What problem it solves

Academic research requires researchers to move through literature work, writing, review, revision, and finalization while preserving the accuracy and integrity of claims. The project addresses this by providing structured skills and an orchestrated pipeline that support research tasks without removing the researcher from important decisions.

Key features

• Deep research — Provides a multi-agent research team with guided planning, systematic-review support, intent detection, dialogue monitoring, and optional reference verification.

  Source: README

• Academic paper writing — Supports multi-agent paper writing with style calibration, writing-quality checks, LaTeX hardening, visualization, citation conversion, and figure verification.

  Source: README

• Academic paper review — Provides a multi-perspective peer-review process with dynamic reviewers, a devil's advocate, evidence-anchored judgments, optional calibration, and traceability of revision requests.

  Source: README

• Academic pipeline — Orchestrates a ten-stage workflow with adaptive checkpoints, claim verification, experiment provenance, optional reproducibility-lock configuration, and narrative regression checks.

  Source: README

• Study screening — Supports protocol-driven screening for systematic, scoping, and rapid reviews with blinded reviewers, adjudication, resumable batches, quality control, PRISMA counts, and RIS handoff.

  Source: README

Quick start

Copied verbatim from the project's README.

/plugin marketplace add Imbad0202/academic-research-skills
/plugin install academic-research-skills

Who it may suit

This may suit researchers, students, and academic writing teams that want structured assistance across literature review, manuscript preparation, and peer-review revision. It may also suit readers who need explicit checkpoints and human confirmation while using AI-assisted research workflows.

Topics to discuss

• How can the integrity gates be evaluated against real manuscript and citation-verification tasks?

• Which workflow stages benefit most from human confirmation, and where could confirmation be streamlined?

• What additional integrations or adapters would make the research pipeline more useful to academic teams?

Written by ReadmeX AI from the project's README, source and public GitHub data; it may contain mistakes.

Read the original README https://github.com/Imbad0202/academic-research-skills#readme

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