proplab_system_statusMonitor PropLab health: check API status, recent pipeline runs, data freshness, and errors. Diagnose outages or stale prop data for NBA/WNBA feeds.
Check PropLab system health: API health status, recent pipeline runs, data freshness, and any errors.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is fully covered by structured data. The description adds useful content context (what is inspected: pipelines, freshness, errors) but says nothing about auth requirements, rate limits, or scope constraints. Adds some value over annotations, so a 3 is appropriate.
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?
A single front-loaded sentence with a colon-delimited enumeration of returned content — no filler or restatement of the name. Efficient, though the list is slightly abbreviated rather than fully structured.
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?
There is no output schema, so the description must convey return content, and it does so by naming the four areas inspected. With zero parameters and full annotation coverage, this is largely sufficient; only the absence of any note on failure/error signaling keeps it from the top band.
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?
The tool takes zero parameters, which is the baseline-4 case. The description accurately implies a parameterless full-status snapshot with no filtering options, consistent with the empty schema.
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?
States a specific verb (Check) plus resource (PropLab system health) and enumerates the exact content returned: API health, pipeline runs, data freshness, errors. It is clearly distinct in domain from the data-oriented siblings (games, backtests, picks), though it does not explicitly name an alternative, so it lands just below the top band.
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?
Usage is implied by the nature of a health/status check, but there is no explicit when-to-use guidance, no mention of when not to call it, and no routing to or away from any sibling tool. Adequate but with a clear gap for an agent deciding whether this is the right diagnostic call.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.