bimajanuri

Academic Writing Skill — AI skill for Claude Code

AI community

Academic writing and literature-synthesis support for AI agents, including Claude Code, OpenCode, and other Agent Skills-compatible hosts.

How to install Academic Writing Skill

This entry records only its repository, not the path inside it, so there is no exact command to give. Open bimajanuri/academic-writing-skill and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Academic Writing Skill does

Academic writing and literature-synthesis support for AI agents, including Claude Code, OpenCode, and other Agent Skills-compatible hosts. The skill covers the full path from literature discovery to final format conversion. Manuscripts are produced in English (US) academic style, while research input may be provided in Bahasa Indonesia or English.

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README

Academic Writing Skill

**Academic writing and literature-synthesis support for AI agents**, including Claude Code, OpenCode, and other Agent Skills-compatible hosts. The skill covers the full path from literature discovery to final format conversion. Manuscripts are produced in **English (US) academic style**, while research input may be provided in **Bahasa Indonesia or English**.

The skill uses a **modular, multi-method pipeline** with seven stages and a human review gate at each stage. Its **Method Selection Router** chooses the appropriate qualitative or quantitative synthesis protocol for the task.

Key Features

Method Selection Router — 6 synthesis modes: SLR (PRISMA 2020), Scoping Review (PRISMA-ScR/PCC/JBI), Meta-Ethnography (eMERGe + Noblit & Hare), Narrative Review (SANRA), Integrative Review (Whittemore & Knafl), Critical Review (appraisal lenses)
7-stage pipeline with quality gates: Explore → Plan → Write → Cite → Revise → Validate → Output
Dedicated qualitative synthesis engines:
- Reciprocal Translation Engine — 1st/2nd/3rd order constructs, reciprocal vs refutational vs line-of-argument (meta-ethnography)
- Conceptual Mapping Engine — concept taxonomy, geographic/timeline/methodological distribution, research gaps (scoping)
- Academic Debate Engine — pro/con clusters + timeline of idea development (narrative)
Shared Paper Review extraction contract: Title & Authors, Journal, Year, Purpose, Method, Key Findings, Limitations, Gaps, Theory, Novelty, Future Studies, DOI & Publisher, and provenance. Each mode can add its own fields.
Per-mode extraction matrix: SLR, PCC (scoping), 1st/2nd constructs (meta-ethnography), argument positions (narrative), qual+quant data (integrative), epistemological/methodological/bias lenses (critical)
Literature search via OpenAlex / Semantic Scholar / Crossref / DOAJ / PubMed / arXiv (all free)
Scopus Quartile filter (Q1–Q4)
*Gap Analysis (Gap Matrix)