Agent skill

Journal Selector for Manuscripts

by huangwb8 in huangwb8/ChineseResearchLaTeX

Recommends journals for a manuscript by filtering a bundled impact-factor catalog, verifying scope and quality online, and writing a ranked Markdown report.

MITAuto-check passedResearch & Science

SKILL.md written in Chinese; this summary is our English description.

Install Journal Selector for Manuscripts

skills CLI
$ npx skills add huangwb8/ChineseResearchLaTeX --skill paper-select-journal -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install huangwb8/ChineseResearchLaTeX paper-select-journal --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/huangwb8/ChineseResearchLaTeX.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/paper-select-journal .claude/skills/paper-select-journal && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
paper-select-journal
GitHub stars
2.9k
Token cost
~1.7k tokens
SKILL.md length
349 words
Files
17 (incl. scripts, references, assets)
Skills in repo
27
Repo updated
First seen
Licence
MIT

At a glance

Recommends journals for a manuscript by filtering a bundled impact-factor catalog, verifying scope and quality online, and writing a ranked Markdown report.

  • Choosing which journals to submit a finished manuscript to
  • SKILL.md covers 流程 and 约束
  • Runs Python scripts from its folder; calls python3
  • Getting a ranked shortlist of SCI journals with scope and quality checks

What it does

You supply a manuscript (pasted text or .md, .txt, .tex, .pdf or .docx files) and optional preferences. The agent writes a manuscript profile, then runs scripts/shortlist_journals.py against the bundled 2023IF.xlsx catalog for a minimal hard filter (impact-factor floor, excluded journals, basic metadata) that produces a Set1 candidate pool. The model, not a fixed scoring formula, then plans which candidates deserve checking.

Those candidates are verified online for official site, aims and scope, Chinese Academy of Sciences division, reputation and predatory-journal warning signs, forming Set2, and papers from the last 3 months on PubMed are fetched with scripts/fetch_pubmed_recent.py as evidence. The final report keeps only well-supported journals, at most 10, ranked by recommendation, and prefers fewer over padding. Journals with warnings or a low impact factor are excluded unless the report explains why a field expert would still trust them. It is not meant for polishing a paper, translating an abstract or looking up a single journal.

When your agent uses it

  • Choosing which journals to submit a finished manuscript to
  • Getting a ranked shortlist of SCI journals with scope and quality checks
  • Turning a paper abstract or LaTeX source into submission suggestions
  • Screening out predatory or low-impact journals for a paper

Example prompts

  • “Recommend journals for my manuscript in ./paper/main.tex; I want something with fast review.”
  • “Which SCI journals suit this abstract? I prefer open access.”
  • “Pick journals for the attached Word manuscript and exclude any I submitted to last year.”

Requirements

  • Python 3 to run the bundled scripts
  • Network access to journal sites and PubMed

What it can do on your machine

Read from SKILL.md and the folder at commit b8b4142. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 5 files in scripts/ (Python, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Journal Selector for Manuscripts loads about 1.7k tokens when it runs, and up to ~2.3k if it reads all its reference files. Until then it costs about 86 tokens; SKILL.md has 349 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~86
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from huangwb8/ChineseResearchLaTeX at commit b8b4142, republished under its MIT licence (© huangwb8). 349 words, ~1,652 tokens.

Download SKILL.mdSave it as .claude/skills/paper-select-journal/SKILL.md (or your agent's skills folder). This skill also uses 16 other files; get the full folder from GitHub.
name
paper-select-journal
description
当用户明确要求“推荐投稿期刊”“帮我的论文选 SCI 杂志”“这篇 manuscript 适合投哪些 journal”“期刊匹配/选刊/投稿建议”时必须使用。适用于用户提供全文、摘要、Markdown、LaTeX、PDF、Word 或混合材料的场景;本 skill 会基于 manuscript 与用户偏好,先用内置 `2023IF.xlsx` 做最小硬过滤生成候选池,再由宿主模型自主规划 Set1/Set2/Set3,并联网核验 scope / 质量 / 近 3 个月 PubMed 论文,最后输出 1 份按推荐度排序的 Markdown 选刊报告。⚠️ 不适用:用户只是想润色论文、只想翻译摘要、或只问某个单一期刊的官网信息而不需要系统选刊。
metadata.author
Bensz Conan

Paper Select Journal

核心原则
  • 当前信息必须实时核验:scope、官网、业内认可度、中科院分区、近 3 个月论文都属于时效性信息,不能靠旧记忆。
  • 中间文件只允许落在当前工作目录下的 .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/paper-select-journal/ 隐藏目录;用户若明确指定其他目录,才可覆盖默认值。
  • Set1 不再依赖固定语义权重。脚本只负责最小硬过滤与候选池整理,真正的语义规划由当前宿主模型完成。
  • Set1 不是最终答案。最终报告只保留证据充分的 Set3,最多 10 个期刊。
  • 不能推荐明显预警、垃圾期刊或影响因子低于 3 的期刊;若确实保留低于 3 的例外,必须写明“为何它仍是领域内人类专家认可的稳妥选择”。
  • 宁可少报,也不要为了凑满 10 个而硬凑。
输入与工作区
  • 用户需求可选,manuscript 必选。
  • manuscript 可来自粘贴的标题 / 摘要 / 全文片段,或本地 .md、.txt、.tex、.pdf、.docx,也可混合提供。
  • 一旦进入隐藏工作区流程,后续供脚本读取的 analysis/*.json 必须保留在当前 run 目录内;不要把 manuscript_profile.json、set2_scope_review.json、final_recommendations.json 指到 run 目录外。

先初始化隐藏工作区:

bash
python3 <skill_root>/scripts/init_workspace.py --project-root .

脚本会创建 .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/paper-select-journal/{yyyy-mm-dd-hh-mm}/,其中至少包含:

  • inputs/
  • analysis/
  • candidates/
  • pubmed/
  • reports/

后续所有中间文件都必须留在该 run 目录内。

流程

输入

按用户请求和配置文件提供必要输入;缺失信息应明确列出并停止依赖该输入的步骤。

执行步骤
先写 manuscript 画像

完整理解论文后,把结果写入 analysis/manuscript_profile.json。

  • 模板:templates/manuscript_profile.template.json
  • 写法:references/manuscript-profile.md 最低字段:
  • title
  • abstract
  • keywords
  • manuscript_summary

画像的作用是帮助 AI 理解稿件,而不是喂给固定打分公式。 如果用户偏好复杂,优先把偏好写成自然语言放进 target_journal_brief 或 notes,不要为了脚本凑很多硬编码线索。 如果确实需要保留低 IF 的人工例外期刊,只能作为后续人工补录候选,并且必须在最终报告里解释“为什么它虽然低于阈值,仍是领域内稳妥选择”。

用内置 2023IF.xlsx 做 Set1 候选池

内置目录:assets/journal_catalog/2023IF.xlsx

运行:

bash
python3 <skill_root>/scripts/shortlist_journals.py \
  --workspace .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/paper-select-journal/{yyyy-mm-dd-hh-mm} \
  --profile .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/paper-select-journal/{yyyy-mm-dd-hh-mm}/analysis/manuscript_profile.json

产物:

  • candidates/set1_candidates.json
  • candidates/set1_candidates.md

这里的脚本只做最小硬过滤:

  • 影响因子下限
  • 用户明确排除的期刊
  • 基础元数据整理(JIF、分区、OA 比例、引用量)

不要把这一步输出误解为“已经按语义排好序的最终 shortlist”。 你必须读取该候选池,再结合 manuscript 自主规划真正值得进入 Set2 的期刊。

联网核验 scope、官网、分区与质量,得到 Set2

根据 candidates/set1_candidates.json 与 manuscript 画像,自主决定先核验哪些候选,并逐个联网核验:

  • 官方网站
  • Aims & Scope
  • 中科院小类及其分区
  • 业内认可度
  • 是否存在预警 / 垃圾期刊信号

优先使用:

  • 期刊官网
  • PubMed / NLM
  • 主流出版社页面
  • 可信的分区信息来源

把通过核验的期刊写入:

  • analysis/set2_scope_review.json

模板:templates/scope_review.template.json 核验口径:references/journal-quality-checklist.md

4a. 抓取 Set2 最近 3 个月 PubMed 原始论文证据

运行:

bash
python3 <skill_root>/scripts/fetch_pubmed_recent.py \
  --workspace .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/paper-select-journal/{yyyy-mm-dd-hh-mm} \
  --profile .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/paper-select-journal/{yyyy-mm-dd-hh-mm}/analysis/manuscript_profile.json \
  --scope-review .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/paper-select-journal/{yyyy-mm-dd-hh-mm}/analysis/set2_scope_review.json

产物:

  • pubmed/recent_articles.json
  • pubmed/recent_articles.md

这里只提供原始证据,不负责打分或排序。脚本只做 API 调用、XML 解析和按日期整理。

4b. AI 评定主题相似性,决定哪些期刊进入 Set3

你必须同时阅读:

  • analysis/manuscript_profile.json
  • pubmed/recent_articles.json

这里的“AI”指当前执行本 skill 的宿主模型本身:

  • Claude Code 中由当前 Claude 会话完成
  • Codex 中由当前 Codex 会话完成
  • 不要为 Step 4b 额外调用外部 AI API、独立模型服务或单独打分脚本

也就是说,Step 4b 的规划、语义判断、Set3 去留决策和 set3_similarity_review.json 写入,都必须用当前工作环境已提供的 AI 算力原生完成。

逐个判断 Set2 期刊最近 3 个月论文与稿件在以下维度上的语义相关性:

  • 主题是否真的对口,而不只是 token 碰撞
  • 研究问题是否接近
  • 方法学是否接近
  • 相关论文数量与密度是否足以支持进入最终推荐

执行时先快速浏览全部 Set2 近期论文形成比较框架,再逐刊做语义判断,最后统一决定 Set3 去留并写出可复核理由。 不要再把这一步退化成机械 token 打分或硬编码加权公式。

把结论写入:

  • analysis/set3_similarity_review.json

模板:templates/set3_similarity_review.template.json

每个期刊至少要写:

  • journal_name
  • include_in_set3
  • similarity_assessment
  • relevant_articles
  • irrelevant_articles_count
  • overall_relevance_level

overall_relevance_level 只允许:

  • high
  • medium
  • low
  • none
Show full SKILL.md (144 more words)Show less
形成最终推荐 JSON

基于 analysis/set3_similarity_review.json,把最终最多 10 个期刊写入 analysis/final_recommendations.json。

  • 模板:templates/final_recommendations.template.json
  • 字段说明:references/report-schema.md

必须保留:

  • 影响因子
  • 中科院小类及其分区
  • 业内认可度
  • 官方网站
  • 为什么推荐
  • 最近 3 个月类似主题论文
  • 每篇证据论文的 AI relevance
渲染最终 Markdown 报告

运行:

bash
python3 <skill_root>/scripts/render_report.py \
  --workspace .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/paper-select-journal/{yyyy-mm-dd-hh-mm} \
  --final-json .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/paper-select-journal/{yyyy-mm-dd-hh-mm}/analysis/final_recommendations.json

最终输出:

  • reports/paper-select-journal-report.md

如需 --output 覆盖默认文件名,也只能写到当前 run 目录内部,不能把最终 Markdown 报告写到隐藏工作区之外。

  • 所有期刊写在同一个 Markdown 文件里

  • 每个期刊使用 # 层级,下面按需用 ##、###

  • 每个期刊都要写明:影响因子、中科院小类及分区、业内认可度、官方网站、推荐理由,以及最近 3 个月类似主题论文表格和 AI 相关性说明

  • scope 不匹配,再高 IF 也不要强推

  • 有明显预警 / 垃圾期刊风险,直接淘汰

  • 近 3 个月没有相似主题论文,不一定淘汰,但推荐度要下调

  • include_in_set3 为 false 的期刊,不要进入最终推荐

  • 中科院分区无法可靠核验时,优先换成信息更透明的候选

  • 用户未明确偏好时,自主选择最稳妥方案,不要把提问变成阻塞

  • <skill_root> 表示当前 skill 的真实安装目录。

  • 不要假设用户当前工作目录里一定有 paper-select-journal/ 源码副本。

  • 如果你已经处在 skill 根目录,也可以直接运行 python3 scripts/...。

  • references/manuscript-profile.md

  • references/journal-quality-checklist.md

  • references/report-schema.md

输出

输出 Skill description 所承诺的交付物,并明确格式、路径和失败返回形式。

输出管理

本 Skill 的新任务中间文件统一写入 ./.bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/{skill名}/input|output|log/。同一任务复用一个任务根目录;多 Skill 协作才创建 shared/。正式交付物不写入该目录,历史隐藏目录只允许显式兼容读取、迁移或清理。

校验

完成后执行 Skill 已有的静态检查、脚本验证或人工复核,并记录通过标准。

失败与恢复

保留错误证据和已完成产物;仅在输入、环境或外部依赖恢复后从最近的失败步骤重试。

约束

遵守以下公共约束,并执行本 Skill 的专属边界。

公共硬约束
  • 任务需要落盘时,使用唯一的 ./.bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/ 根目录;共享材料放入 shared/,Skill 专属材料放入该 Skill 的 input/、output/、log/。
  • 正式交付物、源代码和正式计划按项目约定保存,不写入任务工作区;未经授权不覆盖、删除、迁移或远程写入。
  • 项目维护变更检查 BAC 可用性并记录需求、AI 产出、工具结果、文件改动和验证摘要;BAC 只做过程审计,不替代署名、责任或合规判断。
  • 不记录 API Key、访问令牌、密码、Cookie、环境/凭据文件、私有 Prompt、身份信息、本地用户名、主机名或不必要的大体积原始数据。
  • 文件路径必须规范化并限制在授权项目范围内;外部 URL、子进程和网络访问遵循最小权限,防止路径遍历、SSRF 和命令注入。
  • Skill 版本唯一记录在自身 config.yaml:skill_info.version;公开 API、协议、目录或配置变更同步文档与 CHANGELOG.md。
  • 仅将 Skill 或 Bensz 基础设施本身的设计缺陷交给 bensz-collect-bugs;先脱敏写入 ~/.bensz-skills/bugs/,当前任务不中断,只有用户明确要求才公开上报,禁止直接修改用户已安装的 Skill 源码。
<!-- End of canonical common constraints. -->
Skill 专属约束

不得超出本 Skill description 和上方流程所声明的范围;不将未验证的信息伪装成确定结论。

© huangwb8, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 16 other files (scripts, references, assets) in skills/paper-select-journal of huangwb8/ChineseResearchLaTeX.

  • SKILL.md
  • CHANGELOG.md
  • README.md
  • assets/journal_catalog/2023IF.xlsx
  • config.yaml
  • references/journal-quality-checklist.md
  • references/manuscript-profile.md
  • references/report-schema.md
  • scripts/common.py
  • scripts/fetch_pubmed_recent.py
  • scripts/init_workspace.py
  • scripts/render_report.py
  • scripts/shortlist_journals.py
  • templates/final_recommendations.template.json
  • templates/manuscript_profile.template.json
  • templates/scope_review.template.json
  • … and 1 more

Open the folder on GitHubat commit b8b4142

Compare with similar skills

Journal Selector for Manuscripts next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Paper OrchestraAr9av/PaperOrchestra6791 repos~3.5kAutomated safety check: PassCustom licence

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    Recommends five pairs of NSFC application codes, primary and secondary, from a grant proposal's text and writes the reasons to a Markdown report.

    2.9k GitHub starsUsed in 1 repo~1.1k tokens
    Auto-check passed
  • NSFC Proposal Length Aligner

    huangwb8/ChineseResearchLaTeX

    Checks a Chinese NSFC grant proposal against section length budgets, reports where it runs short or long, and guides meaning-preserving expansion or trimming.

    2.9k GitHub starsUsed in 1 repo~1.3k tokens
    Auto-check passed

Questions about Journal Selector for Manuscripts

What does Journal Selector for Manuscripts do?

Recommends journals for a manuscript by filtering a bundled impact-factor catalog, verifying scope and quality online, and writing a ranked Markdown report. docx files) and optional preferences.xlsx catalog for a minimal hard filter (impact-factor floor, excluded journals, basic metadata) that produces a Set1 candidate pool.

When should I use Journal Selector for Manuscripts?

Journal Selector for Manuscripts fits situations like: choosing which journals to submit a finished manuscript to; getting a ranked shortlist of SCI journals with scope and quality checks; turning a paper abstract or LaTeX source into submission suggestions; screening out predatory or low-impact journals for a paper.

How do I install Journal Selector for Manuscripts in Claude Code?

Run `npx skills add huangwb8/ChineseResearchLaTeX --skill paper-select-journal -a claude-code`. Or copy the skill folder (skills/paper-select-journal in huangwb8/ChineseResearchLaTeX) into .claude/skills/paper-select-journal in your project. Claude Code loads it when a task matches its description.

How do I install Journal Selector for Manuscripts in Codex?

Run `npx skills add huangwb8/ChineseResearchLaTeX --skill paper-select-journal -a codex`. Or copy the skill folder (skills/paper-select-journal in huangwb8/ChineseResearchLaTeX) into .agents/skills/paper-select-journal in your project. Codex loads it when a task matches its description.

Can I use Journal Selector for Manuscripts in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add huangwb8/ChineseResearchLaTeX --skill paper-select-journal -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/paper-select-journal, .gemini/skills/paper-select-journal, .github/skills/paper-select-journal and .opencode/skills/paper-select-journal in your project.

What does Journal Selector for Manuscripts need to run?

Going by SKILL.md and its folder, Journal Selector for Manuscripts needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3 to run the bundled scripts; Network access to journal sites and PubMed.

Does Journal Selector for Manuscripts access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Journal Selector for Manuscripts safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Journal Selector for Manuscripts use?

Journal Selector for Manuscripts is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Journal Selector for Manuscripts use?

About 1.7k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 599 tokens, read only when the agent opens those files.

What are the alternatives to Journal Selector for Manuscripts?

Skills that share tags, products or a category with Journal Selector for Manuscripts: Citation Management (foryourhealth111-pixel/Vibe-Skills, 3.6k stars), Citation Management (K-Dense-AI/claude-scientific-writer, 2.4k stars), Citation Management (neflibata-feng/MyArxiv-Agent, 126 stars) and Nature Academic Search (wp-a/nature-academic-search, 304 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Journal Selector for Manuscripts?

huangwb8 (a GitHub user) maintains it in huangwb8/ChineseResearchLaTeX, which has 2,880 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on October 4, 2026.

Source: huangwb8/ChineseResearchLaTeX on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.