scitix

scitix / siclaw

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AI-powered SRE platform — read-only infrastructure diagnostics with deep investigation, security governance, and team collaboration

siclaw.ai
40
1
100% credibility
Found Mar 08, 2026 at 38 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

Siclaw is an open-source AI agent platform designed for SRE teams to perform secure, read-only diagnostics on Kubernetes infrastructure via terminal, web UI, or team chat integrations.

How It Works

1
🔍 Discover Siclaw

You hear about an AI helper that diagnoses Kubernetes problems by reading logs and status without changing anything.

2
📦 Get it running

Install with a simple command and launch it right in your terminal.

3
🧠 Connect your AI

Link it to your favorite AI service like ChatGPT so it can think and analyze.

4
💬 Ask about issues

Type a question like 'Why is my pod crashing?' and watch it investigate step by step.

5
Grow your setup
🖥️
Web dashboard

Run a local server for a friendly screen to chat and manage tasks.

☁️
Team cluster

Deploy to your Kubernetes for everyone to share the AI helper securely.

✅ Issues solved faster

Your team gets quick root-cause answers, learns from past fixes, and stays ahead of alerts.

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AI-Generated Review

What is siclaw?

Siclaw is an AI-powered SRE platform in TypeScript for read-only Kubernetes infrastructure diagnostics. Describe a pod CrashLoopBackOff or network issue in plain English, and it runs kubectl, pulls logs, traces paths, and delivers root-cause analysis via TUI, web UI, or chatbots (Slack, Discord, Telegram). It emphasizes deep investigation, security governance with whitelists, and team collaboration across workspaces.

Why is it gaining traction?

Its hypothesis-driven engine gathers context, generates theories, validates in parallel, and concludes—smarter over time via investigation memory. Unlike general AI-powered projects on GitHub, it stays read-only (no mutations), supports alert webhooks, cron jobs, and extensible skills for runbooks. Multi-channel access and MCP for custom tools hook SREs tired of manual triage.

Who should use this?

SREs and DevOps engineers debugging K8s incidents like failing nodes or pod evictions. On-call teams needing safe, collaborative diagnostics without prod risks, or those building AI-powered SRE workflows with shared skills and IM integration.

Verdict

Worth trying for K8s diagnostics—quick TUI npm install or Helm deploy shines—but 17 stars and 1.0% credibility signal early maturity; limited tests and community mean prod caution. Strong docs make it a solid prototype for AI-powered SRE teams.

(198 words)

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