xint
X Intelligence CLI — search, monitor, analyze, and engage on X/Twitter. TypeScript + Bun. AI agent skill.
Agent Observability & Monitoring
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install 1kalin/afrexai-agent-observabilityInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Score, monitor, and troubleshoot AI agent fleets in production. Built for ops teams running 1-100+ agents.
Evaluates your agent deployment across 6 dimensions and returns a 0-100 health score with specific fixes.
| Score | Rating | Action |
|---|---|---|
| 80-100 | Production-grade | Optimize and scale |
| 60-79 | Operational | Fix gaps before scaling |
| 40-59 | Risky | Immediate remediation needed |
| 0-39 | Blind | Stop scaling, instrument first |
Ask the agent to evaluate your setup:
``...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
Score your AI agent fleet health across 6 dimensions (0-100). Detect waste, prevent failures, attribute costs.
What you get:
Who it's for: Ops teams, platform engineers, CTOs running AI agents in production.
Links:
Built by AfrexAI.
# Agent Observability & Monitoring Score, monitor, and troubleshoot AI agent fleets in production. Built for ops teams running 1-100+ agents. ## What This Does Evaluates your agent deployment across 6 dimensions and returns a 0-100 health score with specific fixes. ## 6-Dimension Assessment ### 1. Execution Visibility (0-20 pts) - Can you see what every agent is doing right now? - Task queue depth, active/idle ratio, error rates - **Benchmark**: Top quartile tracks 95%+ of agent actions in real-time ### 2. Cost Attribution (0-20 pts) - Do you know exactly what each agent costs per task? - Token spend, API calls, compute time, tool invocations - **Benchmark**: Unmonitored agents waste 30-55% on retries and hallucination loops ### 3. Output Quality (0-15 pts) - Are agent outputs validated before reaching users or systems? - Accuracy sampling, hallucination detection, regression tracking - **Benchmark**: 1 in 12 agent outputs contains a material error without monitoring ### 4. Failure Recovery (0-15 pts) - What happens when an agent fails mid-task? - Retry logic, graceful degradation, human escalation paths - **Benchmark**: Mean time to detect agent failure without monitoring: 4.2 hours ### 5. Security & Boundaries (0-15 pts) - Are agents staying within authorized scope? - Tool access auditing, data exfiltration checks, permission drift - **Benchmark**: 23% of production agents access tools outside their intended scope ### 6. Fleet Coordination (0-15 pts) - Do multi-agent workflows hand off cleanly? - Message passing reliability, deadlock detection, duplicate work - **Benchmark**: Uncoordinated fleets duplicate 18-25% of work ## Scoring | Score | Rating | Action | |-------|--------|--------| | 80-100 | Production-grade | Optimize and scale | | 60-79 | Operational | Fix gaps before scaling | | 40-59 | Risky | Immediate remediation needed | | 0-39 | Blind | Stop scaling, instrument first | ## Quick Assessment Prompt Ask the agent to evaluate your setup: ``...
# Agent Observability & Monitoring Score your AI agent fleet health across 6 dimensions (0-100). Detect waste, prevent failures, attribute costs. **What you get:** - 6-dimension health scoring (execution visibility, cost attribution, output quality, failure recovery, security, fleet coordination) - 2026 benchmarks per dimension - Cost framework by fleet size (1-100+ agents) - 90-day monitoring roadmap - 7 common monitoring mistakes - Industry-specific priority adjustments (10 verticals) **Who it's for:** Ops teams, platform engineers, CTOs running AI agents in production. **Links:** - [AI Agent Context Packs](https://afrexai-cto.github.io/context-packs/) — $47 industry-specific decision frameworks - [AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) — find hidden waste - [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/) — configure your stack Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/).
X Intelligence CLI — search, monitor, analyze, and engage on X/Twitter. TypeScript + Bun. AI agent skill.
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