claudecodex

deepeval

为 AI 应用添加 DeepEval 评估、追踪、数据集、Confident AI 报告和迭代改进循环的 skills。

2 on GitHubby Confident AIv1.0.0Apache-2.0updated yesterdaydeveloper-tools
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Plugin deepeval from marketplace kael-odin-plugins-zh in kael-odin/claude-plugins-zh. Commands read from the repo's manifest — today.

What it installs

Skills (3)

  • deepeval-otel

    Export raw OpenTelemetry traces from an AI application to Confident AI's Observatory. TRIGGER when the user wants to send OpenTelemetry or OTLP traces/spans from an LLM app, agent, RAG pipeline, or chatbot to Confident AI; configure the Confident AI OTLP endpoint; set confident.span.* or confident.t

  • deepeval-tracing

    Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI. TRIGGER when the user wants to add DeepEval tracing or @observe to an LLM app, agent, RAG pipeline, or chatbot; wire a framework, model-provider, or vector-database integration (LangGraph, LangCha

  • deepeval

    DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; send results to C

View source on GitHub kael-odin.github.io

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cockroachdb

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将 Claude Code 直接连接到你的 CockroachDB 集群,进行实操数据库工作——探索 schema、编写优化的 SQL、调试查询,并管理分布式数据库集群。该插件提供 14 个工具,涵盖两个活跃的 MCP 后端(自托管 MCP Toolbox 和托管式 CockroachDB Cloud MCP Server)、三个专用 agent(DBA、Developer、Operator)、覆盖 6 个运维领域的 32 个 skill,以及内置安全 hook。

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databricks

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面向 CLI、Apps、Lakebase、Model Serving、Lakeflow Jobs、Spark Declarative Pipelines、Declarative Automation Bundles(DAB)以及经典版到无服务器迁移的 Databricks skill。

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clay

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在 Claude Code 中使用 Clay:设置并登录 clay CLI,查询和分析 Clay 表格,在 Clay 的 GTM 数据库中搜索人员和公司,管理受众、信号、例程和工作流,并起草和审阅 Sequencer 营销活动。包含自动批准该插件自身 clay CLI 调用和 Clay skills 的 hooks;需要 Clay 账户。

38 skills · hooks

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amplitude

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将 Amplitude 作为专业分析工具使用——埋点接入 Amplitude、发现产品机会、分析图表、创建仪表盘、管理实验,并洞察用户与账户。

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data-agent-kit

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本插件为在 Google Cloud 上工作的数据工程师与数据库从业者提供一套专用技能,相当于一位专家助手:在常用的编码代理里用自然语言描述需求,即可设计复杂的数据管道、用 dbt 转换数据、编写 Spark 与 BigQuery SQL 笔记本,并在 GCP 数据生态中编排端到端工作流。

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Maintain deepeval?

This page updates itself from your repo. Add the badge to your README, or get it Featured to pin it above the organic results with a followed link to your site.

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