rag-eval SKILL.md skillA
rag-eval from agentscope-ai/openjudge is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add agentscope-ai/openjudge/rag-eval@git:20260708.2151defPins git:20260708.2151def in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- agentscope-ai/openjudge
- Path
skills/eval_pipeline/05-rag-eval/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260708.2151def, committed Jul 8, 2026
- Size
- 9,684 bytes
- Repository stars
- 1,054
- License
- Apache-2.0
Use when the user has a RAG (Retrieval-Augmented Generation) system and wants to evaluate its quality — separating retrieval issues from generation issues. Also use when the user mentions RAG evaluation, faithfulness checking, hallucination detection in RAG, retrieval quality, chunking optimization, or "is my RAG pipeline working." Outputs a diagnostic matrix that pinpoints whether problems are in retrieval or generation.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# RAG Eval Evaluate RAG systems by diagnosing retrieval and generation separately. A single "RAG accuracy" number hides whether the problem is finding the right documents or using them correctly. This skill separates them so you know what to fix. ## When to Activate - User has a RAG pipeline (retriever + generator) with traces - User wants to know if their RAG system hallucinates - User is optimizing chunking strategy and needs before/after comparison - User wants to build a RAG evaluation dataset ## Checklist You MUST create a task for each item and complete them in order: 1. **Load RAG traces** — validate query + context + answer triples 2. **Separate retrieval vs generation** — determine which layers to evaluate 3. **Run faithfulness evaluation** — is the answer grounded in retrieved docs? 4. **Run retrieval evaluation** — are the right documents retrieved? 5. **Build diagnostic matrix** — cross-tabulate to find root cause 6. **Output findings** — prioritized issues with concrete fixes ## Fast path: run the bundled script Once each trace has a faithfulness judgment (and ideally a retrieval signal), build the …
Read the whole file at its exact version.
How to install
mdr add agentscope-ai/openjudge/rag-eval@sha256:fead7ab1ca8392e2The line at the top of this page pins the label git:20260708.2151def, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_g3vwissiitmzmtbl)
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Versions
The registry has recorded 1 version of this file, committed on Jul 8, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (9684 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
agentscope-ai/openjudge · 1,054 stars · license Apache-2.0 · pushed 2026-11-05 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_g3vwissiitmzmtbl GET https://markdownregistry.com/api/v1/resolve?ref=agentscope-ai/openjudge/rag-eval GET https://markdownregistry.com/api/v1/blob/fead7ab1ca8392e2cd81d8412546e975a210061adc83003a6770f1c146bb5ec6
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.