query_metrics

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 tool executes queries and returns JSON results, but lacks details on error handling, rate limits, authentication requirements, or whether it's read-only or mutating. The description doesn't contradict annotations (none exist), but provides only basic operational context.

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 well-structured with a clear purpose statement followed by organized parameter and return sections. Every sentence adds value, though the parameter explanations could be slightly more concise. It's appropriately sized for a 6-parameter tool with technical details.

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 complexity (6 parameters, technical query execution) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the core purpose and parameters well, though it lacks usage context and some behavioral details. The output schema reduces the need to describe return format in the description.

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%, so the description must compensate. It provides clear explanations for all 6 parameters, including format details (RFC3339 for times, examples like '15s' for step), defaults (region: us-east-1), and context (range queries for start/end/step). This adds substantial value beyond the bare schema, though it doesn't fully explain parameter interactions or constraints.

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: 'Execute a PromQL query against an Amazon Managed Prometheus workspace.' It specifies the exact action (execute), technology (PromQL), and target resource (Amazon Managed Prometheus workspace), which distinguishes it from sibling tools that focus on workspace management rather than query execution.

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. While it's clear this is for querying metrics, there's no mention of when to use it over other query methods or tools, nor any prerequisites or constraints beyond the parameters listed. This leaves the agent without context for tool selection.

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