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get_prometheus_metadata

Retrieve metadata for all metrics from a Prometheus datasource to understand available data and structure for monitoring and analysis.

Instructions

Get metadata for all metrics from a Prometheus datasource

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasourceUidYesThe Prometheus datasource UID
limitNoLimit the number of metrics returned
Behavior2/5

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. While 'Get metadata' implies a read-only operation, it doesn't specify what 'metadata' includes (e.g., metric names, types, help text), whether there are rate limits, authentication requirements, or how results are structured. This leaves significant gaps for a tool that fetches data from an external system.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that efficiently communicates the core purpose without unnecessary words. It's front-loaded with the essential information and has zero wasted content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool that retrieves data from an external system (Prometheus) with no annotations and no output schema, the description is insufficient. It doesn't explain what 'metadata' encompasses, how results are returned, potential limitations, or error conditions. Given the complexity of interacting with a monitoring system, more contextual information would be helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents both parameters (datasourceUid and limit). The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining what a 'Prometheus datasource UID' represents or providing context for the limit parameter. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get metadata') and target resource ('all metrics from a Prometheus datasource'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_prometheus_labels' or 'get_prometheus_series' that also retrieve Prometheus data, so it doesn't reach the highest score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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. With many sibling tools for Prometheus data retrieval (e.g., get_prometheus_labels, get_prometheus_series), there's no indication of what makes this tool distinct or when it's the appropriate choice.

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

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