skills/43-wentorai-research-plugins/skills/literature/fulltext/SKILL.md
16 full-text access skills. Trigger: accessing paper PDFs, bulk downloading, open access, text mining. Design: legal full-text retrieval from open repositories, archives, and preprint servers.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research fulltext-skillsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Select the skill matching the user's need, then read its SKILL.md.
| Skill | Description | |-------|-------------| | arxiv-latex-source | Download and parse LaTeX source files from arXiv preprints | | bioc-pmc-api | Access PMC Open Access articles in BioC format for text mining | | core-api-guide | Search and retrieve open access research papers via CORE aggregator | | dataverse-api | Deposit and discover research datasets via Harvard Dataverse API | | doaj-api | Search open access journals and articles in the DOAJ directory | | hal-archive-api | Access French and European research via the HAL open archive API | | institutional-repository-guide | Access papers from institutional and subject repositories at scale | | interlibrary-loan-guide | Access papers through interlibrary loan and document delivery services | | open-access-guide | Navigate open access policies, repositories, and legal full-text retrieval me... | | open-access-mining-guide | Mine open access full-text repositories for research data extraction | | osf-api | Manage open science projects and preprints via the OSF REST API | | pmc-ftp-bulk-download | Bulk download PMC Open Access articles via FTP for large-scale mining | | pmc-oai-api | PubMed Central OAI-PMH metadata harvesting | | preprint-servers-guide | Guide to preprint servers across scientific disciplines | | unpaywall-api | Find free legal full-text versions of scholarly articles via Unpaywall | | zotero-ai-butler-guide | AI-powered paper summarization plugin for Zotero |
development
Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.
development
Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.
testing
Performs placebo-in-time sensitivity analysis with hierarchical null model and optional Bayesian assurance. Use when checking model robustness, verifying lack of pre-intervention effects, or estimating study power.
data-ai
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware custom priors.