Conduct systematic literature reviews with search planning, screening, synthesis, and citation checks.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "literature-review" skill from askskill: 1. Download https://raw.githubusercontent.com/affaan-m/ECC/main/skills/scientific-thinking-literature-review/SKILL.md 2. Save it as ~/.claude/skills/scientific-thinking-literature-review/SKILL.md 3. Reload skills and tell me it's ready
Create a systematic literature review plan for the clinical effects of continuous glucose monitoring in patients with type 2 diabetes, including search terms, database selection, inclusion and exclusion criteria, screening workflow, evidence extraction table, and final review structure.
A complete review workflow with search strategy, screening criteria, evidence log template, and writing outline.
I am researching privacy-preserving methods for federated learning in edge computing. Help me design a literature screening framework that separates core papers, review papers, and low-relevance sources, and provide an evidence synthesis approach and citation checking checklist.
An actionable screening framework, source prioritization method, synthesis guidance, and citation check points.
Help me complete a literature review for a course paper on the impact of remote work on team collaboration efficiency: first plan the search strings, then organize thematic groups, and finally generate a review draft structure with citation-check reminders.
A step-by-step plan from search to writing, with a clear literature review section structure.
Use this skill when the task is to find, screen, synthesize, and cite a body of academic or technical literature.
Ask the user which level of rigor is needed. If unspecified, default to a scoping review for exploratory work and a systematic review for publication or clinical claims.
Convert the prompt into a searchable research question.
For clinical or biomedical work, use PICO:
For technical work, use:
Create a search protocol before collecting sources:
Minimum useful database set:
Keep a search log that makes the review reproducible:
| Database | Date searched | Query | Filters | Results | Export |
| --- | --- | --- | --- | ---: | --- |
| PubMed | 2026-05-11 | `("CRISPR"[tiab] OR "Cas9"[tiab]) AND "sickle cell"[tiab]` | 2020:2026, English | 86 | PMID list |
| arXiv | 2026-05-11 | `CRISPR sickle cell gene editing` | q-bio, 2020:2026 | 9 | BibTeX |
Save raw IDs, URLs, DOIs, abstracts, and notes separately from the final prose.
Deduplicate in this order:
Record how many duplicates were removed.
Screen in stages:
For systematic work, record exclusion reasons:
Use a structured extraction table:
| Study | Design | Population/Data | Method | Comparator | Outcome | Key finding | Limitations |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Author Year | RCT/cohort/review/etc. | sample or corpus | method | baseline | measured outcome | result | caveat |
For technical papers, include dataset, benchmark, metric, baseline, and reproducibility notes.
Group evidence by theme rather than summarizing papers one by one.
Useful synthesis lenses:
Separate claims by confidence:
Before finalizing:
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Create PRISMA 2020 systematic reviews with verified citations and IMRAD drafts.
Search peer-reviewed papers and research methodology guidance from your AI workflow.
Search PubMed literature, MeSH terms, PMIDs, and citation data efficiently.
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Synthesize user research into themes, insights, and prioritized recommendations.
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