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- 53 total agents across 13 categories (was 23 in 5 categories) - New categories: DevOps, Finance, Education, Healthcare, Legal, HR, Creative, Security - Quickstart folder with working Telegram bot, Docker support, and step-by-step guide - Framework comparison table: OpenClaw vs AutoGPT vs CrewAI vs LangChain vs MetaGPT - agents.json: machine-readable index of all 53 templates - .github/: FUNDING.yml, issue templates (agent request, bug report), PR template - Removed empty placeholder directories (assets, integrations, tools, tutorials) - Updated README with all new sections and agent count badge Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
🔍 Log Analyzer
Your AI log intelligence agent that finds patterns, surfaces anomalies, and explains what your logs are trying to tell you.
Overview
Log Analyzer processes high-volume log data to extract meaningful patterns and surface issues that matter. It clusters errors, correlates events across services, and translates stack traces into plain English. Built for engineers who are tired of grep-ing through thousands of log lines to find the one that matters.
Quick Start
- Copy the
SOUL.mdto your OpenClaw project - Configure your preferred channel (Telegram, Slack, Discord)
- Run
openclaw start
Or deploy instantly with CrewClaw →
Features
- Automatic error clustering and deduplication
- Anomaly detection for new and spiking error patterns
- Cross-service event correlation for distributed systems
- Natural language explanations of stack traces and error codes
- Log query generation for popular platforms (Elasticsearch, Loki, Splunk)
Sample Output
Log Summary — Last 60 min
Events: 284,320 | Errors: 5,971 (2.1%)
Status: ELEVATED (baseline 0.4%)
New Errors:
ConnectionRefused redis:6379 (1,247x) ← investigate
TimeoutError upstream 10s (892x) ← cascading
Correlation: Redis outage → session timeout → API 504s
Suggestion: Check Redis cluster health
Configuration
| Setting | Default | Description |
|---|---|---|
| log_source | elasticsearch | Log aggregation platform |
| anomaly_sensitivity | medium | How aggressively to flag anomalies |
| summary_interval | 1h | How often to generate summaries |
| error_threshold | 1% | Error rate that triggers an alert |
| cluster_similarity | 0.85 | Threshold for grouping similar errors |
Integrations
- Elasticsearch / Kibana
- Grafana Loki
- AWS CloudWatch Logs
- Splunk
- Datadog Logs