Le descrizioni degli strumenti sono in inglese.
Osservabilità LLM
Monitoraggio, tracce, valutazione e qualità delle applicazioni LLM.
Utilizzo
Attività
Ordina per
121
Classifica degli strumenti
Classifica per crescita misurata e normalizzata tra le fonti. I valori grezzi mantengono la propria finestra; una variazione richiede almeno due rilevazioni in 7 giorni.
- 1Attivo
pyxen
AgenteA lightweight Python library that decouples agentic runtime from applications it builds
githubcrescita misurataApri fonte ↗
1stelle GitHubstabile - 2Attivo
Multi-agent quality gate skill for Claude Code that researches, reviews, tests and challenges AI-generated work before the final answer.
githubcrescita misurataApri fonte ↗
Installa
git clone https://github.com/ma-nucho-pro/supervisor-skill-claude ~/.claude/skills/supervisor-skill-claude2stelle GitHubstabile - 3Attivo
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.
githubcrescita misurataApri fonte ↗
22stelle GitHubstabile - 4Attivo
bakeoff
SkillTurn one decision into a judged tournament of solutions, then pick the best — a Claude Code skill that generates candidates, auto-derives the rubric, judges independently, and returns a defensible winner.
githubcrescita misurataApri fonte ↗
Installa
/plugin marketplace add CoriChui/bakeoff10stelle GitHubstabile - 5Attivo
skill-graveyard
SkillAudit which Claude Code skills you actually use — surface dead installs and hallucinated invocations from your session logs.
githubcrescita misurataApri fonte ↗
Installa
/plugin marketplace add sfrangulov/skill-graveyard10stelle GitHubstabile - 6Attivo
agent-stack
SkillProduction patterns for agent orchestrators, harnesses, evals, MCP/A2A interoperability, memory, provider routing, and LLM usage metering.
githubcrescita misurataApri fonte ↗
Installa
git clone https://github.com/ssheleg/agent-stack ~/.claude/skills/agent-stack2stelle GitHubstabile - 7Attivo
axiom
SkillAxiom is a curated marketplace of shared plugins for Claude Code and Codex.
githubcrescita misurataApri fonte ↗
Installa
git clone https://github.com/netopsengineer/axiom ~/.claude/skills/axiom5stelle GitHubstabile - 8Attivo
dsh-plugins
AgenteGeneric DeepSeek Harness (dsh) plugins: A2A protocol server, session storage mirror, and Langfuse observability.
githubcrescita misurataApri fonte ↗
1stelle GitHubstabile - 9Attivo
Production reliability, benchmarking, and evaluation layer for MCP agent runtimes — protocol negotiation, A2A interop, circuit breakers, connection pooling, adaptive streaming, and autoscaling, with measured throughput/latency and a…
githubcrescita misurataApri fonte ↗
3stelle GitHubstabile - 10Attivo
rashomon
SkillMeasure prompt and skill improvements with blind A/B comparison.
githubcrescita misurataApri fonte ↗
Installa
/plugin marketplace add shinpr/rashomon18stelle GitHubstabile - 11Attivo
langfuse-mcp
MCPA Model Context Protocol (MCP) server for Langfuse, enabling AI agents to query Langfuse trace data for enhanced debugging and observability
githubcrescita misurataApri fonte ↗
105stelle GitHubstabile - 12Attivo
simple-output-styles
SkillMake Claude write clearly, for everyone.
githubcrescita misurataApri fonte ↗
Installa
/plugin marketplace add stefanobaghino/simple-output-styles16stelle GitHubstabile - 13Dormiente
agenttap
AgenteReal-time debugging proxy for Agent2Agent (A2A) multi-agent systems
githubcrescita misurataApri fonte ↗
3stelle GitHubstabile - 14Attivo
headsup
SkillGlanceable Claude Code and Codex state in your terminal tabs: white=idle, blue=working, orange=waiting. Multi-terminal (iTerm2, WezTerm, AI Power Term), a live status bar with Anthropic usage limits, /sfl and /nil window save-and-restore,…
githubcrescita misurataApri fonte ↗
Installa
git clone https://github.com/wasulajr/headsup ~/.claude/skills/headsup1stelle GitHubstabile - 15Attivo
sc-prism-releases
SkillRun 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…
githubcrescita misurataApri fonte ↗
Installa
git clone https://github.com/sandhusukhdeep2/sc-prism-releases ~/.claude/skills/sc-prism-releases1stelle GitHubstabile - 16Attivo
verdict-contract
SkillYour LLM reviewer said APPROVE. Did it? A structured verdict contract: prompt rule + parser + exit-code gate in one stdlib file, with the 42 counterexamples that forced every line. Free, MIT.
githubcrescita misurataApri fonte ↗
Installa
git clone https://github.com/tonydzi/verdict-contract ~/.claude/skills/verdict-contract2stelle GitHubstabile - 17Attivo
Description Evidence-driven evaluation, benchmarking, and verified repair for Agent Skills across Codex, Claude Code, Gemini CLI, and Antigravity.
githubcrescita misurataApri fonte ↗
Installa
git clone https://github.com/MaxLaurieHutchinson/skill-evaluation-graph ~/.claude/skills/skill-evaluation-graph2stelle GitHubstabile
Risorse didattiche e di riferimento
Classifica mista: la crescita misurata ha la precedenza. Queste risorse restano accessibili separatamente e non partecipano alla classifica principale.
- 1AttivoApri fonte ↗
Handbook técnico aberto sobre engenharia de IA em produção: ML tradicional, LLMs, RAG, agentes, segurança, observabilidade, FinOps e deployment.
githubRisorsacrescita misurata1stelle GitHubstabile - 2AttivoApri fonte ↗
trigger_tree
SkillDocumentation-discovery telemetry for Claude Code — heat/cold maps, health grade, evidence-backed router fixes. 100% local, zero tokens. /tt
githubInstalla
Risorsacrescita misurata/plugin marketplace add Hedde/trigger_tree14stelle GitHubstabile - 3AttivoApri fonte ↗
Agentic_AI_Engineer
AgenteMy complete journey to becoming an Agentic AI Engineer through structured learning, projects, experiments, and production-ready implementations of modern AI systems.
githubRisorsacrescita misurata18stelle GitHubstabile - 4AttivoApri fonte ↗
tunelab
SkillClaude Code plugin for LLM fine-tuning, distillation, and evaluation — decide whether you need fine-tuning at all, distill your LLM logs into small local models (MLX/LoRA), evaluate with held-out discipline, and learn the why at every step.
githubInstalla
Risorsamomentum stimato/plugin marketplace add rchaz/tunelab6stelle GitHub·