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Magnus HedemarkandGitHub 035e58d3e3 docs(routing): remediate description and neighbor boundaries
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Haystack — Production Search & NLP Pipelines (deepset)

An expert-level skill for building production search and NLP pipelines with Haystack. Pipelines are validated DAGs with typed components and explicit connections.

Why Install This Skill

When your agent loads this skill, it becomes a Haystack expert who can:

  • Design pipeline DAGs — add_component + connect with typed input/output slots
  • Build RAG pipelines — document indexing + query pipelines with embedding retrieval
  • Create agentic systems — tool-using agents with ReAct pattern
  • Integrate generative AI — PromptBuilder (Jinja2) + LLM generators
  • Evaluate pipeline quality — faithfulness, relevancy, and custom metrics
  • Deploy with Hayhooks — REST API deployment for production

What You Get

Directory Purpose
SKILL.md Core paradigm, where-to-start table, framework comparison
references/ Deep dives into pipeline design, RAG, agents, evaluation, Hayhooks, and framework comparisons

Framework Comparison

Haystack uses explicit Pipeline DAGs (add_component + connect) — different from LangChain's LCEL pipe operator and LlamaIndex's query engines. Pipelines are validated at declaration time.

Requirements

Python 3.8+ with haystack-ai package.

Quick Start

Start with the setup and first workflow in SKILL.md, then use the linked resources for the specific task you need to complete.

Triggers

Use this skill for the task types and keywords described in its SKILL.md description.