Aedifion MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool is for getting status, implying a read-only operation, but doesn't clarify aspects like authentication needs, rate limits, error conditions, or what the status output entails (e.g., running, stopped, error). For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 appropriately sized and front-loaded, with the main purpose stated clearly in the first sentence. The parameter list is concise and directly relevant. There's no unnecessary verbosity, making it easy to scan, though the structure could be slightly improved by integrating parameter details more seamlessly.

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?

Given the complexity (a status-checking tool with 2 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the status output includes, potential error scenarios, or dependencies on other tools (e.g., needing a created instance first). For a tool in this context, more detail is needed to guide effective use.

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 schema description coverage is 0%, meaning parameters are undocumented in the schema. The description lists the parameters ('instance_id' and 'project_id') and briefly describes them, adding some semantic value (e.g., 'instance_id: The instance ID.'). However, it doesn't fully compensate for the coverage gap—it lacks details like format constraints, examples, or how these IDs relate to other tools, leaving parameters partially unclear.

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's purpose: 'Get the status of an analytics instance.' It specifies the verb ('Get') and resource ('analytics instance'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_analytics_instance' or 'get_analytics_status', which might have overlapping or related purposes.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing an existing analytics instance, or compare it to siblings like 'get_analytics_instance' (which might retrieve details) or 'get_analytics_status' (which could be broader). Without such context, an AI agent might struggle to select the right tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.