From axiom-cli
Explores an Axiom dataset to reveal its schema, fields, volume, and patterns. Use when discovering a new dataset or investigating data structure.
How this skill is triggered — by the user, by Claude, or both
Slash command
/axiom-cli:explore-datasetThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Systematically explore an Axiom dataset to understand its structure, content, and potential use cases.
Systematically explore an Axiom dataset to understand its structure, content, and potential use cases.
When invoked with a dataset name (e.g., /explore-dataset logs), the name is available as $ARGUMENTS.
If no dataset specified, list what's available:
axiom dataset list -f json
Always start here. Discover actual field names and types:
axiom query "['<dataset>'] | getschema" --start-time -1h
Identify:
OTel trace data: If schema contains trace_id, span_id, attributes.*, note that:
['service.name'] not ['resource.service.name']['attributes.custom']['field'] with tostring() for aggregationsaxiom-apl skill's OTel reference for field mappingsExamine actual values:
axiom query "['<dataset>'] | limit 10" --start-time -1h -f json
Look for:
Understand data volume patterns:
axiom query "['<dataset>'] | summarize count() by bin(_time, 1h) | sort by _time asc" --start-time -24h
Analyze:
For each key categorical field (status, level, service):
axiom query "['<dataset>'] | summarize count() by <field> | top 20 by count_" --start-time -1h
Identify:
For numeric fields (duration, bytes, count):
axiom query "['<dataset>'] | summarize count(), min(<field>), max(<field>), avg(<field>), percentiles(<field>, 50, 95, 99)" --start-time -1h
Search for error indicators:
axiom query "search in (['<dataset>']) 'error' or 'fail' or 'exception' | limit 20" --start-time -1h
Provide a summary including:
## Dataset Summary: <name>
### Purpose
<What system generated this data, what it represents>
### Key Fields
| Field | Type | Description |
|-------|------|-------------|
| ... | ... | ... |
### Volume
- Events per hour: ~X
- Data freshness: last event at X
### Key Dimensions
- `status`: 200, 400, 500, ...
- `service.name`: api, web, worker, ...
### Recommended Queries
<Common queries for this dataset>
### Monitoring Opportunities
<What could be alerted on>
getschema directly for single field lookupssearch); extract patterns then optimizeFor query syntax, invoke the axiom-apl skill which provides comprehensive documentation on operators, functions, and patterns.
npx claudepluginhub axiomhq/cli --plugin axiom-cliDetects anomalies in Axiom datasets using statistical analysis including volume spikes, new values, outliers, and rare events. Requires authenticated Axiom CLI.
Profiles unfamiliar datasets: schema structure, column distributions, null rates, cardinality, outliers, table relationships, and temporal coverage. Onboard new data sources, audit freshness, or discover foreign keys.
Explores datasets interactively: lists tables with stats, previews rows and schemas, shows column distributions, flags quality issues with SWD-styled charts.