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Skills/huangwb8/chineseresearchlatex/systematic-literature-review
systematic-literature-review logo

systematic-literature-review

huangwb8/chineseresearchlatex
836 installs2K stars
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Installation

npx skills add https://github.com/huangwb8/chineseresearchlatex --skill systematic-literature-review

Summary

当用户明确要求"做系统综述/文献综述/related work/相关工作/文献调研"时使用。AI 自定检索词,多源检索→去重→AI 逐篇阅读并评分(1–10分语义相关性与子主题分组)→按高分优先比例选文→自动生成"综/述"字数预算→资深领域专家自由写作(固定摘要/引言/子主题/讨论/展望/结论),保留正文字数与参考文献数硬校验,强制导出 PDF 与 Word。支持多语言翻译与智能编译(en/zh/ja/de/fr/es)。

SKILL.md

Systematic Literature Review

与 bensz-collect-bugs 的协作约定

  • 当用户环境中出现因本 skill 设计缺陷导致的 bug 时,优先使用 bensz-collect-bugs 按规范记录到 ~/.bensz-skills/bugs/,严禁直接修改用户本地 Claude Code / Codex 中已安装的 skill 源码。
  • 若 AI 仍可通过 workaround 继续完成用户任务,应先记录 bug,再继续完成当前任务。
  • 当用户明确要求“report bensz skills bugs”等公开上报动作时,调用本地 gh 与 bensz-collect-bugs,仅上传新增 bug 到 huangwb8/bensz-bugs;不要 pull / clone 整个 bug 仓库。

定位

  • 目标:在一个隔离工作目录内完成“检索 → 去重 → 评分 → 选文 → 写作 → 校验 → PDF/Word 导出”的完整综述流水线。
  • 适用:用户明确要系统综述、文献综述、related work、文献调研,并希望得到 LaTeX + BibTeX + PDF/Word 产物。
  • 不适用:只想补单条参考文献、只想润色已有正文、只想写普通摘要或与综述无关的文章。
  • 最高原则:以最佳可用证据和写作质量完成综述;不确定时说明处理方式,不为赶进度牺牲可信度。

输入

最少需要:

  1. {主题}:一句话主题。
  2. 可选范围:时间、语言、研究类型、数据库偏好等。
  3. 档位:Premium / Standard / Basic;未指定时读取 config.yaml 默认值。
  4. 目标字数与参考文献范围:未指定时按 config.yaml.scoring.default_*_range。
  5. 输出目录或安全化前缀:未指定时使用安全化主题名。

输出

默认交付以下核心文件:

  • {主题}_工作条件.md:输入、检索、评分、选文、结构与校验记录。
  • {主题}_review.tex:正文唯一 LaTeX 源文件。
  • {主题}_参考文献.bib:选中文献 BibTeX。
  • word_budget_run{1,2,3}.csv、word_budget_final.csv、non_cited_budget.csv:综/述字数预算。
  • {主题}_验证报告.md:字数、章节、引用一致性等验证结果。
  • {主题}_review.pdf
  • {主题}_review.docx

必要中间产物包括:

  • papers*.jsonl
  • scored_papers.jsonl
  • selected_papers.jsonl
  • selection_rationale.yaml
  • 可选 evidence_cards_{主题}.jsonl

硬约束

  • 强制导出 PDF 与 Word;只有明确失败并记录原因时才允许缺失。
  • 正文字数与参考文献数必须落在当前档位范围内;可由用户覆盖,默认值以 config.yaml 为准。
  • 正文固定包含:摘要、引言、至少 1 个子主题段、讨论、展望、结论。
  • \cite{key} 必须与 BibTeX key 一致;缺失即报错。
  • 正文禁止泄露 AI 工作流,例如“检索/去重/评分/选文/字数预算”等元叙事只能写入 {主题}_工作条件.md。
  • 摘要必须为单段,避免方法学流水账;表格宽度与样式约束见 references/review-tex-section-templates.md。
  • 不为凑引用而堆砌低分文献;无法确认时优先不改、不引。

主流程

0. 准备

  • 记录主题、档位、字数/参考范围与输出目录。
  • 开始前优先阅读:
  • references/ai_query_generation_prompt.md
  • references/ai_scoring_prompt.md
  • references/expert-review-writing.md
  • references/review-tex-section-templates.md
  • 涉及翻译时再读 references/multilingual-guide.md

1. 多查询检索

  • AI 为主题自主规划查询变体,通常 5-15 组。
  • 优先用 OpenAlex,必要时按 config.yaml.search.provider_priority 自动降级。
  • 检索结果写 Search Log;resume 时若 papers 路径失效,应清理后重检。

2. 去重

  • 用 dedupe_papers.py 生成去重结果与映射。
  • 所有后续流程只读取去重后的候选集。

3. AI 评分与数据抽取

  • AI 按 references/ai_scoring_prompt.md 逐篇阅读标题与摘要,输出 scored_papers.jsonl。
  • 每篇至少包含:score、subtopic、rationale、alignment、extraction。
  • 评分范围固定为 1-10 分;仅对 >=5 分文献分配子主题,避免弱相关论文污染子主题规划。
  • 自检分布是否健康:高分约 20-40%,中分 40-60%,低分 10-30%。

4. 选文与 Bib 生成

  • select_references.py 按目标参考范围和高分优先比例选出最终集合。
  • 生成 selected_papers.jsonl、references.bib、selection_rationale.yaml。
  • Bib 清洗必须保留:大小写无关去重 key、LaTeX 特殊字符转义、缺失字段警告。
  • 摘要缺失或过短的条目标记 do_not_cite,并在报告中提示摘要覆盖率风险。

5. 子主题与配额规划

  • AI 基于评分结果规划 3-7 个子主题,并给出段落配额。
  • 默认思路:引言约 1.5k、讨论/展望各约 1k、结论约 0.6k,其余分给子主题段。
  • 结果写入工作条件与数据抽取表,作为写作锚点。

6. 字数预算

  • 用 plan_word_budget.py 生成 3 份预算 CSV,再汇总为 word_budget_final.csv。
  • 引用段与无引用段预算均需覆盖;总字数误差必须控制在 config.yaml.word_budget.tolerance 内。

7. 写作

  • 正文章节固定为:摘要、引言、子主题段、讨论、展望、结论。
  • 写作前读取 word_budget_final.csv,按文献综/述预算组织证据。
  • 默认采用单篇引用优先;引用要紧跟所支撑的观点,避免段末堆砌。
  • 如需详细写作规范,直接遵循:
  • references/expert-review-writing.md
  • references/review-tex-section-templates.md

8. 有机扩写与验证

  • 若字数不足,只允许在最短或证据不足的子主题段内做增量扩写,不新增子主题,不改原主张和引用。
  • 依次运行:
  • validate_counts.py
  • validate_review_tex.py
  • 可选 validate_word_budget.py
  • generate_validation_report.py

9. 导出与多语言

  • 通过 compile_latex_with_bibtex.py 生成 PDF。
  • 通过 convert_latex_to_word.py 生成 Word。
  • 如用户要求多语言版本,使用 multi_language.py 翻译正文并智能编译;失败时保留错误报告与 broken 文件,并优先支持恢复备份。

工作目录与文件隔离

  • 所有中间文件必须写入 {work_dir}/.systematic-literature-review/。
  • 最终交付物放在工作目录根部。
  • AI 临时脚本必须放到 {work_dir}/.systematic-literature-review/scripts/。
  • 不要把临时文件写到工作目录根部,不要用绝对路径写 /tmp/*,也不要读写其他 run 目录。
  • 以环境变量 SYSTEMATIC_LITERATURE_REVIEW_SCOPE_ROOT 和 SYSTEMATIC_LITERATURE_REVIEW_SCRIPTS_DIR 为准。

关键命令

# 推荐主入口
python3 scripts/run_pipeline.py --topic "{主题}" --runs-root runs

# 旧入口 / resume
python3 scripts/pipeline_runner.py --topic "{主题}" --domain general --work-dir runs/{safe_topic}
python3 scripts/pipeline_runner.py --resume runs/{safe_topic}

# 阶段 3 评分后,从第 4 阶段继续
python3 scripts/pipeline_runner.py --resume runs/{safe_topic} --resume-from 4

环境与脚本

  • 运行环境:Python 3.9+、LaTeX(xelatex/bibtex)、pandoc。
  • 关键脚本:
  • 检索:multi_query_search.py、openalex_search.py
  • 去重:dedupe_papers.py
  • 选文:select_references.py、build_reference_bib_from_papers.py
  • 数据抽取:update_working_conditions_data_extraction.py
  • 字数预算:plan_word_budget.py、validate_word_budget.py
  • 校验:validate_counts.py、validate_review_tex.py、generate_validation_report.py
  • 导出:compile_latex_with_bibtex.py、convert_latex_to_word.py

可选:成本追踪

  • 初始化:python3 systematic-literature-review/scripts/pipeline_cost.py init
  • 抓取定价:python3 systematic-literature-review/scripts/pipeline_cost.py fetch-prices
  • 记录 token:pipeline_cost.py log ...
  • 汇总:pipeline_cost.py summary
  • 所有成本数据写到 .systematic-literature-review/cost/

参考材料

  • references/ai_query_generation_prompt.md
  • references/ai_scoring_prompt.md
  • references/expert-review-writing.md
  • references/review-tex-section-templates.md
  • references/multilingual-guide.md
  • references/development-validation-guide.md

Score

0–100
65/ 100

Grade

C

Popularity17/30

836 installs — growing adoption. Source repo has 2,318 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

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Systematic Literature Review FAQ

How do I install the Systematic Literature Review skill?

Run “npx skills add https://github.com/huangwb8/chineseresearchlatex --skill systematic-literature-review” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Systematic Literature Review skill do?

当用户明确要求"做系统综述/文献综述/related work/相关工作/文献调研"时使用。AI 自定检索词,多源检索→去重→AI 逐篇阅读并评分(1–10分语义相关性与子主题分组)→按高分优先比例选文→自动生成"综/述"字数预算→资深领域专家自由写作(固定摘要/引言/子主题/讨论/展望/结论),保留正文字数与参考文献数硬校验,强制导出 PDF 与 Word。支持多语言翻译与智能编译(en/zh/ja/de/fr/es)。 The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Systematic Literature Review skill free?

Yes. Systematic Literature Review is a free, open-source skill published from huangwb8/chineseresearchlatex. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Systematic Literature Review work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Systematic Literature Review works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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