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Evaluate and monitor AI agent fleets across six key dimensions to score health, identify issues, and optimize performance for ops teams managing 1-100+ agents.

AI 与大模型

许可证:MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本:v1.1.0

统计:⭐ 0 · 420 · 0 current installs · 0 all-time installs

0

安装量(当前) 0

🛡 VirusTotal :良性 · OpenClaw :可疑

Package:1kalin/afrexai-agent-observability

安全扫描(ClawHub)

  • VirusTotal :良性
  • OpenClaw :可疑

OpenClaw 评估

This is a high-level, instruction-only observability guide/prompts for assessing agent fleets — it doesn't install anything or request credentials, but the runtime prompt is vague and asks an agent to 'run the assessment' against 'our current deployment' without specifying how to collect data, which could lead an autonomous agent to try to access sensitive system or cloud resources.

目的

The name and description claim fleet observability, and the content is a plausible checklist and prompt for that purpose. However, the skill is purely instruction-only (no code, no declared integrations, no env vars), so it cannot actually perform automated monitoring by itself — it can only guide an agent or human to perform the assessment. The claim to 'Run the agent observability assessment against our current deployment' is disproportionat…

说明范围

SKILL.md contains open-ended runtime prompts that ask the agent to evaluate the 'current deployment' and to gather counts, spend, alerts, and recent failures. The instructions do not confine how the agent should obtain that information (no explicit APIs/paths to query, no declared env vars). That vagueness grants broad discretion — an autonomous agent could attempt to read environment variables, query cloud APIs, inspect files, or contact exte…

安装机制

No install spec and no code files — lowest-risk install footprint. Nothing will be written to disk by the skill itself because there is no install step.

证书

The skill declares no required environment variables, credentials, or config paths, which is consistent with an instruction-only checklist. However, the assessment questions (monthly spend, monitoring existence, alerting targets) typically require privileged access to billing, monitoring, or deployment APIs; those are not declared, creating an implicit gap. If an agent pursues answers programmatically, it may request credentials later — the sk…

持久

always is false and there are no persistence or system-modifying instructions. Autonomous invocation is allowed (platform default) but the skill does not request elevated or persistent privileges itself.

安装(复制给龙虾 AI)

将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「AI Agent Observability」。简介:Evaluate and monitor AI agent fleets across six key dimensions to score health,…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/1kalin/afrexai-agent-observability/SKILL.md
(来源:yingzhi8.cn 技能库)

SKILL.md

打开原始 SKILL.md(GitHub raw)

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