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Zotero Research Assistant

Community
Bubble-OoO
zotero-research-assistant

Access and configure a user's local or cloud Zotero library without MCP by executing the bundled JSON CLI. Use for Skill setup or troubleshooting, Zotero connection configuration, collection/folder browsing, exact collection item retrieval, library search, paper metadata, PDF full text, annotations, notes, tags, comparisons, and literature reviews. Trigger when the user mentions Zotero, a Zotero collection/folder such as “目录下的论文”, papers in their library, PDF annotations, adding Zotero notes/tags, or fixing this Skill. Never invent library contents; ground every claim in CLI output.

Overview

PublisherBubble-OoO
Repositoryzotero-research-assistant-skill
Skill namezotero-research-assistant
Stars
98
Forks
11
Bundled files
9
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.

  • 9 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Bubble-OoO on GitHub. Read the source before you install it.

Installation

Install the Zotero Research Assistant 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/Bubble-OoO/zotero-research-assistant-skill/tree/main
  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/Bubble-OoO/zotero-research-assistant-skill.git \
  .claude/skills/zotero-research-assistant
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Zotero Research Assistant 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 Zotero Research Assistant 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 Zotero Research Assistant 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.

Zotero Research Assistant

Use the bundled scripts/run_zotero.py; do not require or configure MCP. Resolve the absolute path of this skill directory before running it. The runner can delegate to a Conda or virtual-environment interpreter configured with ZOTERO_PYTHON. Read references/setup.md only when placing, configuring, or troubleshooting the Skill.

Setup and troubleshooting behavior

When asked to install, configure, validate, or repair the Skill, perform all safe and reversible terminal and file operations directly. Do not tell the user to run commands or edit .env manually. Detect the operating system and available Python 3.10+ or Conda environments, preserve existing configuration and credentials, request approval for protected filesystem or package-install operations when required, and validate with health afterward. Ask the user only for actions the Agent cannot safely complete, such as enabling Zotero desktop communication, supplying a missing secret through a secure local method, or approving an external write. Never print secrets.

Required behavior

  1. Run python <skill-dir>/scripts/run_zotero.py health before the first Zotero operation in a task. If it returns ok: false, report the error and stop; do not answer from memory.
  2. Treat ok: false from every command as a hard failure. Never transform an error or empty result into a positive claim.
  3. Cite each mentioned library item as [First author, year, Zotero key] when those fields exist.
  4. Distinguish a Zotero collection from a topic query. Never search the whole library using a collection name as a keyword.

Route requests

Collection or folder requests

When the user says “目录/分类/文件夹中的论文”:

  1. Resolve the collection exactly:

    python <skill-dir>/scripts/run_zotero.py find-collection "<name-or-path>"

  2. If the result is ambiguous, show the returned paths and ask the user to choose. Do not guess.

  3. Read its bibliographic items:

    python <skill-dir>/scripts/run_zotero.py collection-items "<collection-key>" --recursive --limit 200

Use --recursive for the natural-language meaning “目录下” unless the user explicitly requests only items directly filed in that collection. Report the resolved collection path and whether subcollections were included.

Topic, title, author, or keyword requests

Search top-level bibliographic items:

python <skill-dir>/scripts/run_zotero.py search "<query>" --limit 50

To search only inside a known collection, pass --collection "<key-or-path>"; add --recursive when subcollections are in scope.

Paper details and source text

  • Metadata: python <skill-dir>/scripts/run_zotero.py item <item-key>
  • Attachments and notes: python <skill-dir>/scripts/run_zotero.py children <item-key>
  • Annotations: python <skill-dir>/scripts/run_zotero.py annotations <item-key>
  • PDF text: python <skill-dir>/scripts/run_zotero.py read <item-key> --start 0 --max-chars 12000

For summaries, comparisons, quotations, or literature reviews, read source text rather than inferring from titles. If hasMore is true and later sections matter, continue with --start <nextStart>. State the coverage used; do not call a partial window the full paper.

Write safety

Treat notes and tags as external writes.

  1. Prepare and display the complete note, replacement text, or tag list.

  2. Wait for explicit user confirmation in a later message.

  3. Only then run the matching command with --confirm-write:

    • add-note <item-key> "<html>" --confirm-write
    • update-note <note-key> "<html>" --confirm-write
    • add-tags <item-key> <tag>... --confirm-write

Never infer confirmation from the original request. Never add --confirm-write before the user has seen the exact change.

Output discipline

  • Preserve Zotero keys, collection paths, result counts, and error messages.
  • Exclude child attachments, notes, and annotations when the user asks for papers. Include parentless standalone PDFs as documents and clearly label standaloneAttachment: true because they may lack author, year, and other bibliographic metadata.
  • If no result is returned, say that no matching item was found under the stated scope.
  • For multi-paper synthesis, identify the candidate set first, then read each selected paper or its stored abstract before drawing conclusions.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Zotero Research Assistant AI skill do?

Access and configure a user's local or cloud Zotero library without MCP by executing the bundled JSON CLI. Use for Skill setup or troubleshooting, Zotero connection configuration, collection/folder browsing, exact collection item retrieval, library search, paper metadata, PDF full text, annotations, notes, tags, comparisons, and literature reviews. Trigger when the user mentions Zotero, a Zotero collection/folder such as “目录下的论文”, papers in their library, PDF annotations, adding Zotero notes/tags, or fixing this Skill. Never invent library contents; ground every claim in CLI output.

Why use Zotero Research Assistant on TypingMind?

Because you install it once and use it with any model. Zotero Research Assistant 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 Zotero Research Assistant in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Bubble-OoO/zotero-research-assistant-skill/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Zotero Research Assistant?

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 Zotero Research Assistant?

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

Is the Zotero Research Assistant AI skill free?

It is published on GitHub by Bubble-OoO. 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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