Die Werkzeugbeschreibungen sind auf Englisch.

LLM-Beobachtbarkeit

Monitoring, Traces, Bewertung und Qualität von LLM-Anwendungen.

Anwendungsfall

Aktivität

Sortieren nach

118

Werkzeug-Rangliste

Ranked by normalized popularity across sources. Rohwerte behalten ihr eigenes Zeitfenster; eine Änderung erfordert mindestens zwei Messungen in 7 Tagen.

  1. 1
    Aktiv

    Mide si tu agente de IA cumple las reglas que le escribiste. Lee el historial local de Claude Code y devuelve un porcentaje por regla. Sin instalar nada, sin red, biblioteca estándar.

    githubgemessenes WachstumQuelle öffnen ↗

    Installieren git clone https://github.com/jleonceo/adherencia-reglas ~/.claude/skills/adherencia-reglas

    1GitHub-Sternestabil
  2. 2
    Aktiv

    Vendor-neutral OpenTelemetry tracing for A2A agents and MCP services, with W3C context propagation and privacy-safe telemetry.

    githubgemessenes WachstumQuelle öffnen ↗

    1GitHub-Sternestabil
  3. 3
    Aktiv

    8 MCP SMB products — standalone AI servers for SMBs: Guardrails, FinOps, Observability, Router, Trust Score, Memory, ThinkSecure, A2A Lite. 37 tools, TNC credits billing.

    githubgemessenes WachstumQuelle öffnen ↗

    1GitHub-Sternestabil
  4. 4
    Aktiv

    Skill instalable para Claude Code que mide si tu agente cumple las reglas establecidas. Lee el historial de sesiones de tu disco y devuelve un porcentaje por regla de cumplimiento. Sin instalar nada, sin red, biblioteca estándar.

    githubgemessenes WachstumQuelle öffnen ↗

    Installieren /plugin marketplace add jleonceo/skill-adherencia-reglas

    1GitHub-Sternestabil
  5. 5

    Agent
    Aktiv

    The agent framework where the model never holds the trigger — every consequential action clears your policy first, waits for a human when it matters, and lands on a record you can verify. Build on it, or put it around the agent you already…

    githubgemessenes WachstumQuelle öffnen ↗

    1GitHub-Sternestabil
  6. 6

    Sonstige
    Aktiv

    Local-first Agentic AI Infrastructure Platform with LLM Gateway, Agent DAG Runtime, MCP Tool Hub, A2A Agent Mesh, Local RAG, Tool Sandbox and Observability.

    githubgemessenes WachstumQuelle öffnen ↗

    1GitHub-Sternestabil
  7. 7
    Aktiv

    Run many AIs on one board and keep control of all of it. Deterministic code decides who acts — never a model. A privacy floor keeps sensitive work on your machine, your own tests decide what counts as done, and every action lands on a…

    githubgeschätztes MomentumQuelle öffnen ↗

    Installieren git clone https://github.com/sandhusukhdeep2/sc-prism-releases ~/.claude/skills/sc-prism-releases

    1GitHub-Sterne
  8. 8
    Aktiv

    Agent Skill that asks: should there be an agentic system at all? Then designs, builds, audits, verifies, and ports systems—from workflows to governed teams.

    githubgeschätztes MomentumQuelle öffnen ↗

    Installieren git clone https://github.com/ingcontartese-netizen/multi-agent-system-architect-v2 ~/.claude/skills/multi-agent-system-architect-v2

    1GitHub-Sterne
  9. 9

    Agent
    Aktiv

    面向长程研发任务的 Java Agent Harness,支持 A2A 跨语言协作、可恢复执行、上下文工程与 Eval 驱动开发。

    githubgemessenes WachstumQuelle öffnen ↗

    0GitHub-Sternestabil
  10. 10

    Agent
    Aktiv

    Provide clear documentation for AgentStack’s MCP protocol, plugins, and ecosystem API with usage examples and tool references.

    githubgemessenes WachstumQuelle öffnen ↗

    0GitHub-Sternestabil
  11. 11
    Aktiv

    Architecture-first Python scaffold for an auditable multi-agent corporate credit desk using A2A, MCP, deterministic credit policies, model routing, and OpenTelemetry.

    githubgemessenes WachstumQuelle öffnen ↗

    0GitHub-Sternestabil
  12. 12

    Agent
    Ruhend

    Contract-based testing for LLM agents: hybrid evaluation, multi-agent + A2A, deterministic replay.

    githubgemessenes WachstumQuelle öffnen ↗

    0GitHub-Sternestabil
  13. 13
    Ruhend

    A Python proof-of-concept for tracing multi-turn Agent-to-Agent (A2A) conversations as a single unified MLflow trace for LLM observability and evaluation.

    githubgemessenes WachstumQuelle öffnen ↗

    0GitHub-Sternestabil
  14. 14

    Agent
    Aktiv

    A2A green-agent orchestrator for evaluating agents on the AppWorld benchmark, built on the AgentBeats SDK

    githubgemessenes WachstumQuelle öffnen ↗

    0GitHub-Sternestabil
  15. 15

    Agent
    Ruhend

    AgentOps: Multi-agent infrastructure remediation platform. A2A protocol, agent coordination, HITL approval, auto-rollback.

    githubgemessenes WachstumQuelle öffnen ↗

    0GitHub-Sternestabil
  16. 16

    Sonstige
    Aktiv

    🔑 HomeStream · 家园·流 — 零成本自托管多Agent协作框架,通往AI世界的那把钥匙 | Zero-cost self-hosted multi-agent framework — The key to AI world

    githubgemessenes WachstumQuelle öffnen ↗

    0GitHub-Sternestabil
  17. 17
    Aktiv

    Governed local-LLM observability: model policy, prompt scanner, capture proxy, 21 tools.

    mcpgemessenes WachstumQuelle öffnen ↗

    Installieren claude mcp add ai-guardian -- uvx ai-guardian-aiops

    0GitHub-Sternestabil

Lern- und Referenzressourcen

Ranked by normalized popularity across sources. Diese Ressourcen bleiben getrennt zugänglich und fließen nicht in die Hauptwertung ein.

  1. 1
    AktivQuelle öffnen ↗

    Handbook técnico aberto sobre engenharia de IA em produção: ML tradicional, LLMs, RAG, agentes, segurança, observabilidade, FinOps e deployment.

    githubRessourcegemessenes Wachstum
    1GitHub-Sternestabil