Why does the skill use regional ingest URLs?

Axiom uses regional edge URLs (like us-east-1 or eu-central-1) to reduce latency and improve the reliability of data ingestion compared to the standard API endpoint.

How do I set up the Axiom skill for Claude Code?

You need to export your AXIOM_API_TOKEN as an environment variable and ensure you have a dataset created in your Axiom account.

Which API token type should I use?

Use an API Token (prefix xaat-) for most operations like ingesting and querying. Use a Personal Access Token (prefix xapt-) if you need full account access or user-specific endpoints.

What is Axiom Processing Language (APL)?

APL is a query language used by Axiom, similar to KQL (Kusto Query Language), designed to filter, summarize, and analyze large volumes of log and event data.

Axiom Observability

Name: Axiom Observability
Author: vm0-ai

byvm0-ai

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Analytics & Monitoring

Integrates the Axiom observability platform to ingest, query, and analyze logs and event data via REST API.

About

This skill connects Claude Code to the Axiom cloud-native observability platform, enabling developers to manage high-volume logs and event data programmatically. It provides a comprehensive set of tools for ingesting data through regional edge endpoints, executing complex analytics using Axiom Processing Language (APL), and managing datasets or monitors directly from the terminal. Whether you are debugging production issues or building automated observability pipelines, this skill simplifies the process of interacting with your telemetry data.

Key Features

Advanced querying and aggregation using Axiom Processing Language (APL)
18 GitHub stars
Deployment tracking via automated annotations
Regional edge ingestion for high-performance data logging
Programmatic dataset creation, management, and deletion
Support for JSON, NDJSON, and batch data ingestion

Use Cases

Debugging distributed systems by querying real-time logs with APL
Building custom CI/CD pipelines that report build telemetry to Axiom
Automating deployment markers to correlate code changes with performance shifts

About

Key Features

Advanced querying and aggregation using Axiom Processing Language (APL)
18 GitHub stars
Deployment tracking via automated annotations
Regional edge ingestion for high-performance data logging
Programmatic dataset creation, management, and deletion
Support for JSON, NDJSON, and batch data ingestion

Use Cases

Debugging distributed systems by querying real-time logs with APL
Building custom CI/CD pipelines that report build telemetry to Axiom
Automating deployment markers to correlate code changes with performance shifts