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agentic-rag-evaluator

Acts as the verification and grounding layer in Retrieval-Augmented Generation (RAG) pipelines.

Skill by smartrus

IndexedMIT
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/smartrus-agentic-rag-evaluator

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Acts as the verification and grounding layer in Retrieval-Augmented Generation (RAG) pipelines. Evaluates retrieved context chunks for factual accuracy, relevance, and completeness before they reach the generation stage. Detects hallucination risk, stale data, source conflicts, and insufficient context. Trigger when: rag evaluation, rag quality, retrieval quality check, grounding check, hallucination detection, context verification, rag pipeline audit, retrieval accuracy, evaluate rag. Do NOT trigger: building RAG pipelines from scratch, vector database setup or tuning, prompt engineering for LLMs, general data quality auditing without RAG context, or training data validation (use data-poisoning-auditor).

Use cases: backend, data, ml, security

Reviews

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/agentic-rag-evaluator

What's inside

Skill name
agentic-rag-evaluator
Description
Acts as the verification and grounding layer in Retrieval-Augmented Generation (RAG) pipelines. Evaluates retrieved context chunks for factual accuracy, relevance, and completeness before they reach the generation stage. Detects hallucination risk, stale data, source conflicts, and insufficient context. Trigger when: rag evaluation, rag quality, retrieval quality check, grounding check, hallucination detection, context verification, rag pipeline audit, retrieval accuracy, evaluate rag. Do NOT trigger: building RAG pipelines from scratch, vector database setup or tuning, prompt engineering for LLMs, general data quality auditing without RAG context, or training data validation (use data-poisoning-auditor).
License
MIT
Instructions
1 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (3)

  • SKILL.md
  • evals.json · evals/
  • rag_evaluator.py · scripts/

Read SKILL.md on GitHub

More from smartrus/claude-skills-and-apps

Signals

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Last commit (this folder)
Mar 23, 2026 (7 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
Repository
github.com/smartrus/claude-skills-and-apps
Website
smartrus.github.io/claude-skills-and-apps/
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Source
GitHubgithub-graphql

More from smartrus

Cite this page

agentic-rag-evaluator skill. Agent Mart. https://agentmart.dev/skills/smartrus-agentic-rag-evaluator (last updated 2026-10-24)