graylog-tst

Search and analyze Graylog test environment logs with Lucene syntax.

Updated Mar 5, 2026
One-click install
npx skills add https://github.com/pi-2r/copilot-cli-docker --skill graylog-tst
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: graylog-tst
Source: https://github.com/pi-2r/copilot-cli-docker/tree/main/.copilot/skills/graylog-tst
Command: npx skills add https://github.com/pi-2r/copilot-cli-docker --skill graylog-tst

SYSTEM DOCUMENTATION & REQUIREMENTS

## What problem does it solve? Provides a safe, test-only interface to interact with a Graylog MCP server for log search, analysis, and troubleshooting without touching production data.

## Core Features & Use Cases

  • Search test/staging log messages using Lucene syntax for targeted investigations.
  • Aggregate logs (group by fields, counts, percentile metrics) to derive insights from test data.
  • List available streams and scope searches to specific streams to improve performance and relevance.
  • List indices and index sets to understand data availability and health in the test environment.
  • List configured inputs (syslog, GELF, etc.) to verify data ingestion points.
  • Discover available fields per stream before querying using list_fields to ensure valid queries.
  • Get current server time and system status to monitor health during debugging.

### Quick Start Prefix prompts with #graylog-tst to activate this skill and start with a simple search such as '#graylog-tst Search for errors'.

Frequently Asked Questions about graylog-tst

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I search and analyze test logs in Graylog staging environments?

You can search and analyze test logs in Graylog staging environments by using Lucene syntax to query specific streams and indices, aggregating fields and counts to derive debugging insights safely isolated from production data.

What is the best way to discover available fields before querying Graylog streams?

Discovering available fields before querying Graylog streams requires listing configured fields per stream to ensure valid Lucene syntax queries, preventing search errors and improving data relevance during test environment troubleshooting.

Can I aggregate test logs by percentile metrics and grouped fields in Graylog?

You can aggregate test logs by grouping fields, calculating counts, and deriving percentile metrics to analyze staging data distributions, verify ingestion health, and monitor system status during development debugging.

How do I verify data ingestion points and index health in a Graylog test environment?

Verifying data ingestion points and index health in a Graylog test environment involves listing configured inputs like syslog or GELF, reviewing index sets, and checking system status to ensure test data availability.

Does this Graylog log management skill work safely with production data?

This Graylog log management skill does not work with production data because it enforces safe, test-only usage through explicit activation tags, connectivity checks, and environment-driven configuration to isolate staging and development debugging.

Why do I need to use explicit activation tags for Graylog test log searches?

You need explicit activation tags like #graylog-tst for Graylog test log searches to enforce safe environment-driven configuration, ensuring queries only execute against staging data and bypassing production connectivity.