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Magnus Hedemark 738ec715e7 Add human-focused README.md to every skill and bundle directory

Each README is written for a human audience, explaining:
- What the skill does (not what format it follows)
- What benefit the user gets from installing it
- Quick setup and usage patterns
- When to load/trigger the skill
- What scripts, references, and templates it ships

data-scientist already had a README — left unchanged.

48 READMEs added across all skill and bundle directories.

2026-07-09 22:30:12 -04:00

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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.

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