MCP-Ambari-API

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the report type but doesn't describe what the output contains (e.g., metrics like storage usage, node health), whether it's read-only or has side effects, or any performance considerations (e.g., latency, data freshness). This leaves significant gaps for an agent to understand the tool's 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 a single, efficient sentence that front-loads the core purpose without unnecessary details. Every word contributes to understanding the tool's function, making it appropriately concise and well-structured for quick comprehension.

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 tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is minimally adequate. It states what the tool does but lacks context on usage, behavior, and parameters. The presence of an output schema mitigates some gaps by documenting return values, but overall completeness is limited to the basic purpose.

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 description adds no parameter-specific information beyond what's in the schema (which has 0% description coverage). It implies parameters like 'cluster_name' and 'lookback_minutes' through context ('using Ambari metrics'), but doesn't explain their roles, defaults, or constraints. Given the low schema coverage, the description fails to compensate adequately, resulting in a baseline score.

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 action ('Produce a DFSAdmin-style capacity and DataNode report') and specifies the data source ('using Ambari metrics'), which distinguishes it from generic reporting tools. However, it doesn't explicitly differentiate from sibling tools like 'get_cluster_info' or 'query_ambari_metrics' that might also provide cluster-related data.

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, ideal scenarios, or exclusions, leaving the agent to infer usage from the purpose alone. For example, it doesn't clarify if this is for monitoring, troubleshooting, or capacity planning compared to other tools.

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