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literature-manager文献经理

Agent Skill

literature-manager 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

28,813

周安装

1,177

GitHub Stars

2

下载量

9,322
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:literature-manager(文献经理)
来源仓库:https://github.com/isonaei/literature-manager
安装命令:
openclaw skills install literature-manager
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install literature-manager

简介

literature-manager 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。

  • 搜索、下载、转换、组织和审核学术文献集,适用于文献管理场景。
  • 通过安装命令 openclaw skills install literature-manager 集成到 OpenClaw 宿主环境。
  • 使用前需确认权限范围、维护状态及是否涉及联网、命令执行或文件读写。
  • 建议结合来源仓库和原始 README 进一步核验具体用法和功能边界。

SKILL.md

name
literature-manager
description
Search, download, convert, organize, and audit academic literature collections. Use when asked to find papers, build a literature library, add papers to references, download PDFs, convert papers to markdown, organize references by category, audit a reference collection, or collect code/dataset links for tools mentioned in papers.

Literature Manager

Manage academic literature collections: search → download → convert → organize → verify.

Dependencies

  • pdftotext (poppler-utils) — PDF text extraction
  • curl — downloading
  • python3 — JSON processing in audit
  • file (coreutils) — PDF validation
  • uvx markitdown[pdf] (optional) — fallback PDF→MD converter (note: plain uvx markitdown does NOT work for PDFs — must use uvx markitdown[pdf])

Quick Start

# Download a single paper by DOI
bash scripts/download.sh "10.1038/s41592-024-02200-1" output_dir/

# Convert PDF to markdown
bash scripts/convert.sh paper.pdf output.md

# Verify a single PDF+MD pair
bash scripts/verify.sh paper.pdf paper.md

# Full audit of a references/ folder
bash scripts/audit.sh /path/to/references/

Workflow

1. Search

Use web_fetch on Google Scholar:

https://scholar.google.com/scholar?q=QUERY&as_ylo=YEAR

Extract: title, authors, year, journal, DOI, PDF links.

For each result, identify the best open-access PDF source (see Download Strategy).

2. Download

Run scripts/download.sh <DOI_or_URL> <output_dir/> per paper. The script tries sources in order:

  1. Direct publisher PDF (Nature, eLife, Frontiers, PNAS, bioRxiv, arXiv)
  2. EuropePMC (PMC_ID → PDF)
  3. bioRxiv/arXiv preprint
  4. Sci-Hubhttps://sci-hub.box/<DOI> (use when publisher is paywalled)
# Sci-Hub download example:
curl -L "https://sci-hub.box/10.1038/nature12345" -o paper.pdf
⚠️ Legal note: Sci-Hub may violate publisher terms of service or copyright law in some jurisdictions. Use only if you understand and accept the legal implications in your context.

If all sources fail (including Sci-Hub), flag as permanent paywall. Provide the user with the DOI and ask for manual download.

3. Convert

Run scripts/convert.sh <input.pdf> <output.md>. Uses pdftotext (reliable) with uvx markitdown[pdf] as fallback.

# Correct markitdown command for PDFs:
uvx markitdown[pdf] input.pdf > output.md

# ⚠️ The following will NOT work for PDFs (missing [pdf] extra):
# uvx markitdown input.pdf

Prefer uvx markitdown[pdf] over pdftotext when full fidelity (tables, figures captions) matters.

4. Organize

Standard folder structure:

references/
├── README.md              # Human index (summaries per category)
├── index.json             # Machine index (structured metadata)
├── RESOURCES.md           # Code repos + datasets
├── resources.json         # Structured version
├── <category-1>/
│   ├── papers/            # PDFs
│   └── markdown/          # Converted text
└── <category-N>/
    ├── papers/
    └── markdown/

Categories are user-defined. Number-prefix for sort order (e.g., 01-theoretical-frameworks/).

index.json schema per paper

{
  "id": "short_id",
  "title": "Full title",
  "authors": ["Author1", "Author2"],
  "year": 2024,
  "journal": "Journal Name",
  "doi": "10.xxxx/...",
  "category": "category_name",
  "subcategory": "optional",
  "pdf_path": "category/papers/filename.pdf",
  "markdown_path": "category/markdown/filename.md",
  "tags": ["tag1", "tag2"],
  "one_line_summary": "English one-liner",
  "key_concepts": ["concept1"],
  "relevance_to_project": "English description"
}

README.md pattern

Per category section, per paper: title, authors, year, journal, DOI, short summary in user's language.

4b. DOI-Based Filenames & Path Mapping

Downloaded files are often named using DOI format rather than AuthorYear:

10-1038_ncomms3018.md        # DOI: 10.1038/ncomms3018
10-1016_j-neuron-2015-03-034.md

When markdown_path entries in index.json become stale (e.g., after folder reorganization), maintain a separate mapping file:

// temp/paper_md_mapping.json
{
  "author2024_keyword": "references/new-downloads/10-1038_s41592-024-02200-1.md",
  ...
}

To build this mapping: cross-reference each paper's DOI in index.json against actual files on disk. Use find + Python to automate.

index.json Known Pitfalls

  • id: null corruption: If many entries have id=null and share the same pdf_path, the index was likely corrupted during a batch write. Rebuild from actual files on disk.
  • DOI errors: Verify DOIs resolve correctly — typos in DOI fields are common (e.g., wrong suffix digits). Always cross-check with publisher page.
  • Dead markdown_path: After restructuring folders, markdown_path in index.json often points to old locations. Use the mapping file above as the source of truth.

5. Verify

Run scripts/audit.sh <references_dir/> for full verification:

  • Every PDF is valid (file -b = PDF)
  • Every PDF title matches filename (pdftotext | head)
  • Every PDF has matching markdown (and vice versa)
  • index.json is valid, complete, paths exist, no duplicate IDs
  • README.md stats match actual counts

6. Collect Resources

For tool/method papers, find GitHub repos and public datasets. Store in RESOURCES.md + resources.json.

Sub-agent Strategy

For large batches, parallelize:

  • Download: 1 sub-agent per batch of ~5-8 papers
  • Organize: 1 sub-agent to build indexes
  • Verify: 1 independent sub-agent (never the same as organizer)

Always use a separate sub-agent for verification (QC should not self-grade).

⚠️ Sub-agent Rules (Learned from Practice)

  1. One batch at a time — do not spawn multiple note-writing batches simultaneously; LLM rate limits will cause silent failures
  2. Set a cron monitor whenever spawning long-running agents — agents can fail silently without triggering auto-announce; cron catches this
  3. Cron monitor pattern:
   1. Spawn agent(s)
   2. Immediately set a cron job (every 10-15 min, isolated agentTurn)
      → Check if expected output files exist
      → Re-spawn failed agents
      → When all complete: announce + delete cron
   3. After task finishes, confirm cron was removed

Adding Papers Incrementally

To add papers to an existing collection:

  1. Download + convert new papers into correct category folder
  2. Append entries to index.json
  3. Update README.md stats
  4. Run audit to verify consistency

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

77.78%
按下载量换算7,251

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install literature-manager 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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