logfire-read — community logfire-read, logger, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Perfect for Logging Analysis Agents needing structured logging of Python function calls with JSONL output. Structured logging of python function calls for use with containerized applications and docker compose

michaeltschreiber michaeltschreiber
[0]
[0]
Updated: 3/5/2026

Agent Capability Analysis

The logfire-read skill by michaeltschreiber is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Perfect for Logging Analysis Agents needing structured logging of Python function calls with JSONL output.

Core Value

Empowers agents to read Logfire records using JSONL output and repo's reader utilities, enabling targeted queries with the agent helper for advanced log analysis and filtering with protocols like Docker Compose.

↓ Capabilities Granted for logfire-read

Debugging containerized applications
Analyzing log data with Python scripts
Filtering logs with specific messages using the agent helper

! Prerequisites & Limits

  • Requires Python environment
  • Docker Compose setup needed
  • JSONL output format only
Labs Demo

Browser Sandbox Environment

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logfire-read

Install logfire-read, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly

Logfire Read Skill

Use this skill to read Logfire records with JSONL output using the repo’s reader utilities.

Quick Start

  1. Load .env from the repo root:
sh
1set -a
2. ./.env
3set +a
  1. Run the JSONL reader:
sh
1python scripts/logfire-fetch.py

Or use the bundled script:

sh
1./.codex/skills/logfire-read/scripts/read_logs.sh --message-like "Processing failed" --limit 10

Agent-Friendly CLI

Use the agent helper for targeted queries:

sh
1python scripts/logfire-read-agent.py --since 2026-01-11T00:00:00Z --message-like "Processing failed" --limit 10

Module API

Use query_logfire() for programmatic access:

python
1from logger import query_logfire
2
3rows = query_logfire(jsonl=True, level=21, message_like="Processing failed", limit=10)
4for row in rows:
5    print(row)

Environment Variables

Required:

  • LOGFIRE_READ_URL (e.g., https://logfire-us.pydantic.dev/v1/query)
  • LOGFIRE_READ_TOKEN

Optional filters:

  • LOGFIRE_READ_COLUMNS
  • LOGFIRE_READ_LIMIT
  • LOGFIRE_READ_SINCE
  • LOGFIRE_READ_LEVEL
  • LOGFIRE_READ_MESSAGE_LIKE
  • LOGFIRE_READ_TRACE_ID
  • LOGFIRE_READ_SPAN_ID
  • LOGFIRE_READ_JSONL=true

Output Format

  • JSONL output returns one JSON object per record.
  • level is converted to severity strings (trace, debug, info, warn, error, fatal).

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is logfire-read?

Perfect for Logging Analysis Agents needing structured logging of Python function calls with JSONL output. Structured logging of python function calls for use with containerized applications and docker compose

How do I install logfire-read?

Run the command: npx killer-skills add michaeltschreiber/logger. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for logfire-read?

Key use cases include: Debugging containerized applications, Analyzing log data with Python scripts, Filtering logs with specific messages using the agent helper.

Which IDEs are compatible with logfire-read?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for logfire-read?

Requires Python environment. Docker Compose setup needed. JSONL output format only.

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add michaeltschreiber/logger. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use logfire-read immediately in the current project.

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