rag-architecture-review
Review an existing Retrieval-Augmented Generation system and find why it underperforms. Use when asked to review or audit a RAG pipeline, diagnose wrong/ungrounded answers from a 'chat with your docs' feature, or improve an already-built knowledge assistant. Produces a staged review — ingestion, chunking, retrieval, reranking, generation, evaluation — with prioritised findings, root causes, and concrete fixes.
npx skills add mohitagw15856/pm-claude-skills --skill rag-architecture-review --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# RAG Architecture Review Skill A RAG system that "hallucinates sometimes" is almost never one bug — it's a chain where the weakest stage caps quality, and the symptom (a wrong answer) is far from the cause (a chunk that was never retrieved). This skill reviews an existing pipeline stage by stage, isolates where quality leaks, and ranks fixes by impact so you work the biggest lever first. (Designing a new system from scratch? Use [`rag-design-doc`](../rag-design-doc/SKILL.md).) ## Working from a brief Given a partial description ("it uses pgvector and sometimes makes things up"), **deliver the full staged review anyway** — infer the likely setup for each unstated stage, label the inference, and flag what to confirm. Never withhold the review for missing detail; a labelled assumption plus "confirm this" beats a blank. ## Required Inputs Ask for these only if they aren't already provided (else infer and label): - **The current architecture** — ingestion, chunking, embedding model, vector store, retrieval (top-k, hybrid?), reranking, and the generation prompt. - **The symptoms** — examples of bad answers (wrong, ungrounded, stale, refuses) with the expected answer. - **The corpus** —
- Working from a brief
- Required Inputs
- Output Format
- RAG Review: [system]
- Quality Checks
- Anti-Patterns
- Based On
What does the rag-architecture-review skill do?
Review an existing Retrieval-Augmented Generation system and find why it underperforms. Use when asked to review or audit a RAG pipeline, diagnose wrong/ungrounded answers from a 'chat with your docs' feature, or improve an already-built knowledge assistant. Produces a staged review — ingestion, chunking, retrieval, reranking, generation, evaluation — with prioritised findings, root causes, and concrete fixes.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill rag-architecture-review --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.