research-literature-review

research-literature-review is a skill for Claude Code, Codex from huangwb8/ChineseResearchLaTeX. It costs 127 tokens per session (4,184 once invoked), scanned A, original, MIT.

A workflow for producing a systematic literature review, which is a structured summary of research found through a defined search and selection process.

In plain words
What is it for?
Use it to search multiple sources, group and score papers, write a review with sections and references, and export checked LaTeX, PDF, and Word files.
Why use it?
It organizes searching, duplicate removal, relevance scoring, paper selection, writing, and length checks into one process, reducing manual coordination.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code; mentions Codex.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 scripts/run_pipeline.py --topic "{主题}" --query-file ./queries.json --publish-dir ./review-deliverables.

Good fit Use it to search multiple sources, group and score papers, write a review with sections and references, and export checked LaTeX, PDF, and Word files.

Compare 6 skills from other repositories ↓
About the project

ChineseResearchLaTeX is a collection of LaTeX templates and an AI-assisted workflow for preparing Chinese research documents such as grant proposals, papers, theses, and academic CVs. Researchers use it to plan, format, review, compile, and revise these documents with human oversight. The catalogue skills and instructions support its agent-based research-writing workflow.

huangwb8/ChineseResearchLaTeX · 2,726 stars · on GitHub

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/huangwb8/ChineseResearchLaTeX
agentmods
npx agentmods add skills/huangwb8/chineseresearchlatex/research-literature-review

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for research-literature-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/huangwb8/chineseresearchlatex/research-literature-review/github.svg)](https://agentmods.dev/skills/huangwb8/chineseresearchlatex/research-literature-review)
Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/huangwb8/chineseresearchlatex/research-literature-review"><img src="https://agentmods.dev/badge/skills/huangwb8/chineseresearchlatex/research-literature-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 127 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,184 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00127 $0.04184
Opus 5 $0.00063 $0.02092
Sonnet 5 $0.00025 $0.00837
Haiku 4.5 $0.00013 $0.00418

Measured 4d ago against content hash f2223b8e8278, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

research-literature-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

The scan reads SKILL.md. This mod also ships 32 executable files (qa/test_resume_state.py, qa/test_workspace_layout.py, scripts/api_cache.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/research-literature-review/SKILL.md · 230 lines

How it starts

The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Literature Review

定位与检索依赖

  • 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。
  • research-literature-search 是阶段 1/2 的必需依赖(contract rls.v1)。review 只消费其 manifest、canonical candidates 和 provenance,不再内嵌 provider 或执行第二套 canonical 去重。
  • 旧名 systematic-literature-review 仅作为 prompt 兼容别名保留;.systematic-literature-review/ 仍是稳定历史工作区名。

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。
  6. 查询输入:阶段 1 前必须提供符合公开 schema 的多查询 JSON;推荐用 --query-file,也可填写当前 run 的 input/queries.json

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

  • 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 ghbensz-collect-bugs,仅上传新增 bug 到 huangwb8/bensz-bugs;不要 pull / clone 整个 bug 仓库。

准备

  • 记录主题、档位、字数/参考范围与输出目录。
  • 先读取 references/ai_query_generation_prompt.md,生成查询 JSON。公开 schema 支持以下三种形态:
    • {"queries": [{"query": "...", "rationale": "..."}]}
    • [{"query": "...", "rationale": "..."}]
    • ["query 1", "query 2"]
  • 剔除空查询后,有效数量必须满足 config.yaml:query_input.min_queries/max_queries(默认 5–25)。
  • 已知工作目录时,直接将文件保存到 <work-dir>/input/queries.json,或用 --query-file <path> 让 runner 将显式输入复制到该位置。工作目录尚未建立时,先运行 --prepare-only,填充打印出的 input/queries.json,再以 --resume ... --resume-from 1 继续。
  • 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

多查询检索(调用 research-literature-search)

Read the full file on GitHub · 230 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago Changed · -18 lines f2223b8e8278
  2. 7d ago Changed · +13 lines 164dffac11b6
  3. 10d ago Changed · +18 lines · -40 tokens per session 100d0c6b05e8
  4. 13d ago First seen · 217 lines · 167 tokens per session scan A decdf862ecad

Subscribe to this mod's changes

research-literature-review is a skill published in the GitHub repository huangwb8/ChineseResearchLaTeX (2,726 stars, last pushed yesterday), licensed MIT. It adds 127 tokens to every session and 4,184 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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