ai-observer — security grade SAFE, quality 73/100

Security audit verdict: SAFE · quality 73/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by tobilg · Codex Skill · ★ 273

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is ai-observer safe to install? View the security audit →

About ai-observer

AI Observer Unified local observability for AI coding assistants AI Observer is a self-hosted, single-binary, OpenTelemetry-compatible observability backend designed specifically for monitoring local AI coding tools like Claude Code, Gemini CLI, and OpenAI Codex CLI. Track token usage, costs, API latency, error rates, and session activity across all your AI coding assistants in one unified dashboard—with real-time updates and zero external dependencies. Why AI Observer? AI coding assistants are becoming essential development tools, but understanding their behavior and costs remains a challenge: Visibility: See exactly how your AI tools are performing across sessions Cost tracking: Monitor token usage and API calls to understand spending Debugging: Trace errors and slow responses back to specific interactions Privacy: Keep your telemetry data local—no third-party services required Features Multi-tool support — Works with Claude Code, Gemini CLI, and OpenAI Codex CLI Real-time dashboard — Live updates via WebSocket as telemetry arrives Customizable widgets — Drag-and-drop dashboard builder with multiple widget types Historical import — Import past sessions from local JSONL/JSON...

aiclaude-codecodex-cliduckdbgemini-cliobservabilityopentelemetry

Quick Facts

Stars273
Forks25
LanguageGo
CategoryCodex Skill
LicenseMIT
Quality Score73.491299301002/100
Last Updated2026-09-15
Created2025-12-23
Platformsclaude-code, cli, codex, gemini, go
Est. Tokens~23k

ai-observer alternative? Top 6 similar tools

Looking for a ai-observer alternative? If you're comparing ai-observer with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • clawmetry by vivekchand · ⭐ 421

    See your agent think. Zero-config observability & governance for 30 AI agent runtimes: Claude Code, OpenAI Cod

  • browser-echo by instructa · ⭐ 320

    ⚡ Stream browser logs to terminal, zero setup, perfect for Ai Agents

  • CodexFlow by lulu-sk · ⭐ 86

    CodexFlow is a unified desktop workbench for AI coding agents (Codex/Claude/Gemini/Antigravity) across Windows

  • getspecstory by specstoryai · ⭐ 1.3k

    Install our local first extensions for your favorite AI IDE or Terminal Agent. Process your histories into reu

  • quint-code by m0n0x41d · ⭐ 1.3k

    Engineering decisions engine that know when they're stale. Frame, compare, decide — with evidence decay and p

  • cccc by ChesterRa · ⭐ 1.3k

    Coordinate your coding agents like a group chat — read receipts, delivery tracking, and remote ops from your p

More Codex Skill Tools

Explore other popular codex skill tools:

View all Codex Skill tools →

Popular Go Agent Tools

Frequently Asked Questions

What is ai-observer?

ai-observer is Unified local observability for AI coding assistants. It is categorized as a Codex Skill with 273 GitHub stars.

What programming language is ai-observer written in?

ai-observer is primarily written in Go. It covers topics such as ai, claude-code, codex-cli.

How do I install or use ai-observer?

You can find installation instructions and usage details in the ai-observer GitHub repository at github.com/tobilg/ai-observer. The project has 273 stars and 25 forks, indicating an active community.

What license does ai-observer use?

ai-observer is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to ai-observer?

The top alternatives to ai-observer on Agent Skills Hub include clawmetry, browser-echo, CodexFlow. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Codex Skill tools