get_metric_metadataDescribe one metric before you use it: parity, category, minimum interval and any caveat attached to it.
CALL THIS BEFORE get_metric_timeseries if the metric is unfamiliar. The
minimum interval tells you the finest resolution that is real rather
than interpolated, and the caveat is where an approximate metric admits
what it approximates.| Name | Required | Description | Default |
|---|---|---|---|
| metric | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering safety. The description adds useful behavioral context: it clarifies that the tool provides resolution granularity and discloses approximation caveats, which is beyond the annotation coverage. No contradiction.
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?
Three sentences, front-loaded with the core purpose, followed by a precise usage directive and a brief explanation of two key fields. No filler or repetition.
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 one-parameter, no-output-schema tool, the description provides sufficient information: what it returns, when to use it, and why. It does not detail the exact metric identifier format, but that is a minor gap given the tool's simplicity and the clarity of the 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?
Schema description coverage is 0%, so the description carries the burden. It refers to 'one metric' but does not explicitly define the format or domain of the 'metric' parameter (e.g., a metric ID or name). While the tool name and context make it reasonably inferable, the description could be more explicit about what value to pass.
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 states a clear verb and resource: 'Describe one metric' and lists the specific fields it returns (parity, category, minimum interval, caveat). It distinguishes itself from the sibling get_metric_timeseries by being the prerequisite call, so an agent can tell them apart immediately.
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 explicitly instructs 'CALL THIS BEFORE get_metric_timeseries if the metric is unfamiliar', naming the exact sibling and the condition for use. It also explains why (minimum interval and caveat), leaving no ambiguity about when to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.