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Recsys Engineering

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jhljx
recsys-engineering

Design, implement, debug, and review industrial recommendation-system architecture or algorithms using released PDFs, curated examples, and runnable templates.

Overview

Publisherjhljx
RepositoryRecSys-Industrial-Book
Skill namerecsys-engineering
Stars
467
Forks
31
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by jhljx on GitHub. Read the source before you install it.

Installation

Install the Recsys Engineering AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/jhljx/RecSys-Industrial-Book/tree/main/.agents/skills/recsys-engineering
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/jhljx/RecSys-Industrial-Book.git /tmp/RecSys-Industrial-Book
mkdir -p .claude/skills
cp -r /tmp/RecSys-Industrial-Book/.agents/skills/recsys-engineering .claude/skills/recsys-engineering
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Recsys Engineering in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Recsys Engineering on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Recsys Engineering is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Recommendation-system engineering

Resolve constraints that change implementation: objective, QPS, P99, data/feature scale, freshness, consistency, runtime, deployment, availability, privacy, and cost.

Search the local PDF index and read cited pages. Keep 本书依据, repository convention, and engineering assumptions separate. Reuse runnable templates and label [MOCK] teaching substitutes.

Services require explicit contracts, timeouts, overload/degradation, observability, version consistency, rollback, and capacity. Models require objective, sampling, feature-time semantics, offline/online parity, complexity, and evaluation.

Run the changed path. Report 本书依据, 工程实现, 验证, and unresolved 待业务确认.

Frequently asked questions

What does the Recsys Engineering AI skill do?

Design, implement, debug, and review industrial recommendation-system architecture or algorithms using released PDFs, curated examples, and runnable templates.

Why use Recsys Engineering on TypingMind?

Because you install it once and use it with any model. Recsys Engineering is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Recsys Engineering in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jhljx/RecSys-Industrial-Book/tree/main/.agents/skills/recsys-engineering. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Recsys Engineering?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Recsys Engineering?

As many as you like. As long as a model supports skills, you can use Recsys Engineering with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Recsys Engineering AI skill free?

It is published on GitHub by jhljx. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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