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Claude Eval Harness

affaan-m/everything-claude-code

Formal evaluation framework for Claude Code sessions that applies evaluation-driven development to define capability and regression checks, run deterministic and model graders, and track pass@k/pass^k reliability metrics before shipping.

Code Model Evaluation and Benchmarking

evaluating-code-models

Orchestra-Research/AI-Research-SKILLs

A comprehensive toolkit for evaluating the performance of code generation models. It supports benchmarking against industry standards like HumanEval, MBPP, and MultiPL-E across multiple languages. Use this tool to quantitatively compare different LLM coding abilities and measure code synthesis quality using pass@k metrics.

LLM Evaluation Harness

evaluating-llms-harness

Orchestra-Research/AI-Research-SKILLs

Evaluates large language models across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag) with standardized prompts and metrics, making it easy to benchmark HuggingFace or API models, compare releases, and track training progress.

LangChain Observability Setup

langchain-observability

jeremylongshore/claude-code-plugins-plus-skills

Guide for instrumenting LangChain applications with LangSmith tracing, Prometheus metrics, OpenTelemetry spans, structured logging, Grafana dashboards, and alerting to monitor health and performance in staging or production.

Langfuse Observability Setup

langfuse-observability

jeremylongshore/claude-code-plugins-plus-skills

Set up comprehensive Langfuse observability with Prometheus metrics, Grafana dashboards, and AlertManager rules to monitor LLM operations, track latency, costs, and errors, and ensure integration health.

LangSmith LLM Observability

langsmith-observability

Orchestra-Research/AI-Research-SKILLs

LangSmith centralizes tracing, evaluation, and monitoring for LLM applications, letting teams debug prompts, run regression tests, collect latency/cost metrics, and integrate with OpenAI, Anthropic, LangChain, or LlamaIndex to keep production systems observable.

LLM Evaluation Toolkit

sickn33/antigravity-awesome-skills

Guides comprehensive evaluation of LLM applications with automated metrics, human reviews, and LLM-as-judge patterns to benchmark prompts, detect regressions, and validate deployments.

Mistral Observability Stack

mistral-observability

jeremylongshore/claude-code-plugins-plus-skills

Instrument Mistral AI clients, expose Prometheus metrics, configure alerts, and build Grafana dashboards to keep API usage, latency, cost, and errors in check.

Model Evaluation Metrics

model-evaluation-metrics

jeremylongshore/claude-code-plugins-plus-skills

Automates guidance for evaluating machine learning models, covering best practices, sample code, and validation patterns triggered by mentions of model evaluation metrics.

OpenEvidence Observability Setup

openevidence-observability

jeremylongshore/claude-code-plugins-plus-skills

Configure OpenEvidence clinical AI integrations with Prometheus metrics, OpenTelemetry tracing, structured logging, and Grafana dashboards so you can monitor health, latency, errors, cache behavior, and alerts.

OpenRouter Usage Analytics

openrouter-usage-analytics

jeremylongshore/claude-code-plugins-plus-skills

Implements tracking, dashboards, and verification steps to analyze OpenRouter usage patterns, helping teams optimize costs and monitor integrations with concrete metrics and usage-driven insights.

Deep Learning Optimization

optimizing-deep-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Optimizes deep learning models by analyzing architecture, data, and metrics to select optimizers, learning rate schedules, and regularization strategies, then outputs optimized code and evaluates accuracy, time, and resource usage.

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