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. While 'Fetch' implies a read operation, it doesn't specify whether this requires authentication, has rate limits, returns real-time vs historical data, or what format the time-series data takes. The description mentions 'exact metric names only' which is useful context, but overall behavioral information is minimal for a tool with 12 parameters.

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 extremely concise - a single sentence that gets straight to the point with no wasted words. It's front-loaded with the core purpose and includes an important constraint ('exact metric names only') in a compact form. Every word serves a purpose.

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 complex tool with 12 parameters, no annotations, and 0% schema description coverage, the description is inadequate. While there's an output schema (which helps), the description doesn't provide enough context about behavior, parameter usage, or relationship to sibling tools. The single sentence doesn't compensate for the lack of structured documentation.

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?

With 0% schema description coverage and 12 parameters (11 optional, 1 required), the description provides almost no parameter guidance. It mentions 'exact metric names only' which hints at the 'metric_names' parameter, but doesn't explain what constitutes an 'exact' name, format requirements, or provide examples. The description doesn't address any of the other 11 parameters, leaving significant gaps in understanding.

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 ('Fetch') and resource ('time-series metrics from Ambari Metrics'), making the purpose immediately understandable. It specifies 'exact metric names only' which provides important scope information. However, it doesn't explicitly differentiate from sibling tools like 'list_ambari_metrics_metadata' or 'list_common_metrics_catalog', which might also involve metrics.

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. There's no mention of prerequisites, appropriate contexts, or comparisons to sibling tools like 'list_ambari_metric_apps' or 'list_common_metrics_catalog'. The agent must infer usage from the tool name and description alone.

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