Agent skill

Research Literature Review

by haibarazz in haibarazz/awesome-codex-research

面向信息系统计算设计科学(CDS)研究,根据用户的数据、研究情境与研究问题,分别识别问题/理论视角和技术/算法两条文献对话线,检索并核验全文,制作可追溯的文献对话地图,最终澄清研究的最近邻、理论祖先、方法缺口与可辩护定位。适用于选题定位、相关工作规划、方法定位和后续综述;核心不是代写文献综述。

No licenceAuto-check passedResearch & Science

Install Research Literature Review

skills CLI
$ npx skills add haibarazz/awesome-codex-research --skill research-literature-review -a claude-code

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

GitHub CLI
$ gh skill install haibarazz/awesome-codex-research research-literature-review --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/haibarazz/awesome-codex-research.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research-literature-review .claude/skills/research-literature-review && 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
research-literature-review
GitHub stars
100
Token cost
~558 tokens
SKILL.md length
64 words
Files
13 (incl. references)
Skills in repo
9
Repo updated
First seen
Licence
None found

At a glance

面向信息系统计算设计科学(CDS)研究,根据用户的数据、研究情境与研究问题,分别识别问题/理论视角和技术/算法两条文献对话线,检索并核验全文,制作可追溯的文献对话地图,最终澄清研究的最近邻、理论祖先、方法缺口与可辩护定位。适用于选题定位、相关工作规划、方法定位和后续综述;核心不是代写文献综述。

  • Works in 7 steps: 建立研究锚点。… → 生成问题/视角线。 读取… → 生成技术/算法线。 读取… → …
  • Tasks that involve Literature review
  • SKILL.md covers 默认工作流, 推荐工作目录 and 产出门槛
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Research Literature Review is an agent skill from haibarazz/awesome-codex-research. 面向信息系统计算设计科学(CDS)研究,根据用户的数据、研究情境与研究问题,分别识别问题/理论视角和技术/算法两条文献对话线,检索并核验全文,制作可追溯的文献对话地图,最终澄清研究的最近邻、理论祖先、方法缺口与可辩护定位。适用于选题定位、相关工作规划、方法定位和后续综述;核心不是代写文献综述。

Its SKILL.md is about 560 tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including reference files (for example `agents/openai.yaml`, `examples/dialogue-maps/P01.md` and `examples/dialogue-maps/P04.md`).

It sits in Research & Science, covering Literature review.

When your agent uses it

  • Tasks that involve Literature review

Example prompts

  • “/research-literature-review”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. 建立研究锚点。 写清数据对象、分析单位、场景、行动者、时间结构、标签/结果、拟回答的研究问题,以及当前最不确定的贡献主张。研究问题用现象或决策困难表述,不先写成“提出某模型”。
  2. 生成问题/视角线。 读取 problem-perspective-prompt.md,先从用户研究提出候选现象、领域与理论文献流,再生成查询式。初筛后通常保留 1–2 条核心流。
  3. 生成技术/算法线。 读取 technical-method-prompt.md,从数据结构、计算任务和设计挑战推出候选技术流与查询式;通常保留 2–4 条,不能按模型名堆砌。
  4. 检索并按对话角色筛选。 同时寻找最近邻、理论/技术祖先、桥接论文和关键对照。摘要只用于初筛;记录查询、来源、日期、纳入理由与尚未覆盖的相邻词。
  5. 取得并核验全文。 读取 paper-positioning-card.md。优先复用本地文件;缺失时使用合法的开放来源或用户已有访问权限。核对标题、作者、版本、页数和正文身份后再阅读。
  6. 逐篇制作对话地图。 重点阅读 Introduction、Literature Review/Related Work、理论与方法概览,复原每篇论文怎样组织问题线和技术线;重要判断附原文位置,并区分作者明示与阅读者归纳。
  7. 综合研究定位。 读取 research-positioning.md,说明用户工作继承什么、连接什么、与最近邻有何具体差异、哪些空间尚未被覆盖,以及下一轮需要补检索或补证什么。只有用户明确需要时,才把定位材料改写成文献综述。

What it can do on your machine

Read from SKILL.md and the folder at commit e3ca125. 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

    No scripts in the folder and no shell commands in SKILL.md.

    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

Research Literature Review loads about 558 tokens when it runs, and up to ~2.9k if it reads all its reference files. Until then it costs about 44 tokens; SKILL.md has 64 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~558
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.9k

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); files beside SKILL.md are not scanned.

SKILL.md

Without a licence we can't republish the file, so here is its outline and opening line. It has 64 words (~558 tokens).

name
research-literature-review

Read the full SKILL.md on GitHub

Files

SKILL.md and 12 other files (references) in skills/research-literature-review of haibarazz/awesome-codex-research.

  • SKILL.md
  • agents/openai.yaml
  • examples/dialogue-maps/P01.md
  • examples/dialogue-maps/P04.md
  • examples/dialogue-maps/P05.md
  • examples/dialogue-maps/P06.md
  • examples/dialogue-maps/P08.md
  • examples/dialogue-maps/P15.md
  • examples/index.md
  • references/paper-positioning-card.md
  • references/problem-perspective-prompt.md
  • references/research-positioning.md
  • references/technical-method-prompt.md

Open the folder on GitHubat commit e3ca125

Compare with similar skills

Research Literature Review 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.

Research Literature Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research Literature Review this skillhaibarazz/awesome-codex-research100—~558Automated safety check: PassNone
Nature Paper CardYuan1z0825/nature-skills47k2 repos~2.1kAutomated safety check: PassApache-2.0
Systematic Review ScreenerImbad0202/academic-research-skills51k—~8.4kAutomated safety check: PassCustom licence
Literature Reviewneflibata-feng/MyArxiv-Agent12620 repos~5.9kAutomated safety check: NotesMIT
Preprint Search on bioRxivLigphiDonk/Oh-my--paper73912 repos~3.7kAutomated safety check: PassMIT
Academic Paper Writing PipelineImbad0202/academic-research-skills51k—~16kAutomated safety check: PassCustom licence

Similar skills

  • Nature Paper Card

    Yuan1z0825/nature-skills

    Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.

    47k GitHub starsUsed in 2 repos~2.1k tokens
    Research & ScienceAuto-check passed
  • Systematic Review Screener

    Imbad0202/academic-research-skills

    Screens records for systematic, scoping and rapid reviews against fixed eligibility rules, using two blinded AI reviewers and a third adjudicator, with traceable PRISMA counts.

    51k GitHub stars~8.4k tokensUpdated yesterday
    Research & ScienceAuto-check passed
  • Literature Review

    neflibata-feng/MyArxiv-Agent

    Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.).

    126 GitHub starsUsed in 20 repos~5.9k tokens
    Research & ScienceAuto-check: notes
  • Preprint Search on bioRxiv

    LigphiDonk/Oh-my--paper

    Searches bioRxiv life sciences preprints by keyword, author, date range or category with a Python script, returning JSON metadata and optional PDF downloads.

    739 GitHub starsUsed in 12 repos~3.7k tokens
    Research & ScienceAuto-check passed
  • Academic Paper Writing Pipeline

    Imbad0202/academic-research-skills

    Runs a 12-agent pipeline that plans, drafts, cites, reviews and formats academic papers, with modes for revision, rebuttals, abstracts and citation checks.

    51k GitHub stars~16k tokensUpdated yesterday
    Research & ScienceAuto-check passed
  • Deep Research Workflow

    TokenRhythm/opensquilla

    Runs multi-round research in three stages with a persisted state file, evidence tracking and a long-form report with per-claim citations.

    7.1k GitHub stars~1.3k tokensUpdated yesterday
    Research & ScienceAuto-check passed

More from haibarazz/awesome-codex-research

All 9 skills in this repo
  • Autoresearch

    haibarazz/awesome-codex-research

    Run rigorous end-to-end autonomous ML and AI research after a user provides a dataset, target, and research budget.

    93 GitHub stars~2.2k tokensUpdated 18 days ago
    Auto-check passed
  • Cds Method Innovation

    haibarazz/awesome-codex-research

    Guide a complete baseline-first ML or computational data-science method-innovation project, from workspace and direction discovery through finding and running common and recent baselines, diagnosing…

    93 GitHub stars~715 tokensUpdated 18 days ago
    Auto-check passed
  • Autodl Remote

    haibarazz/awesome-codex-research

    A skill your agent uses when the host coding agent should control an AutoDL or SSH server from the local machine, run remote commands, and explicitly upload or download selected files.

    93 GitHub stars~2.7k tokensUpdated 18 days ago
    Auto-check passed
  • Autodl Remote Tmux

    haibarazz/awesome-codex-research

    A skill your agent uses when AutoDL Remote should run or monitor long remote jobs through tmux panes.

    93 GitHub stars~666 tokensUpdated 18 days ago
    Auto-check passed
  • Auto Exp

    haibarazz/awesome-codex-research

    Plan, execute, monitor, verify, compare, and document reproducible machine-learning experiments.

    93 GitHub stars~1.4k tokensUpdated 18 days ago
    Auto-check passed
  • Review Comment Decomposer

    haibarazz/awesome-codex-research

    结合论文原文拆解审稿意见为最小可回应原子问题,规划补实验与回复构思两条工作线,归组共同关切,并输出带忠实中文翻译注释、每条 comment 一份建议逻辑和原子点英文小标题的可编译 LaTeX 回复骨架。用于返修规划、review decomposition、atomic concerns、rebuttal strategy 和回复信模板生成;完整回复正文留待作者后续撰写。

    100 GitHub stars~1.1k tokensUpdated 18 days ago
    Auto-check: warnings

Questions about Research Literature Review

What does Research Literature Review do?

面向信息系统计算设计科学(CDS)研究,根据用户的数据、研究情境与研究问题,分别识别问题/理论视角和技术/算法两条文献对话线,检索并核验全文,制作可追溯的文献对话地图,最终澄清研究的最近邻、理论祖先、方法缺口与可辩护定位。适用于选题定位、相关工作规划、方法定位和后续综述;核心不是代写文献综述。. Research Literature Review is an agent skill from haibarazz/awesome-codex-research.

When should I use Research Literature Review?

Research Literature Review fits situations like: tasks that involve Literature review.

How do I install Research Literature Review in Claude Code?

Run `npx skills add haibarazz/awesome-codex-research --skill research-literature-review -a claude-code`. Or copy the skill folder (skills/research-literature-review in haibarazz/awesome-codex-research) into .claude/skills/research-literature-review in your project. Claude Code loads it when a task matches its description.

How do I install Research Literature Review in Codex?

Run `npx skills add haibarazz/awesome-codex-research --skill research-literature-review -a codex`. Or copy the skill folder (skills/research-literature-review in haibarazz/awesome-codex-research) into .agents/skills/research-literature-review in your project. Codex loads it when a task matches its description.

Can I use Research Literature Review 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 haibarazz/awesome-codex-research --skill research-literature-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-literature-review, .gemini/skills/research-literature-review, .github/skills/research-literature-review and .opencode/skills/research-literature-review in your project.

What does Research Literature Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Research Literature Review is instructions for the agent only.

Does Research Literature Review 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 Research Literature Review 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. Review the folder before installing.

What licence does Research Literature Review use?

No licence was found for Research Literature Review or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Research Literature Review use?

About 558 tokens (SKILL.md is roughly 2.2k 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 2.3k tokens, read only when the agent opens those files.

What are the alternatives to Research Literature Review?

Skills that share tags, products or a category with Research Literature Review: Nature Paper Card (Yuan1z0825/nature-skills, 47k stars), Systematic Review Screener (Imbad0202/academic-research-skills, 51k stars), Literature Review (neflibata-feng/MyArxiv-Agent, 126 stars) and Preprint Search on bioRxiv (LigphiDonk/Oh-my--paper, 739 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research Literature Review?

haibarazz (a GitHub user) maintains it in haibarazz/awesome-codex-research, which has 100 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on September 23, 2026.

Source: haibarazz/awesome-codex-research on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.