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Systematic review

Skill thada2402/AutoResearchClaw/researchclaw/skills/builtin/experiment/systematic-review

Generate research papers autonomously by chatting with OpenClaw, using Python 3.11+, with a self-evolving framework and extensive test coverage.

Install
npx -y skills add thada2402/AutoResearchClaw --skill systematic-review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Structured methodology for comprehensive literature review following PRISMA guidelines. Use during literature search and screening stages.

SKILL.md

1.0 KB, as published. Nobody here has run it

Systematic Review Best Practice

Follow PRISMA-like methodology for literature search:

  1. Define clear inclusion/exclusion criteria BEFORE searching
  2. Use multiple databases (Semantic Scholar, arXiv, OpenAlex)
  3. Search with both broad and narrow queries
  4. Screen by title/abstract first, then full text
  5. Extract: method, dataset, metrics, key findings
  6. Synthesize gaps and opportunities, not just summaries
  7. Prioritize recent (last 2-3 years) high-citation papers
  8. Include at least one seminal/foundational paper per sub-topic

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.