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affaan-m/literature-review

affaan-m

literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

New~1.3kUpdated Jul 14, 2026

Literature Review

Use this skill when the task is to find, screen, synthesize, and cite a body of academic or technical literature.

When to Use

  • Building a systematic, scoping, or narrative literature review.
  • Synthesizing the state of the art for a research question.
  • Finding gaps, contradictions, or future-work directions.
  • Preparing citation-backed background sections for papers or reports.
  • Comparing evidence across peer-reviewed papers, preprints, patents, and technical reports.

Review Types

  • Narrative review: broad synthesis; useful for orientation.
  • Scoping review: maps concepts, methods, and evidence gaps.
  • Systematic review: predefined protocol, reproducible search, explicit screening and exclusion.
  • Meta-analysis: systematic review plus quantitative effect aggregation.

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.

Workflow

1. Define the Question

Convert the prompt into a searchable research question.

For clinical or biomedical work, use PICO:

  • Population
  • Intervention or exposure
  • Comparator
  • Outcome

For technical work, use:

  • system or domain
  • method or intervention
  • comparison baseline
  • evaluation metric

Create a search protocol before collecting sources:

  • databases to search
  • date range
  • languages
  • publication types
  • inclusion criteria
  • exclusion criteria
  • exact search strings

Minimum useful database set:

  • PubMed for biomedical and life-sciences literature.
  • arXiv for CS, math, physics, quantitative biology, and preprints.
  • Semantic Scholar or Crossref for broad academic discovery.
  • Domain-specific sources when relevant, such as clinical-trial registries, patent databases, standards bodies, or official technical docs.

3. Search and Log Evidence

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.

4. Deduplicate

Deduplicate in this order:

  1. DOI
  2. PMID or arXiv ID
  3. exact title
  4. normalized title plus first author and year

Record how many duplicates were removed.

5. Screen Sources

Screen in stages:

  1. title
  2. abstract
  3. full text

For systematic work, record exclusion reasons:

  • wrong population
  • wrong intervention
  • wrong outcome
  • not primary research
  • duplicate
  • unavailable full text
  • outside date range

6. Extract Data

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.

7. Synthesize

Group evidence by theme rather than summarizing papers one by one.

Useful synthesis lenses:

  • strongest evidence
  • conflicting evidence
  • methodological weaknesses
  • population or dataset limits
  • recency and replication
  • practical implications
  • unanswered questions

Separate claims by confidence:

  • High confidence: replicated, high-quality evidence across sources.
  • Medium confidence: plausible but limited by sample, method, or recency.
  • Low confidence: early, speculative, single-source, or weakly measured.

8. Verify Citations

Before finalizing:

  • verify DOI, PMID, arXiv ID, or official URL
  • check author names and publication year
  • do not cite a paper for a claim it does not make
  • mark preprints as preprints
  • distinguish reviews from primary evidence

Output Template

# Literature Review: <Topic>

Generated: <date>
Review type: <narrative | scoping | systematic | meta-analysis>
Search window: <dates>
Databases: <list>

## Research Question

## Search Strategy

## Inclusion and Exclusion Criteria

## Evidence Summary

## Thematic Synthesis

## Gaps and Limitations

## References

## Search Log

Pitfalls

  • Do not treat search snippets as evidence.
  • Do not mix preprints, reviews, and primary studies without labeling them.
  • Do not omit negative or conflicting findings.
  • Do not claim systematic-review rigor without a reproducible protocol.
  • Do not use a single database for a broad claim unless the scope is explicitly limited to that database.
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Overall Score

84/100

Grade

B

Good

Safety

90

Quality

82

Clarity

85

Completeness

78

Summary

This skill provides a structured workflow for conducting literature reviews across academic, biomedical, technical, and scientific domains. It guides users through defining research questions, planning searches across multiple databases (PubMed, arXiv, Semantic Scholar), screening sources, extracting evidence, synthesizing findings by theme, and verifying citations—with explicit templates and pitfall warnings to ensure reproducibility and rigor.

Detected Capabilities

research planningdatabase querying guidancesource deduplicationscreening workflowdata extraction and tabulationevidence synthesiscitation verificationsearch log documentationstructured output generation

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

systematic literature reviewresearch question synthesisevidence screeningliterature gap analysiscitation verification workflowbiomedical research backgroundstate of the art survey

Use Cases

  • Preparing systematic or scoping literature reviews for academic publication
  • Synthesizing state-of-the-art evidence for research questions in biomedical or technical domains
  • Building citation-backed background sections for papers, reports, or grant proposals
  • Identifying research gaps, contradictions, and future-work directions in a field
  • Conducting evidence comparisons across peer-reviewed papers, preprints, patents, and technical reports

Quality Notes

  • Well-structured workflow with clear sequential steps (define question → plan search → screen → extract → synthesize → verify)
  • Provides domain-specific guidance (PICO for clinical work, custom metrics for technical work) and review-type selection (narrative, scoping, systematic, meta-analysis)
  • Includes practical templates for search logs and data-extraction tables that ensure reproducibility
  • Explicitly documents pitfalls (not treating snippets as evidence, omitting negative findings, misrepresenting review type) to guide agents away from common errors
  • Recommends minimum database set with domain-specific additions, reducing over-reliance on a single source
  • Clear confidence stratification (high/medium/low) for synthesized claims helps avoid overstating evidence
  • All supporting tools (PubMed, arXiv, Semantic Scholar, DOI/PMID lookup) are real, widely-accessible services with clear access boundaries
  • MIT license indicates permissive open-source origin
  • Limitations section is thorough but could benefit from explicit guidance on when to escalate (e.g., disagreement between reviewers, low-quality evidence base)
  • Does not cover conflict-of-interest disclosure, though relevant for clinical work; could mention publication bias assessment methods
Model: claude-haiku-4-5-20251001Analyzed: Jul 14, 2026

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Version History

  1. v1.1

    Content updated

    ✦ AINo detectable behavioral changes in instruction content or supporting files.

    2026-07-14

    Latest
  2. v1.0

    2026-05-15

    View This VersionInitial version

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