dynatrace_managed_query_metrics_data

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

Annotations already provide readOnlyHint=true, and the description adds useful behavioral context about querying metrics: large amounts of data can be retrieved, so entitySelector, timerange, and resolution must be constrained. It does not describe output shape or failure modes, but for a read-only tool with annotations this is reasonable coverage.

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 front-loaded with the core purpose and then presents constraints compactly. It is efficient and every clause adds value, though the opening 'Must limit the amount of data being retrieved' is somewhat redundant with the three following 'must' clauses.

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?

The description, combined with the rich schema, covers the main invocation details and safety constraints. However, there is a notable mismatch: the description says entitySelector and resolution 'must' be used, while the schema marks them optional. It also does not describe the expected response shape, which is notable since there is no output schema. These gaps leave an agent somewhat uncertain about mandatory call requirements.

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 coverage is 100%, so the baseline is 3. The description adds cross-parameter meaning beyond the schema by mandating a specific entitySelector, a narrow timerange, and a resolution aligned with that range (e.g., hours rather than minutes for multi-day data). This gives operational context not present in the individual parameter descriptions.

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 operation ('Query metric data') and its primary filters (time range, metric selector), which distinguishes it from siblings like list_available_metrics or get_metric_details. It does not explicitly name a sibling, but the resource and filtering criteria are unambiguous enough for an agent to understand what this tool does.

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 gives explicit, actionable guidance: use a specific entitySelector, a narrow timerange, and a resolution matched to the timerange. However, it does not explicitly state when to avoid this tool or point to alternatives like list_available_metrics or discover_entities, so it stops short of full tool-selection guidance.

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