Paper Search

OrganizationPopular

open-gitagent

paper-search

Academic paper search via Google Scholar using Serper API

Overview

Publisher	open-gitagent
Repository	`opengap`
Skill name	`paper-search`
Stars	2.9K
Forks	348
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 open-gitagent on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/open-gitagent/opengap/tree/main/examples/nvidia-deep-researcher/skills/paper-search

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/open-gitagent/opengap.git /tmp/opengap
mkdir -p .claude/skills
cp -r /tmp/opengap/examples/nvidia-deep-researcher/skills/paper-search .claude/skills/paper-search

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paper Search 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 Paper Search 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 Paper Search 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.

Paper Search

Search for academic papers and scholarly articles via Google Scholar using the Serper API.

When to Use

Finding peer-reviewed research on a topic
Locating seminal papers and their citation counts
Searching for systematic reviews and meta-analyses
Grounding claims in academic literature

How to Use

Formulate an academic-style search query
Optionally specify year filters to narrow results by publication date
Call paper_search with the query
Review results for relevance, citation count, and recency

Result Format

Results are returned in markdown format:


**Title of Paper**
Authors: Author A, Author B
Year: 2024 | Citations: 142
Snippet: Brief excerpt from the paper abstract or body...
URL: https://scholar.google.com/...

Constraints

Results sourced from Google Scholar via Serper API
Supports year filtering (e.g., papers from 2020-2025)
Snippet may be from abstract or body text
Each call counts toward the researcher's 8-call limit per task

Best Practices

Use domain-specific terminology for better results
Include key author names if known
Filter by year for rapidly evolving topics
Prefer highly-cited papers for foundational claims

Frequently asked questions

What does the Paper Search AI skill do?

Academic paper search via Google Scholar using Serper API

Why use Paper Search on TypingMind?

Because you install it once and use it with any model. Paper Search 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 Paper Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/open-gitagent/opengap/tree/main/examples/nvidia-deep-researcher/skills/paper-search. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Paper Search?

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 Paper Search?

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

Is the Paper Search AI skill free?

Yes. It is published on GitHub by open-gitagent under the MIT license. 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Paper Search

When to Use

How to Use

Result Format

Constraints

Best Practices

Frequently asked questions

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