Notre avis
Ce skill fournit une référence complète pour le langage de requête APL d'Axiom, permettant d'écrire, déboguer et optimiser des requêtes d'observabilité.
Points forts
- Référence complète des opérateurs et fonctions APL
- Gestion avancée du temps avec filtres et binning
- Découverte automatique du schéma des datasets
- Intégration avec la CLI Axiom pour l'exécution
Limites
- Nécessite une CLI Axiom authentifiée
- Ne couvre pas les cas très complexes non documentés
- Dépend de la version d'Axiom et peut devenir obsolète
Utilisez ce skill lorsque vous devez analyser des données d'observabilité avec Axiom et avez besoin d'aide pour écrire ou optimiser des requêtes APL.
Ne l'utilisez pas pour des recherches de champs simples (utilisez getschema directement) ou si vous avez déjà une requête fonctionnelle.
Analyse de sécurité
SûrThe skill only uses read-only Axiom CLI commands (axiom dataset list, axiom query, axiom stream) to help construct APL queries. There are no destructive operations, external data exfiltration, or obfuscated code.
Aucun point d'attention détecté
Exemples
Write an APL query to find all error-level logs from the 'production' dataset in the last hour, group by service, and show the count per service.How can I create a time series of average trace duration bucketed by 5-minute intervals in Axiom APL?List the schema fields for the 'k8s-logs' dataset using Axiom APL.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 stream:*), Read, Grep, Glob
Axiom Processing Language (APL)
APL is Axiom's query language for analyzing observability data. This skill provides comprehensive guidance for writing, debugging, and optimizing APL queries.
Quick Reference
Documentation: https://axiom.co/docs/apl/introduction
CLI usage: See references/cli.md
Core Workflow
1. List Available Datasets
axiom dataset list -f json
2. Discover Schema (CRITICAL - Always Do First)
['<dataset>'] | getschema
Never guess field names. The schema shows all fields with their types.
3. Sample Data
['<dataset>'] | limit 10
4. Write Query
See references for operators, functions, and patterns.
APL Syntax Essentials
Dataset Reference
['dataset-name'] // Bracket notation (required for names with dots/dashes)
dataset_name // Plain identifier (only for simple names)
Field Reference
field_name // Plain field
['field.with.dots'] // Bracket notation for dotted fields
['service.name'] // OTel data (see references/otel.md for field mappings)
Basic Query Structure
['dataset']
| where <condition>
| extend <new_field> = <expression>
| summarize <aggregation> by <grouping>
| project <fields>
| sort by <field> desc
| limit 100
Time Handling
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 bucketing
When NOT to Use
- Simple field lookup: Use
getschemadirectly instead of invoking the full skill - Known query patterns: If you already have a working query, don't re-invoke for syntax help
- Real-time alerting: Use Axiom Monitors for continuous alerting, not ad-hoc queries
References
- CLI Usage - Command flags and execution
- Operators - Tabular and scalar operators
- Functions - String, datetime, aggregation functions
- Patterns - Query patterns by use case
- Common Gotchas - Mistakes and fixes
- OpenTelemetry - OTel field mappings and trace patterns
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