工具说明为英文。
LLM 可观测性
LLM 应用的监控、追踪、评估和质量管理。
用途
活跃度
排序方式
121
工具排名
按实测增长排序，并在不同来源间归一化。 原始值保留各自的数据窗口；计算变化需要 7 天内至少两次测量。
- 1活跃
The Fable Workflow: how Claude Fable 5 worked, distilled into skills any model can run, with the eval that keeps it honest. Think / act / prove.
github实测增长打开来源 ↗
安装
git clone https://github.com/Sahir619/fable-method ~/.claude/skills/fable-method2 276GitHub 星标+7 (+0.31 %) - 2活跃
kubeshark
智能体eBPF-powered network observability for Kubernetes. Indexes L4/L7 traffic with full K8s context, decrypts TLS without keys. Queryable by AI agents via MCP and humans via dashboard.
github实测增长打开来源 ↗
12 068GitHub 星标+5 (+0.04 %) - 3活跃
Dashboard for monitoring claude code sessions.
github实测增长打开来源 ↗
安装
/plugin marketplace add JayantDevkar/claude-code-karma325GitHub 星标+4 (+1.2 %) - 4活跃
Skills, prompts, and instructions for building AI agents on top of Dynatrace production context
github实测增长打开来源 ↗
安装
git clone https://github.com/Dynatrace/dynatrace-for-ai ~/.claude/skills/dynatrace-for-ai135GitHub 星标+4 (+3.1 %) - 5活跃
🪢 Langfuse documentation -- Langfuse is the open source LLM Engineering Platform. Observability, evals, prompt management, playground and metrics to debug and improve LLM apps
github实测增长打开来源 ↗
安装
git clone https://github.com/langfuse/langfuse-docs ~/.claude/skills/langfuse-docs240GitHub 星标+3 (+1.3 %) - 6活跃
Build tested agent skills and govern their lifecycle through a user-defined marketplace: evidence, discovery, updates, rollback, quarantine, and 17-platform distribution.
github实测增长打开来源 ↗
安装
git clone https://github.com/FrancyJGLisboa/agent-skills-platform ~/.claude/skills/agent-skills-platform2 379GitHub 星标+3 (+0.13 %) - 7活跃
MCP server for Langfuse LLM observability — trace and observation analysis.
mcp实测增长打开来源 ↗
安装
claude mcp add langfuse -- npx langfuse-observability-mcp-server80GitHub 星标+2 (+2.6 %) - 8783GitHub 星标+1 (+0.13 %)
- 9活跃
Self-hosted AI SRE for Kubernetes — zero-instrumentation eBPF observability plus a copilot that fixes issues through guardrailed, self-verifying actions. BYO-LLM, air-gapped capable.
github实测增长打开来源 ↗
131GitHub 星标+1 (+0.77 %) - 10活跃
Vendor-neutral OpenTelemetry skills for AI coding agents, grounded in upstream sources
github实测增长打开来源 ↗
安装
git clone https://github.com/ollygarden/opentelemetry-agent-skills ~/.claude/skills/opentelemetry-agent-skills97GitHub 星标+1 (+1.0 %) - 11活跃
🐙 ADLC Team Skills — Agentic SDLC for Engineering Teams
github实测增长打开来源 ↗
安装
git clone https://github.com/tikalk/adlc-team-skills ~/.claude/skills/adlc-team-skills132GitHub 星标+1 (+0.76 %) - 12活跃
local-first analytics for AI agent skills
github实测增长打开来源 ↗
安装
git clone https://github.com/crafter-station/skill-kit ~/.claude/skills/skill-kit78GitHub 星标+1 (+1.3 %) - 13活跃
adl-cli
其他A command-line tool to scaffold and manage enterprise-ready AI Agents powered by the A2A (Agent-to-Agent) protocol
github实测增长打开来源 ↗
14GitHub 星标+1 (+7.7 %) - 14活跃
Agent Skill evaluation harness for paired variants, trace artifacts, and runner adapters
github实测增长打开来源 ↗
安装
git clone https://github.com/adewale/skill-eval-harness ~/.claude/skills/skill-eval-harness73GitHub 星标+1 (+1.4 %) - 15活跃
🟪 Open-source runtime that ships any LangGraph or Google ADK agent as a production-ready FastAPI service. Bundled , AG-UI copilotkit API, chat UI, 15+ guardrails, MCP, OpenTelemetry, OIDC. One pip install. Self-hosted, no vendor lock-in.
github实测增长打开来源 ↗
安装
git clone https://github.com/Idun-Group/idun-agent-platform ~/.claude/skills/idun-agent-platform199GitHub 星标+1 (+0.51 %) - 16活跃
A skill creator that proves its skills work. Evidence-driven skill creation for Claude Code and Codex: baseline-tested generation, per-skill regression evals, ecosystem doctor, cross-runtime compile, and an opt-in proactive advisor.
github实测增长打开来源 ↗
安装
git clone https://github.com/tripleyak/SkillForge ~/.claude/skills/SkillForge885GitHub 星标+1 (+0.11 %) - 17活跃
Open benchmark for Claude Code SEO skills — real headless execution against fixture sites with planted-defect answer keys. Deterministic scoring, pre-registered rubric.
github实测增长打开来源 ↗
安装
git clone https://github.com/aleclindz/seo-skill-bench ~/.claude/skills/seo-skill-bench51GitHub 星标+1 (+2.0 %) - 18活跃
74 open-source Agent Skills for Claude Code and Codex: AI SEO, AEO and GEO, code review with an A-F ship grade, CI gates, AI evals, design systems, conversion copy, Instagram growth, iOS and Android app shipping, creator rights, and…
github实测增长打开来源 ↗
130GitHub 星标+1 (+0.78 %) - 19活跃
Query Spanlens LLM observability from Cursor, Claude Desktop, or Continue via MCP.
mcp实测增长打开来源 ↗
安装
claude mcp add mcp-server -- npx @spanlens/mcp-server13GitHub 星标+1 (+8.3 %) - 20活跃
nora
MCPOpen-source, self-hosted control plane for OpenClaw and Hermes AI-agent fleets on Docker/Kubernetes — REST, CLI, and MCP.
github实测增长打开来源 ↗
50GitHub 星标+1 (+2.0 %) - 21活跃
Make Claude Opus 4.8 behave like Claude Fable 5 — doctrine output style, drift-catching hooks, and an eval loop against golden Fable transcripts. Claude Code plugin.
github实测增长打开来源 ↗
安装
/plugin marketplace add rennf93/opus-fable-playbook34GitHub 星标+1 (+3.0 %) - 22活跃
Amazon Bedrock AgentCore enterprise platform accelerator with AWS CDK, Terraform organization guardrails, MCP/A2A agents, security, memory, and observability.
github实测增长打开来源 ↗
6GitHub 星标+1 (+20.0 %) - 23活跃
Log Claude Code sessions to Opik, the open-source LLM observability and evaluation platform, built by Comet. Tracing, evaluation, and skills for observable AI applications.
github实测增长打开来源 ↗
22GitHub 星标+1 (+4.8 %)
学习与参考资源
按实测增长排序，并在不同来源间归一化。 这些资源可单独访问，不参与主要排名。
- 1活跃打开来源 ↗
50+ curated LLM observability tools PLUS 26 Agent Skills (several with runnable, unit-tested scripts) to build, evaluate, debug, secure & monitor reliable LLM apps. Tracing, evals, guardrails, LLMOps.
github安装
资源实测增长git clone https://github.com/ContextJet-ai/awesome-llm-observability ~/.claude/skills/awesome-llm-observability33GitHub 星标+2 (+6.5 %) - 2活跃打开来源 ↗
Curated + scored map of official MCP servers and agents for DevOps, Cloud, SRE, and Platform Engineering — every entry rated on production access, approval gates, and audit evidence.
github资源实测增长78GitHub 星标+1 (+1.3 %)