rag-observability-evals

Name: rag-observability-evals
Author: BagelHole

SKILLWorkflowcommunity

v0.0.0BagelHoleMITUpdated 4mo agoSource →

Monitor and evaluate RAG systems with retrieval quality metrics, groundedness checks, hallucination detection, and continuous regression testing.

Community-submitted skill. Not yet reviewed by the Forge team. Full prompt content may not be available.Request review →

47Repo stars

1Clients

1Formats

4mo agoLast update

Skill

AuthorBagelHole

Version0.0.0

LicenseMIT

CategoryWorkflow

Formatsskill.md

PromptNot published

Compatibility

Claude✓ Supported

Cursor—

Copilot—

ChatGPT—

Gemini—

About

Monitor and evaluate RAG systems with retrieval quality metrics, groundedness checks, hallucination detection, and continuous regression testing.

Keywords

skillclaude

No dependency coverage

This entry publishes no npm package, so Forge has no dependency tree for it. That is a gap in coverage — not a statement that it has no dependencies.

thedotmack/claude-memPersistent Context Across Sessions for Every Agent – Captures everything your agent does
ruvnet/ruflo🌊 The leading agent meta-harness for Claude. Deploy intelligent multi-agent swarms, coord
chopratejas/headroomCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer
1Panel-dev/MaxKB🔥 MaxKB is an open-source platform for building enterprise-grade agents. 强大易用的开源企业级智能体平台
topoteretes/cogneeCognee is the open-source AI memory platform for agents. Give your AI agents persistent lo
Upsonic/UpsonicBuild autonomous AI agents in Python.
the-open-agent/openagent⚡️next-generation personal AI assistant powered by LLM, RAG and agent loops, supporting co
MinishLab/sembleFast and Accurate Code Search for Agents. Uses ~98% fewer tokens than grep+read