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Agent skill

Create Generation Plugin

by NomaDamas in NomaDamas/AutoRAG-Research

Guide developers through creating a custom generation pipeline plugin for AutoRAG-Research.

Apache-2.0Auto-check: notesAI & LLM Engineering

Install Create Generation Plugin

skills CLI
$ npx skills add NomaDamas/AutoRAG-Research --skill create-generation-plugin -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install NomaDamas/AutoRAG-Research create-generation-plugin --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/NomaDamas/AutoRAG-Research.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/create-generation-plugin .claude/skills/create-generation-plugin && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
create-generation-plugin
GitHub stars
149
Token cost
~871 tokens
SKILL.md length
237 words
Files
1
Skills in repo
7
Repo updated
First seen
Licence
Apache-2.0

At a glance

Guide developers through creating a custom generation pipeline plugin for AutoRAG-Research.

  • Works in 3 steps: Scaffold → Implement → Write tests and install
  • Building a new RAG generation strategy (e.g.
  • SKILL.md covers Workflow, Key Files and Examples
  • Calls pip

What it does

Create Generation Plugin is an agent skill from NomaDamas/AutoRAG-Research. Guide developers through creating a custom generation pipeline plugin for AutoRAG-Research. Walks through scaffolding, implementing BaseGenerationPipeline methods, composing with retrieval pipelines, writing YAML configs, testing, and installing. Use when building a new RAG generation strategy (e.g., chain-of-thought RAG, multi-hop RAG).

Its SKILL.md is about 870 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Retrieval-augmented generation and Project scaffolding. It works with LangChain. The repository describes itself as: Automate your RAG research. The licence is Apache-2.0.

When your agent uses it

  • Building a new RAG generation strategy (e.g.
  • Chain-of-thought RAG

Example prompts

  • “/create-generation-plugin”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Bash, Read, Write, Edit

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Scaffold
  2. Implement
  3. Write tests and install

What it can do on your machine

Read from SKILL.md and the folder at commit a473cf0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Create Generation Plugin loads about 871 tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 237 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~871

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read, Write, Edit

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from NomaDamas/AutoRAG-Research at commit a473cf0, republished under its Apache-2.0 licence (© NomaDamas). 237 words, ~871 tokens.

Download SKILL.mdSave it as .claude/skills/create-generation-plugin/SKILL.md (or your agent's skills folder).
name
create-generation-plugin
description
Guide developers through creating a custom generation pipeline plugin for AutoRAG-Research. Walks through scaffolding, implementing BaseGenerationPipeline methods, composing with retrieval pipelines, writing YAML configs, testing, and installing. Use when building a new RAG generation strategy (e.g., chain-of-thought RAG, multi-hop RAG).
allowed-tools
Bash, Read, Write, Edit

Create Generation Plugin

Workflow

1. Scaffold
bash
autorag-research plugin create my_rag --type=generation

Read the generated pipeline.py, pyproject.toml, YAML config, and test file to understand the structure.

2. Implement

For the shared pipeline implementation and testing rules, read:

  • ai_instructions/pipeline_implementer.md
  • ai_instructions/pipeline_test_writer.md
  • ai_instructions/pipeline_architecture_mapper.md

Implement the _generate(query_id, top_k) method. This is where your RAG strategy lives.

Available attributes inside the pipeline:

  • self._llm — LangChain BaseLanguageModel (use await self._llm.ainvoke(prompt))
  • self._retrieval_pipeline — composed retrieval pipeline (use await self._retrieval_pipeline._retrieve_by_id(query_id, top_k))
  • self._service — GenerationPipelineService (use self._service.get_chunk_contents(chunk_ids), self._get_query_text(query_id))

Must return a GenerationResult(text=...) (from autorag_research.orm.service.generation_pipeline).

DO NOT add your own asyncio.gather, asyncio.Semaphore, or any concurrency control. The base pipeline's run() already handles parallel execution of all queries via run_with_concurrency_limit() (semaphore + gather), controlled by the max_concurrency config parameter. Your _generate method is called once per single query — just implement the retrieve-and-generate logic for that one query.

Custom parameters: Add fields to your config class and pass them via get_pipeline_kwargs() → accept them in the pipeline constructor.

Inherited config fields (from BaseGenerationPipelineConfig):

  • llm — LLM model string (auto-converted to LangChain model instance)
  • retrieval_pipeline_name — name of the retrieval pipeline to compose with (Executor injects it)
3. Write tests and install

Use langchain_core.language_models.FakeListLLM to mock the LLM in tests.

bash
cd my_rag_plugin
pip install -e .   # or: uv pip install -e .
cd .. && autorag-research plugin sync

Verify: ls configs/pipelines/generation/my_rag.yaml

Key Files

PurposePath
Base config classautorag_research/config.py → BaseGenerationPipelineConfig
Base pipeline classautorag_research/pipelines/generation/base.py → BaseGenerationPipeline
Service + GenerationResultautorag_research/orm/service/generation_pipeline.py
Plugin entry point discoveryautorag_research/plugin_registry.py

Examples

Study these existing implementations for patterns:

  • autorag_research/pipelines/generation/basic_rag.py — Simple retrieve-then-generate (start here)
  • autorag_research/pipelines/generation/ircot.py — Interleaving retrieval with chain-of-thought
  • autorag_research/pipelines/generation/et2rag.py — Entity-aware RAG
  • autorag_research/pipelines/generation/main_rag.py — Main RAG pipeline
  • YAML configs: configs/pipelines/generation/basic_rag.yaml, configs/pipelines/generation/ircot.yaml

© NomaDamas, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/create-generation-plugin of NomaDamas/AutoRAG-Research.

Open the folder on GitHubat commit a473cf0

Compare with similar skills

Create Generation Plugin next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Create Generation Plugin compared with similar skills
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Create Generation Plugin this skillNomaDamas/AutoRAG-Research149—~871Automated safety check: NotesApache-2.0
SynalinksSynaLinks/synalinks-skills907—~4.8kAutomated safety check: PassApache-2.0
Dive Into LangGraphluochang212/dive-into-langgraph457—~837Automated safety check: NotesCustom licence
wdoc Referencethiswillbeyourgithub/wdoc545—~1.1kAutomated safety check: PassAGPL-3.0
Awesome Chatgpt Searchtaishi-i/awesome-ChatGPT-repositories3.3k—~3.8kAutomated safety check: PassCC0-1.0
RAG ArchitectJeffallan/claude-skills12k1 repos~2kAutomated safety check: PassMIT

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Works with

Categories

Questions about Create Generation Plugin

What does Create Generation Plugin do?

Guide developers through creating a custom generation pipeline plugin for AutoRAG-Research. Create Generation Plugin is an agent skill from NomaDamas/AutoRAG-Research. Guide developers through creating a custom generation pipeline plugin for AutoRAG-Research.

When should I use Create Generation Plugin?

Create Generation Plugin fits situations like: building a new RAG generation strategy (e.g; chain-of-thought RAG.

How do I install Create Generation Plugin in Claude Code?

Run `npx skills add NomaDamas/AutoRAG-Research --skill create-generation-plugin -a claude-code`. Or copy the skill folder (.agents/skills/create-generation-plugin in NomaDamas/AutoRAG-Research) into .claude/skills/create-generation-plugin in your project. Claude Code loads it when a task matches its description.

How do I install Create Generation Plugin in Codex?

Run `npx skills add NomaDamas/AutoRAG-Research --skill create-generation-plugin -a codex`. Or copy the skill folder (.agents/skills/create-generation-plugin in NomaDamas/AutoRAG-Research) into .agents/skills/create-generation-plugin in your project. Codex loads it when a task matches its description.

Can I use Create Generation Plugin in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NomaDamas/AutoRAG-Research --skill create-generation-plugin -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/create-generation-plugin, .gemini/skills/create-generation-plugin, .github/skills/create-generation-plugin and .opencode/skills/create-generation-plugin in your project.

What does Create Generation Plugin need to run?

Going by SKILL.md and its folder, Create Generation Plugin needs the command-line tools its instructions call (pip). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash, Read, Write, Edit.

Does Create Generation Plugin access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Create Generation Plugin safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Create Generation Plugin use?

Create Generation Plugin is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Create Generation Plugin use?

About 871 tokens (SKILL.md is roughly 3.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Create Generation Plugin?

Skills that share tags, products or a category with Create Generation Plugin: Synalinks (SynaLinks/synalinks-skills, 907 stars), Dive Into LangGraph (luochang212/dive-into-langgraph, 457 stars), wdoc Reference (thiswillbeyourgithub/wdoc, 545 stars) and Awesome Chatgpt Search (taishi-i/awesome-ChatGPT-repositories, 3.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Create Generation Plugin?

NomaDamas (a GitHub organization) maintains it in NomaDamas/AutoRAG-Research, which has 149 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on August 9, 2026.

Source: NomaDamas/AutoRAG-Research on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.