status
Live status of AWS, GCP, Azure — active incidents, recent events, EU regions.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| provider | No | aws|gcp|azure|all (default: all) |
Live status of AWS, GCP, Azure — active incidents, recent events, EU regions.
| Name | Required | Description | Default |
|---|---|---|---|
| provider | No | aws|gcp|azure|all (default: all) |
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?
With no annotations provided, the description carries the behavioral transparency burden. It discloses what the tool reports (active incidents, recent events, EU regions) but does not explicitly state that it is a read-only operation or describe any other behavioral traits such as caching or data freshness. This is adequate for a simple status tool but not exhaustive.
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, concise sentence that front-loads the core purpose and immediately provides useful detail about what is covered. Every word earns its place, with no redundancy or filler.
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 status tool with one optional parameter and no output schema, the description is reasonably complete. It tells the user what categories of information will be returned (incidents, events, regions) and which providers are covered. It could benefit from explaining the output format or the meaning of 'live', but it covers the essentials.
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 fully describes the 'provider' parameter with allowed values and default, achieving 100% schema description coverage. The tool description adds no additional meaning or usage details for the parameter, so the baseline score of 3 applies.
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 conveys that the tool provides live cloud status across AWS, GCP, and Azure, including incidents, events, and regional data. It distinguishes itself from sibling tools by specifying the multi-provider status scope, though it lacks an explicit verb like 'retrieve' or 'check'.
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 phrase 'Live status' implies this is the tool to use for real-time cloud health information, and the inclusion of providers/regions gives context. However, there is no explicit guidance about when to prefer this over sibling tools like cloud_incidents or region_status, nor any exclusions or prerequisites.
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.
Several tools have overlapping purposes: cloud_incidents and cloud_status both report incidents; health_check and ping both test connectivity; notification_check and sla_check both verify Art. 30 contract clauses. These overlaps will cause an agent to select the wrong tool.
All tool names use lowercase with underscores, forming a consistent pattern. Even single-word tools like 'ping' fit the style. No mixed conventions.
14 tools is within the well-scoped range, but the set contains near-duplicates (e.g., sla_check vs notification_check) that inflate the count slightly. Still reasonable for the broad cloud monitoring and compliance scope.
The set covers live status, incident timelines, risk analysis, compliance checks, and integration. No critical gaps are apparent for the stated purpose, though historical analysis or alerting tools could be added.