Agent skill

Deep Literature Search

by wentorai in wentorai/research-plugins

Multi-source exhaustive literature search across academic databases

MITAuto-check passedResearch & Science

Install Deep Literature Search

skills CLI
$ npx skills add wentorai/research-plugins --skill deep-literature-search -a claude-code

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

GitHub CLI
$ gh skill install wentorai/research-plugins deep-literature-search --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/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/literature/search/deep-literature-search .claude/skills/deep-literature-search && 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
deep-literature-search
GitHub stars
298
Used in
1 other repo
Token cost
~1.7k tokens
SKILL.md length
735 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Multi-source exhaustive literature search across academic databases

  • Works in 4 steps: Define the Research Question → Identify Key Concepts and Synonyms → Build the Search String → …
  • Tasks that involve Literature review
  • SKILL.md covers Overview, Search Strategy Design, Multi-Database Execution and Deduplication and Screening, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Deep Literature Search is an agent skill from wentorai/research-plugins. Multi-source exhaustive literature search across academic databases

Its SKILL.md is about 1.7k 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 Research & Science, covering Literature review. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Literature review

Example prompts

  • “/deep-literature-search”

Workflow steps

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

  1. Define the Research Question
  2. Identify Key Concepts and Synonyms
  3. Build the Search String
  4. Adapt for Each Database

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    Links to these hosts (documentation or services it may open):

    • prisma-statement.org
    • training.cochrane.org

    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

Deep Literature Search loads about 1.7k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 735 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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 passed

The automated check found no risky patterns in SKILL.md.

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 wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 735 words, ~1,726 tokens.

Download SKILL.mdSave it as .claude/skills/deep-literature-search/SKILL.md (or your agent's skills folder).
name
deep-literature-search
description
Multi-source exhaustive literature search across academic databases

Overview

A deep literature search goes beyond a quick Google Scholar query. It is a methodical, multi-source search process designed to identify all relevant publications on a topic with minimal omissions. This level of thoroughness is required for systematic reviews, meta-analyses, grant applications, and dissertation literature reviews where comprehensiveness is not optional—it is a methodological requirement.

This skill provides a structured framework for planning, executing, and documenting exhaustive literature searches across multiple academic databases. It covers query formulation using controlled vocabularies, database selection strategy, deduplication, screening workflows, and PRISMA-compliant documentation of the search process.

The framework is database-agnostic and can be applied across disciplines, from biomedical sciences (PubMed, Cochrane) to social sciences (PsycINFO, ERIC), engineering (IEEE Xplore, Compendex), and multidisciplinary databases (Web of Science, Scopus, OpenAlex).

Search Strategy Design

Step 1: Define the Research Question

Use the PICO/PEO/SPIDER framework appropriate to your field:

  • PICO (clinical/biomedical): Population, Intervention, Comparison, Outcome
  • PEO (qualitative): Population, Exposure, Outcome
  • SPIDER (mixed methods): Sample, Phenomenon of Interest, Design, Evaluation, Research type

Example: "What is the effect of mindfulness-based interventions (I) on academic stress (O) in graduate students (P) compared to no intervention (C)?"

Step 2: Identify Key Concepts and Synonyms

Break your research question into 2-4 key concepts. For each concept, list all synonyms, related terms, abbreviations, and controlled vocabulary terms:

ConceptSynonyms and Related Terms
Mindfulnessmindfulness-based stress reduction, MBSR, meditation, mindful awareness
Academic stressstudy stress, exam anxiety, academic burnout, student distress
Graduate studentspostgraduate, doctoral students, PhD candidates, master's students
Step 3: Build the Search String

Combine concepts using Boolean logic:

("mindfulness" OR "MBSR" OR "mindfulness-based stress reduction" OR "meditation")
AND
("academic stress" OR "study stress" OR "exam anxiety" OR "academic burnout")
AND
("graduate student*" OR "postgraduate*" OR "doctoral student*" OR "PhD candidate*")

Key syntax rules:

  • Use OR within concept groups (broadens)
  • Use AND between concept groups (narrows)
  • Use * for truncation (e.g., student* matches students, student's)
  • Use "" for exact phrases
  • Use NOT sparingly and document its use
Step 4: Adapt for Each Database

Each database has its own syntax and controlled vocabulary. You must translate your master search string for each target:

  • PubMed: Use MeSH terms alongside free-text; syntax uses [MeSH] tags
  • Scopus: Uses TITLE-ABS-KEY() field codes
  • Web of Science: Uses TS= (Topic) and TI= (Title) field tags
  • IEEE Xplore: Uses "Command Search" with field codes
  • OpenAlex: Uses concept IDs and filter parameters in the API

Multi-Database Execution

DisciplinePrimary DatabasesSupplementary
BiomedicalPubMed, Cochrane, EmbaseCINAHL, PsycINFO
Computer ScienceIEEE Xplore, ACM DL, DBLPScopus, arXiv
Social SciencesPsycINFO, ERIC, Sociological AbstractsWeb of Science
EngineeringCompendex, IEEE XploreScopus, Web of Science
MultidisciplinaryWeb of Science, Scopus, OpenAlexGoogle Scholar (supplementary)
Show full SKILL.md (319 more words)Show less
Execution Checklist

For each database:

  1. Translate the master search string to the database's syntax
  2. Run the search and record the date, exact query string, and result count
  3. Export all results in a structured format (RIS, BibTeX, or CSV)
  4. Save a screenshot or copy of the search interface showing the query and results count
Grey Literature and Supplementary Sources

A truly exhaustive search also covers non-indexed sources:

  • Preprint servers: arXiv, bioRxiv, medRxiv, SSRN
  • Dissertations: ProQuest Dissertations, EThOS, institutional repositories
  • Conference proceedings: Check major conferences in your field
  • Citation chaining: Forward (who cited this?) and backward (what did this cite?) from key papers
  • Expert consultation: Contact domain experts for unpublished or in-press work
  • Trial registries: ClinicalTrials.gov, WHO ICTRP (for clinical topics)

Deduplication and Screening

Deduplication Process

After collecting results from multiple databases, expect 20-40% overlap. Use reference management software to deduplicate:

  1. Import all exported results into a single library (Zotero, EndNote, or Rayyan)
  2. Run automatic deduplication using DOI matching first, then title+author matching
  3. Manually review flagged potential duplicates—automated tools miss ~5-10%
  4. Record the count: total imported, duplicates removed, unique records remaining
Screening Workflow

Apply a two-stage screening process:

  • Title/Abstract screening: Review each unique record against your inclusion/exclusion criteria. Mark as Include, Exclude, or Maybe.
  • Full-text screening: Retrieve full texts for all Include and Maybe records. Apply detailed eligibility criteria.

Use screening tools like Rayyan, Covidence, or ASReview to manage this process, especially for large result sets (500+ records).

PRISMA Documentation

Document your entire search process using the PRISMA 2020 flow diagram:

Records identified (N = ?)
  ├── Database 1 (n = ?)
  ├── Database 2 (n = ?)
  └── Other sources (n = ?)
Duplicates removed (n = ?)
Records screened (n = ?)
Records excluded (n = ?)
Full-text assessed (n = ?)
Full-text excluded with reasons (n = ?)
Studies included (n = ?)

Save your complete search strategies (exact query strings, dates, result counts per database) as supplementary material for your publication. This transparency is essential for reproducibility and is increasingly required by journals.

References

© wentorai, MIT. 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 skills/literature/search/deep-literature-search of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Deep Literature Search 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.

Deep Literature Search compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Deep Literature Search this skillwentorai/research-plugins2981 repos~1.7kAutomated safety check: PassMIT
Nature Paper CardYuan1z0825/nature-skills47k2 repos~2.1kAutomated safety check: PassApache-2.0
Systematic Review ScreenerImbad0202/academic-research-skills51k—~8.4kAutomated safety check: PassCustom licence
Literature Reviewneflibata-feng/MyArxiv-Agent12620 repos~5.9kAutomated safety check: NotesMIT
Preprint Search on bioRxivLigphiDonk/Oh-my--paper73912 repos~3.7kAutomated safety check: PassMIT
Academic Paper Writing PipelineImbad0202/academic-research-skills51k—~16kAutomated safety check: PassCustom licence

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Questions about Deep Literature Search

What does Deep Literature Search do?

Multi-source exhaustive literature search across academic databases. Deep Literature Search is an agent skill from wentorai/research-plugins.

When should I use Deep Literature Search?

Deep Literature Search fits situations like: tasks that involve Literature review.

How do I install Deep Literature Search in Claude Code?

Run `npx skills add wentorai/research-plugins --skill deep-literature-search -a claude-code`. Or copy the skill folder (skills/literature/search/deep-literature-search in wentorai/research-plugins) into .claude/skills/deep-literature-search in your project. Claude Code loads it when a task matches its description.

How do I install Deep Literature Search in Codex?

Run `npx skills add wentorai/research-plugins --skill deep-literature-search -a codex`. Or copy the skill folder (skills/literature/search/deep-literature-search in wentorai/research-plugins) into .agents/skills/deep-literature-search in your project. Codex loads it when a task matches its description.

Can I use Deep Literature Search 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 wentorai/research-plugins --skill deep-literature-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deep-literature-search, .gemini/skills/deep-literature-search, .github/skills/deep-literature-search and .opencode/skills/deep-literature-search in your project.

What does Deep Literature Search need to run?

SKILL.md names no scripts, command-line tools or credentials: Deep Literature Search is instructions for the agent only.

Does Deep Literature Search access the network?

SKILL.md names 2 domains. As links in the text: prisma-statement.org and training.cochrane.org. This is read from the text; nothing was executed.

Is Deep Literature Search safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Deep Literature Search use?

Deep Literature Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deep Literature Search use?

About 1.7k tokens (SKILL.md is roughly 6.9k 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 Deep Literature Search?

Skills that share tags, products or a category with Deep Literature Search: Nature Paper Card (Yuan1z0825/nature-skills, 47k stars), Systematic Review Screener (Imbad0202/academic-research-skills, 51k stars), Literature Review (neflibata-feng/MyArxiv-Agent, 126 stars) and Preprint Search on bioRxiv (LigphiDonk/Oh-my--paper, 739 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deep Literature Search?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

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