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Literature Searcher

Community
Dianel555
literature-searcher

Search CrossRef, OpenAlex, PubMed, Semantic Scholar, and optional Scopus; deduplicate results, download open-access PDFs by DOI, classify papers, monitor new results, and analyze coverage. Use when asked to search literature, monitor a topic, download an open-access paper, classify papers, or analyze literature gaps.

Overview

PublisherDianel555
RepositoryDSkills
Skill nameliterature-searcher
Stars
65
Forks
8
Bundled files
14
LicenseMIT
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.

  • 14 bundled files

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

  • Open source

    Published by Dianel555 on GitHub. Read the source before you install it.

Installation

Install the Literature Searcher 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/Dianel555/DSkills/tree/main/skills/literature-searcher
  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/Dianel555/DSkills.git /tmp/DSkills
mkdir -p .claude/skills
cp -r /tmp/DSkills/skills/literature-searcher .claude/skills/literature-searcher
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Literature Searcher 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 Literature Searcher 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 Literature Searcher 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.

Literature Searcher

Run all commands from skills/literature-searcher. The package uses only the Python standard library.

Search

bash
python -m literature_searcher.searcher search "ionogel flexible sensor" --limit 10
python -m literature_searcher.searcher search "solid electrolyte" \
  --platform openalex --platform semantic_scholar --year-from 2020 --year-to 2024

Without --platform, the command searches CrossRef, OpenAlex, PubMed, and Semantic Scholar. Scopus requires ELSEVIER_API_KEY.

Download Open-Access PDFs

bash
python -m literature_searcher.searcher download --doi 10.1016/j.cej.2022.135593

Downloads query Unpaywall by default. Enable the optional scihub-cli fallback explicitly with --scihub-fallback auto.

Incremental Monitoring And Insight

powershell
New-Item -ItemType Directory -Force data | Out-Null
Copy-Item monitor_config.json.template data/monitor_config.json

Set queries in data/monitor_config.json, then run:

bash
python -m literature_searcher.monitor --config data/monitor_config.json
python -m literature_searcher.insight --input data/monitor_results.json

Monitoring uses the HTTPS DeepLX endpoint in DEEPLX_ENDPOINT by default and does not require a DeepL API key. To use a local OpenAI-compatible model service, set LOCAL_LLM_BASE_URL and LOCAL_LLM_MODEL, then pass --translator local_llm. Translation failures are recorded in the result JSON and do not stop monitoring.

Python API

CapabilityImportEntry point
Multi-platform searchliterature_searcher.searchersearch_papers()
Result deduplicationliterature_searcher.searchermerge_and_deduplicate()
PDF downloadliterature_searcher.downloaderDownloader.download_by_doi()
Paper classificationliterature_searcher.classifierPaperClassifier.classify()
Incremental monitoringliterature_searcher.monitorrun_monitor()
Coverage analysisliterature_searcher.insightanalyze_coverage()

PaperClassifier.classify() and batch_classify() accept both mappings and objects with paper attributes.

Configuration

The package reads these optional variables from the process environment: LITERATURE_EMAIL, OPENALEX_EMAIL, OPENALEX_API_KEY, SEMANTIC_SCHOLAR_API_KEY, ELSEVIER_API_KEY, DEEPLX_ENDPOINT, LOCAL_LLM_BASE_URL, and LOCAL_LLM_MODEL. Copy .env.example to .env in the skill directory to load values automatically. Variables already exported by the calling shell take precedence.

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 Literature Searcher AI skill do?

Search CrossRef, OpenAlex, PubMed, Semantic Scholar, and optional Scopus; deduplicate results, download open-access PDFs by DOI, classify papers, monitor new results, and analyze coverage. Use when asked to search literature, monitor a topic, download an open-access paper, classify papers, or analyze literature gaps.

Why use Literature Searcher on TypingMind?

Because you install it once and use it with any model. Literature Searcher 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 Literature Searcher in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dianel555/DSkills/tree/main/skills/literature-searcher. 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 Literature Searcher?

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 Literature Searcher?

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

Is the Literature Searcher AI skill free?

Yes. It is published on GitHub by Dianel555 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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