Claude-skill-registry context-llm-pipeline

RAG pipeline, embeddings, LLM interactions, and flow orchestration.

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/context-llm-pipeline" ~/.claude/skills/majiayu000-claude-skill-registry-context-llm-pipeline && rm -rf "$T"

manifest: skills/data/context-llm-pipeline/SKILL.md

LLM Pipeline Context

Overview

Core AI logic including RAG flows, LLM service orchestration, and vector retrieval.

Active Files

Orchestration (Flows)

```
backend/flows/ingestion_flow.py
```
- Document ingestion
```
backend/flows/scraping_flow.py
```
- Scrape orchestration
```
backend/flows/template_review_flow.py
```
- LLM review flow

Services

```
backend/services/llm/orchestrator.py
```
- Main LLM handler
```
backend/services/llm/pipeline.py
```
- Pipeline logic
```
backend/services/llm/analyzer.py
```
- Analysis logic
```
backend/services/research/zai.py
```
- ZAI research integration

backend/services/search_pipeline_service.py

- Search pipeline

Shared Packages

```
packages/llm-common/
```
- Shared types and utilities (Submodule)

Usage

Use this skill when working on RAG, prompt engineering, or vector search logic.