com um clique
axiom-apl
// APL query language reference for Axiom. Provides operators, functions, patterns, and CLI usage. Auto-invoked by specialized Axiom skills when writing or debugging APL queries.
// APL query language reference for Axiom. Provides operators, functions, patterns, and CLI usage. Auto-invoked by specialized Axiom skills when writing or debugging APL queries.
Detect anomalies in Axiom datasets using statistical analysis. Use when looking for unusual patterns, volume spikes, outliers, or new error types in observability data.
Explore an Axiom dataset to understand its schema, fields, volume, and patterns. Use when discovering a new dataset, investigating data structure, or understanding what data is available.
Analyze OpenTelemetry distributed traces from Axiom. Use when investigating a trace ID, finding traces by criteria (errors, latency, service), or debugging distributed system issues.
| name | axiom-apl |
| description | APL query language reference for Axiom. Provides operators, functions, patterns, and CLI usage. Auto-invoked by specialized Axiom skills when writing or debugging APL queries. |
| compatibility | Requires authenticated Axiom CLI (axiom) |
| user-invocable | false |
| context | fork |
| allowed-tools | Bash(axiom query *), Bash(axiom dataset list), Bash(axiom dataset list *), Bash(axiom stream *), Bash(axiom config get *), Read, Grep, Glob |
APL is Axiom's query language for analyzing observability data. This skill provides comprehensive guidance for writing, debugging, and optimizing APL queries.
Documentation: https://axiom.co/docs/apl/introduction
CLI usage: See references/cli.md
axiom dataset list -f json
['<dataset>'] | getschema
Never guess field names. The schema shows all fields with their types.
['<dataset>'] | limit 10
See references for operators, functions, and patterns.
['dataset-name'] // Bracket notation (required for names with dots/dashes)
dataset_name // Plain identifier (only for simple names)
field_name // Plain field
['field.with.dots'] // Bracket notation for dotted fields
['service.name'] // OTel data (see references/otel.md for field mappings)
['dataset']
| where <condition>
| extend <new_field> = <expression>
| summarize <aggregation> by <grouping>
| project <fields>
| sort by <field> desc
| limit 100
Always filter by time first - it's the most selective filter.
// Relative time
| where _time >= ago(1h)
| where _time >= ago(24h) and _time < ago(1h)
// Absolute time
| where _time >= datetime(2024-01-15T10:00:00Z)
| where _time between (datetime(2024-01-15) .. datetime(2024-01-16))
Time functions:
ago(timespan) - Relative past timenow() - Current timedatetime(string) - Parse datetimebin(_time, 5m) - Time bucketingbin_auto(_time) - Automatic bucketinggetschema directly instead of invoking the full skill