Complete PromQL toolkit with generation and validation capabilities
94
94%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
{
"context": "Verify that the agent correctly identifies the high-cardinality risk, explains when the pattern is acceptable, and provides both a filtered alternative and a recording rule.",
"type": "weighted_checklist",
"checklist": [
{
"name": "High-cardinality risk is identified and explained",
"description": "The report states that the query has no label filters and explains that this causes fan-out across all series for the metric (referencing the `path`, `status_code`, and multi-service context).",
"max_score": 25
},
{
"name": "Nuanced acceptability analysis provided",
"description": "The report explains that `sum()` aggregation produces a single scalar result, so the query is acceptable IF the cluster can handle the fan-out — it does not simply label the query as 'bad'.",
"max_score": 20
},
{
"name": "Filtered per-service alternative is provided",
"description": "The report includes a query that adds a `job=` or `service=` label filter to restrict the query to a single service.",
"max_score": 20
},
{
"name": "Recording rule definition is provided",
"description": "The report includes a YAML recording rule definition that pre-aggregates the total request rate, reducing per-query scan cost.",
"max_score": 20
},
{
"name": "Semantic and syntactic correctness confirmed",
"description": "The report confirms that the query is syntactically valid and semantically correct for computing total request rate (counter metric with `rate()` and `sum()`).",
"max_score": 15
}
]
}