Nature Academic Search

Community

YuanyuanMa03

nature-academic-search

Multi-source literature search, citation verification, MeSH search strategy, citation file management (.nbib/.ris/.bib conversion), and reference management (BibTeX, related articles, ID conversion) via MCP tools (PubMed, CrossRef, arXiv). Use when the user needs coordinated multi-step literature workflows beyond a single MCP call.

Overview

Publisher	YuanyuanMa03
Repository	`academic-research-skills`
Skill name	`nature-academic-search`
Stars	76
Forks	7
Bundled files	43
License	MIT
Links	Skill source Repository

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.
43 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by YuanyuanMa03 on GitHub. Read the source before you install it.

Installation

Install the Nature Academic 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.
https://github.com/YuanyuanMa03/academic-research-skills/tree/main/plugins/nature-academic-search/skills/nature-academic-search
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/YuanyuanMa03/academic-research-skills/tree/main/plugins/nature-academic-search/skills/nature-academic-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/YuanyuanMa03/academic-research-skills.git /tmp/academic-research-skills
mkdir -p .claude/skills
cp -r /tmp/academic-research-skills/plugins/nature-academic-search/skills/nature-academic-search .claude/skills/nature-academic-search

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

Use it in TypingMind

Enable Nature Academic 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 Nature Academic 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 Nature Academic 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.

Academic Search

Multi-source literature search, citation verification, citation format conversion, and reference management via MCP tools.

MCP Tools

Bundled MCP Server (academic-search)

The bundled MCP server provides these tools — use these names when calling the server:

Tool	Purpose
`search_papers`	Multi-source search across CrossRef, PubMed, arXiv (concurrent)
`get_paper_by_id`	Fetch paper by DOI, PMID, or arXiv ID
`get_citation`	Formatted citation output (APA, MLA, BibTeX, etc.)
`lookup_mesh`	MeSH term exploration and hierarchy

External MCP Tools (require separate installation)

The following tools are referenced in workflows but require external MCP servers to be installed separately. If unavailable, fall back to the bundled search_papers tool.

Tool	Source	Best For
`pubmed_search_articles`	PubMed MCP	Biomedical, MeSH, clinical trials
`search_crossref`	paper-search MCP	Cross-disciplinary, citation counts
`search_arxiv`	paper-search MCP	Preprints (physics, math, CS, biology)

Extended Search (external only)

Tool	Source	Best For
`search_google_scholar`	paper-search MCP	Broad academic search (scraped)
`search_semantic_scholar`	paper-search MCP	Citation graph, field-of-study filters
`search_biorxiv`	paper-search MCP	Biology preprints
`search_medrxiv`	paper-search MCP	Medical preprints
`search_webofscience`	paper-search MCP	Curated index, citation reports
`search_scopus`	paper-search MCP	Broad scholarly database

PubMed Utilities

Tool	Purpose
`pubmed_fetch_articles`	Full metadata by PMID
`pubmed_find_related`	Related article discovery
`pubmed_format_citations`	APA / MLA / BibTeX / RIS formatting
`pubmed_convert_ids`	DOI ↔ PMID ↔ PMCID conversion
`pubmed_lookup_mesh`	MeSH term exploration and hierarchy
`pubmed_lookup_citation`	Bibliographic citation → PMID lookup

Source Routing

See Source Tiers & Reliability for the complete reliability classification and fallback routing rules. The T1→T2→T3 fallback chain is the standard execution order across all workflows.

Quick guide:

User need	Primary (T1)	Secondary (T2)	Last Resort (T3)
Medical / clinical	PubMed	Semantic Scholar	Google Scholar
Cross-disciplinary	CrossRef	Semantic Scholar	Scopus
Preprints / CS / physics	arXiv	bioRxiv / medRxiv	—
Exhaustive review	PubMed + CrossRef + arXiv	Semantic Scholar + bioRxiv/medRxiv	WoS / Scopus
Citation count sensitive	Semantic Scholar	CrossRef	—
Chinese literature	—	—	CNKI / 万方 (manual)

Workflows

#	Workflow	Reference
1	Multi-Source Literature Search	wf1
2	Citation Verification	wf2
3	MeSH Search Strategy	wf3
4	Citation File Management	wf4
5	Reference Management	wf5

Shared Modules

Module	Purpose
Dedup Engine	Unified deduplication (WFs 1, 2, 5a)
Citation Parser	Extract citations from documents (WF 2)
Search Strategy	Query construction, source selection, ranking
RIS/BibTeX Format	Format specifications and field mappings
Format Converter	Multi-source .nbib/.ris/.bib downloader

Environment Setup

API Keys (optional but recommended)

Service	Env Var	Register At	Free Tier
Semantic Scholar	`SEMANTIC_SCHOLAR_API_KEY`	api.semanticscholar.org	100 req/s with key (1/s without)
NCBI E-utilities	`NCBI_API_KEY`	ncbi.nlm.nih.gov/account	10 req/s with key (3/s without)
OpenAlex (polite pool)	`OPENALEX_MAILTO`	— (any email)	Faster pool, avoids HTTP 429

Set via export or .env file.

No-MCP CLI note: the standalone script scripts/academic_search.py (OpenAlex meta-search without the MCP server) hits HTTP 429 quickly without a polite-pool identity. Always pass --mailto <email> (or set OPENALEX_MAILTO) — verified 2026-10-29: same query failed bare and succeeded immediately with --mailto.

Proxy (if behind firewall)

bash
export http_proxy=http://127.0.0.1:7890
export https_proxy=http://127.0.0.1:7890

Pre-flight Check

bash
python scripts/preflight.py

Run before batch operations to verify API endpoints are reachable.

Format Converter Dependencies

The format converter (scripts/format-converter.py) uses Python stdlib only — no extra dependencies. Run python scripts/format-converter.py --test to verify the conversion pipeline.

Error Handling

MCP tool unavailable: report specific failure, continue with remaining tools.
No results: broaden terms, try alternative sources, suggest user refine query.
Script failure (2x): fall back to manual generation from MCP-fetched metadata.

Limitations

Google Scholar and Semantic Scholar are scraped (not API-backed) — results may vary.
Chinese literature (CNKI / 万方) not indexed by CrossRef or PubMed.
Citation counts may be delayed (CrossRef updates monthly).

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 Nature Academic Search AI skill do?

Why use Nature Academic Search on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/YuanyuanMa03/academic-research-skills/tree/main/plugins/nature-academic-search/skills/nature-academic-search. 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 Nature Academic 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 Nature Academic Search?

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

Is the Nature Academic Search AI skill free?

Yes. It is published on GitHub by YuanyuanMa03 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

Academic Search

MCP Tools

Bundled MCP Server (academic-search)

External MCP Tools (require separate installation)

Extended Search (external only)

PubMed Utilities

Source Routing

Workflows

Shared Modules

Environment Setup

API Keys (optional but recommended)

Proxy (if behind firewall)

Pre-flight Check

Format Converter Dependencies

Error Handling

Limitations

Bundled files

Frequently asked questions

Related AI Skills

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