Results for “reindexing”

Trigger a full or incremental reindex of the RAG corpus

Guides selection of Qdrant search strategies including hybrid search, reranking, relevance feedback, MMR, and discovery APIs to improve retrieval quality.

Reranking retrieved documents with cross-encoders and LLM rerankers. Cohere Rerank v3, Voyage rerank-2, BGE reranker, ColBERT late interaction, Jina reranker. Cost and latency tradeoffs, top-K in / top-N out strategy. USE WHEN: user mentions "rerank", "reranker", "cross-encoder", "Cohere Rerank", "Voyage rerank", "BGE reranker", "ColBERT", "Jina reranker", "bi-encoder" DO NOT USE FOR: initial retrieval - use `advanced-retrieval` or `hybrid-search`; query rewriting - use `query-transformations`; agent decisions - use `agentic-rag`

Manages vector embeddings with Pinecone for semantic search, recommendation, and RAG pipelines.

Execute a relaunch on a decayed-but-valuable article (Lesson 5 audit + Lesson 8 "don't abandon old winners"). Take a page the audit flagged as decaying or rank-slipping, refresh it against the LIVE SERP (freshen data, re-verify searcher intent, squeeze new keywords, refresh visuals), bump its published date, and re-promote it as if brand new. The "update ~half the calendar" half of the strategy. Triggered from the audit's Relaunch plan.

Rebuild Knowledge Vault index.md from disk truth per capture-llm-wiki schema. Use when vault structure drifted or after bulk ingest of pursuit folders. Karpathy LLM wiki maintenance skill.

Plan, debug, tune, evaluate, export, or deploy public Nemotron embedding and reranking retrieval recipes using the current checkout.

Analyze codebase structure, generate domain-specific sub-skills (UI, Backend, Database, etc.), and create agent-guidance files to help AI agents navigate and develop consistently within a project. Use when onboarding to a new codebase, creating project documentation, or setting up agent guidance systems.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Refactor legacy codebases, migrate outdated frameworks, and implement gradual modernization. Handles technical debt, dependency updates, and backward compatibility. Use PROACTIVELY for legacy system updates, framework migrations, or technical debt reduction.

Use this skill for search indexing, embeddings, RAG chunking, freshness, retrieval evaluation, source citations. Trigger when the task involves ai engineering work related to Search Indexing RAG, implementation, audits, debugging, strategy, or validation.

Build or modify a RAG retrieval pipeline with vector store search, corpus routing, citation rendering, and book fidelity enforcement.