AI-Powered-Literature-Review-Skills: Instructions file for Codex

AGENTS.md

AI-Powered-Literature-Review-Skills AGENTS.md is an instructions file for Codex, OpenCode from stephenlzc/AI-Powered-Literature-Review-Skills. It costs 4,040 tokens per session, scanned A, original, MIT.

Project guidance for a literature-review skill that searches academic databases and produces structured research summaries and citations.

In plain words
What is it for?
Use it when researching papers in CNKI, Web of Science, ScienceDirect, or PubMed, checking sources, creating citations, or generating a literature review.
Why use it?
It describes the review stages, supported sources, browser-based research approach, citation format, and project files so literature searches follow a repeatable process.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md.

This is stephenlzc/AI-Powered-Literature-Review-Skills's own configuration. It tells Codex and OpenCode how to work on AI-Powered-Literature-Review-Skills itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything AI-Powered-Literature-Review-Skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to stephenlzc/AI-Powered-Literature-Review-Skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/stephenlzc/AI-Powered-Literature-Review-Skills/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/stephenlzc/AI-Powered-Literature-Review-Skills

Made for: Codex, OpenCode.

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README.md
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Per session 4,040 This file is loaded in full into every session.
When invoked 4,040 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.04040 $0.04040
Opus 5 $0.02020 $0.02020
Sonnet 5 $0.00808 $0.00808
Haiku 4.5 $0.00404 $0.00404

Measured 12d ago against content hash bd563c3252e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

AI-Powered-Literature-Review-Skills AGENTS.md 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 12d ago.

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.

AGENTS.md · 470 lines

How it starts

The opening of the file, as written. The whole thing — 470 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md - Literature Reviewer Skill

项目概述

本项目是一个 Kimi CLI Skill(技能插件),名为 literature-reviewer-skill,用于帮助用户进行系统性的学术文献回顾(Literature Survey)。

版本: 3.1.0
最后更新: 2025-03-09

核心特性

  • 8阶段工作流:完整的文献调研流程
  • 浏览器自动化:无需API配置,直接访问数据库
  • 多数据库支持:CNKI、Web of Science、ScienceDirect、PubMed
  • 结构化输出:GB/T 7714-2015引文 + 标题 + 摘要的Markdown文档
  • 综述生成:自动生成结构化的文献综述

技术栈

  • 语言: Python 3.8+
  • 架构: 顺序执行工作流
  • 数据库访问: 浏览器自动化(Playwright)
  • 外部依赖:
    • Kimi CLI 的 browser skill
    • Kimi CLI 的 docx skill(可选)

项目结构

literature-reviewer-skill/
├── SKILL.md                          # Skill 定义文件(主入口)
├── AGENTS.md                         # 本文件
├── README.md                         # 项目说明文档
│
├── agents/                           # Agent 模板目录
│   ├── explore-agent.md              # 搜索 Agent 模板
│   ├── verify-agent.md               # 验证 Agent 模板
│   ├── synthesize-agent.md           # 综述 Agent 模板
│   └── orchestrator.md               # 协调器 Agent 模板
│
├── references/                       # 参考资料文档
│   ├── cnki-guide.md                 # CNKI 检索详细指南
│   ├── database-access.md            # 各数据库访问指南
│   └── gb-t-7714-2015.md             # GB/T 7714-2015 引用格式规范
│
└── assets/                           # 资源目录(预留)

8阶段工作流

Phase 0: Session Log      → 创建会话目录
Phase 1: Query Analysis   → AI生成关键词和检索策略
Phase 2: Parallel Search  → 浏览器自动化检索
Phase 3: Deduplication    → 去重筛选
Phase 4: Verification     → 元数据验证
Phase 5: Data Export      → 导出文献信息
Phase 6: Paper Analysis   → 单篇文献深度分析
Phase 7: Citation Format  → GB/T 7714-2015格式化
Phase 8: Synthesis        → 生成综述(大纲→撰写→审查→润色)

Phase 0: Session Log(会话管理)

目标:创建会话目录,记录工作进度,支持中断续传

目录结构

sessions/{YYYYMMDD}_{topic_short}/
├── session_log.md              # 工作日志
├── metadata.json               # 会话元数据
├── papers_raw.json             # 原始检索结果
├── papers_deduplicated.json    # 去重后文献
├── papers_analysis.json        # 文献分析结果
└── output/
    ├── references.md           # 文献清单(含摘要)
    ├── papers_analysis.md      # 单篇文献深度分析
    └── literature_review.md    # 最终综述(含摘要、关键词)

Read the full file on GitHub · 470 lines

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. 12d ago First seen · 470 lines · 4,040 tokens per session scan A bd563c3252e8

Subscribe to this mod's changes

AI-Powered-Literature-Review-Skills AGENTS.md is an instructions file published in the GitHub repository stephenlzc/AI-Powered-Literature-Review-Skills (141 stars, last pushed 5d ago), licensed MIT. It adds 4,040 tokens to every session, about $0.0202 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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