AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides guidance and best practices for configuring log ingestion into PostHog for applications written in languages other than those with native SDK support. It emphasizes the use of OpenTelemetry (OTLP) to export structured logs, ensuring that system telemetry is captured effectively without requiring significant changes to existing logging infrastructure. The skill focuses on shifting from verbose, step-by-step logging to wide, context-rich events that facilitate easier debugging and analysis.
What it does
- Provides instructions for configuring OTLP exporters to send logs to PostHog.
- Outlines best practices for structured logging to improve queryability and reduce noise.
- Explains how to differentiate between user-centric events and system-centric logs.
- Offers guidance on using environment variables for secure configuration of ingestion endpoints.
- Supports integration with AI-driven debugging tools via the PostHog MCP server.
When to use it
- When you need to centralize logs from applications that lack specific PostHog SDK support.
- When you want to adopt structured logging patterns to make production debugging more efficient.
- When you are setting up observability for services that need to correlate logs with session replays or feature flags.
- When you are transitioning from verbose, step-level logging to canonical wide events.
Advantages
- Enables unified observability by placing logs alongside product analytics and session replays.
- Promotes the use of industry-standard OpenTelemetry protocols.
- Reduces storage costs and query complexity by encouraging structured, high-value log events.
- Facilitates easier correlation between system errors and specific user sessions.
Usage examples
- “How do I configure my application to send logs to PostHog using OpenTelemetry?”
- The agent provides the necessary OTLP exporter configuration steps and environment variable requirements to point your application logs to the PostHog ingest endpoint.
- “What is the best way to structure my logs for better debugging?”
- The agent explains the 'wide event' pattern, providing a JSON example that includes trace context, business attributes, and relevant metadata to replace granular, low-value log lines.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/posthog/logs-other/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip logs-other.zip -d .agents/skills
Documentation by PostHog
PostHog logs for Other Languages
This skill helps you add PostHog log ingestion to Other Languages applications.
Reference files
references/other.md- Other languages logs installation - docsreferences/start-here.md- Getting started with logs - docsreferences/search.md- Search logs - docsreferences/best-practices.md- Logging best practices - docsreferences/troubleshooting.md- Logs troubleshooting - docsreferences/link-session-replay.md- Link session replay - docsreferences/debug-logs-mcp.md- Debug logs with mcp - docs
Consult the documentation for API details and framework-specific patterns.
Key principles
Environment variables: Always use environment variables for PostHog keys and OpenTelemetry endpoints. Never hardcode them.
Minimal changes: Add log export alongside existing logging. Don't replace or restructure existing logging code.
OpenTelemetry: PostHog logs use the OpenTelemetry protocol. Configure an OTLP exporter pointed at PostHog's ingest endpoint.
Structured logging: Prefer structured log formats with key-value properties over plain text messages.
Framework guidelines
No specific framework guidelines.
Files
- ATTRIBUTION.mdAdded by AutoGineer930 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md1.3 KiB
- references/best-practices.md19.6 KiB
- references/debug-logs-mcp.md2.2 KiB
- references/link-session-replay.md4.9 KiB
- references/other.md2.7 KiB
- references/search.md2.5 KiB
- references/start-here.md2.4 KiB
- references/troubleshooting.md3.5 KiB
SKILL.md
PostHog logs for Other Languages
This skill helps you add PostHog log ingestion to Other Languages applications.
Reference files
references/other.md- Other languages logs installation - docsreferences/start-here.md- Getting started with logs - docsreferences/search.md- Search logs - docsreferences/best-practices.md- Logging best practices - docsreferences/troubleshooting.md- Logs troubleshooting - docsreferences/link-session-replay.md- Link session replay - docsreferences/debug-logs-mcp.md- Debug logs with mcp - docs
Consult the documentation for API details and framework-specific patterns.
Key principles
Environment variables: Always use environment variables for PostHog keys and OpenTelemetry endpoints. Never hardcode them.
Minimal changes: Add log export alongside existing logging. Don't replace or restructure existing logging code.
OpenTelemetry: PostHog logs use the OpenTelemetry protocol. Configure an OTLP exporter pointed at PostHog's ingest endpoint.
Structured logging: Prefer structured log formats with key-value properties over plain text messages.
Framework guidelines
No specific framework guidelines.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- PostHog
- Publisher
- PostHog (Official)
- Source
- PostHog/skills · skills/posthog/logs/skills/other · commit a5d30e7
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Also distributed in
- PostHog/skills
AutoGineer is not affiliated with or endorsed by PostHog.
Related skills
Claude API
AnthropicOfficial
Comprehensive reference for integrating Anthropic's Claude API, SDKs, and Managed Agents into your applications.
Data and AIClaude CodeClaude appsOpenAI Codex+14 moreApache-2.0Medium riskHas scriptsGitHub stars of the source repository188.6k
Transformers
K-Dense· Community
Integrate Hugging Face Transformers for model loading, inference, and fine-tuning across NLP, vision, and audio tasks.
Data and AIClaude CodeClaude appsOpenAI Codex+14 moreMITLow riskGitHub stars of the source repository56.4k
Open Notebook
K-Dense· Community
Integrate with the self-hosted Open Notebook platform to automate research ingestion, context-aware chat, and AI-driven analysis.
Data and AIClaude CodeClaude appsOpenAI Codex+14 moreMITLow riskHas scriptsGitHub stars of the source repository56.4k
Vision Sft
Seth Hobson· Community
A structured workflow for supervised fine-tuning of vision-language models, focusing on adapter configuration and silent failure prevention.
Data and AIClaude CodeClaude appsOpenAI Codex+14 moreMITGitHub stars of the source repository42.3k
LLM Evaluation
Seth Hobson· Community
A comprehensive framework for evaluating LLM application performance using automated metrics, human feedback, and LLM-as-a-judge techniques.
Data and AIClaude CodeClaude appsOpenAI Codex+14 moreMITGitHub stars of the source repository42.3k
Lora Qlora Recipes
Seth Hobson· Community
Provides configuration recipes and best-practice hyperparameters for LoRA and QLoRA supervised fine-tuning.
Data and AIClaude CodeClaude appsOpenAI Codex+14 moreMITGitHub stars of the source repository42.3k
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download logs-other.zip