最少需要：
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionsystematic-literature-reviewExecute the skills CLI command in your project's root directory to begin installation:
Fetches systematic-literature-review from huangwb8/chineseresearchlatex and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate systematic-literature-review. Access via /systematic-literature-review in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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。gh 与 bensz-collect-bugs，仅上传新增 bug 到 huangwb8/bensz-bugs；不要 pull / clone 整个 bug 仓库。最少需要：
{主题}：一句话主题。Premium / Standard / Basic；未指定时读取 config.yaml 默认值。config.yaml.scoring.default_*_range。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*.jsonlscored_papers.jsonlselected_papers.jsonlselection_rationale.yamlevidence_cards_{主题}.jsonlconfig.yaml 为准。\cite{key} 必须与 BibTeX key 一致；缺失即报错。{主题}_工作条件.md。references/review-tex-section-templates.md。references/ai_query_generation_prompt.mdreferences/ai_scoring_prompt.mdreferences/expert-review-writing.mdreferences/review-tex-section-templates.mdreferences/multilingual-guide.mdconfig.yaml.search.provider_priority 自动降级。papers 路径失效，应清理后重检。dedupe_papers.py 生成去重结果与映射。references/ai_scoring_prompt.md 逐篇阅读标题与摘要，输出 scored_papers.jsonl。score、subtopic、rationale、alignment、extraction。>=5 分文献分配子主题，避免弱相关论文污染子主题规划。select_references.py 按目标参考范围和高分优先比例选出最终集合。selected_papers.jsonl、references.bib、selection_rationale.yaml。do_not_cite，并在报告中提示摘要覆盖率风险。plan_word_budget.py 生成 3 份预算 CSV，再汇总为 word_budget_final.csv。config.yaml.word_budget.tolerance 内。word_budget_final.csv，按文献综/述预算组织证据。references/expert-review-writing.mdreferences/review-tex-section-templates.mdvalidate_counts.pyvalidate_review_tex.pyvalidate_word_budget.pygenerate_validation_report.pycompile_latex_with_bibtex.py 生成 PDF。convert_latex_to_word.py 生成 Word。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。{work_dir}/.systematic-literature-review/。{work_dir}/.systematic-literature-review/scripts/。/tmp/*，也不要读写其他 run 目录。SYSTEMATIC_LITERATURE_REVIEW_SCOPE_ROOT 和 SYSTEMATIC_LITERATURE_REVIEW_SCRIPTS_DIR 为准。# 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
xelatex/bibtex）、pandoc。multi_query_search.py、openalex_search.pydedupe_papers.pyselect_references.py、build_reference_bib_from_papers.pyupdate_working_conditions_data_extraction.pyplan_word_budget.py、validate_word_budget.pyvalidate_counts.py、validate_review_tex.py、generate_validation_report.pycompile_latex_with_bibtex.py、convert_latex_to_word.pypython3 systematic-literature-review/scripts/pipeline_cost.py initpython3 systematic-literature-review/scripts/pipeline_cost.py fetch-pricespipeline_cost.py log ...pipeline_cost.py summary.systematic-literature-review/cost/references/ai_query_generation_prompt.mdreferences/ai_scoring_prompt.mdreferences/expert-review-writing.mdreferences/review-tex-section-templates.mdreferences/multilingual-guide.mdreferences/development-validation-guide.mdMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
jezweb/claude-skills
Useful defaults in systematic-literature-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added systematic-literature-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
systematic-literature-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
systematic-literature-review reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for systematic-literature-review matched our evaluation — installs cleanly and behaves as described in the markdown.
systematic-literature-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
systematic-literature-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for systematic-literature-review matched our evaluation — installs cleanly and behaves as described in the markdown.
systematic-literature-review reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: systematic-literature-review is focused, and the summary matches what you get after install.
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