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Agent Skill · 待分类

nutrient-document-processing(营养文件处理)

nutrient-document-processing 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

nutrient-document-processing 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在待分类类的 11,209 个 Skill 里排第 1,290。

总安装 4,015周安装 164GitHub Stars 6下载 1,299核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:nutrient-document-processing(营养文件处理)
来源仓库:https://github.com/pspdfkit-labs/nutrient-agent-skill
仓库路径:skills/nutrient-document-processing
安装命令:
npx skills add https://github.com/pspdfkit-labs/nutrient-agent-skill --skill nutrient-document-processing
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/pspdfkit-labs/nutrient-agent-skill --skill nutrient-document-processing

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

nutrient-document-processing 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合项目协作管理。适用于围绕仓库状态、代码变更或协作事项进行信息组织与查询。通过 npx skills add 命令从 GitHub 仓库安装并使用。

安装前应确认权限范围、维护状态及是否涉及网络或系统操作。建议查阅原始 SKILL.md 获取详细用法和限制说明。

来源仓库内路径:skills/nutrient-document-processing

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/pspdfkit-labs/nutrient-agent-skill --skill nut…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

nutrient-document-processing 怎么安装?

在终端执行 npx skills add https://github.com/pspdfkit-labs/nutrient-agent-skill --skill nutrient-docu…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

nutrient-document-processing 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

nutrient-document-processing 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

nutrient-document-processing 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

nutrient-document-processing 用的人多吗?

公开数据是累计安装 4,015 次,近一周安装 164 次,下载 1,299 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

nutrient-document-processing 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
nutrient-document-processing

营养文件处理 · 本页

4,0156接触敏感数据未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Nutrient Document Processing

Use Nutrient DWS for managed document workflows where fidelity, compliance, or multi-step processing matters more than local-tool convenience.

Setup

  • Get a Nutrient DWS API key at https://dashboard.nutrient.io/sign_up/?product=processor.
  • Direct API calls use Authorization: Bearer $NUTRIENT_API_KEY. export NUTRIENT_API_KEY="nutr_sk_..."
  • MCP setups commonly use @nutrient-sdk/dws-mcp-server with NUTRIENT_DWS_API_KEY.
  • Scripts live in scripts/ relative to this SKILL.md. Use the directory containing this SKILL.md as the working directory: cd <directory containing this SKILL.md> && uv run scripts/<script>.py --help
  • Page ranges use start:end with 0-based indexes and end-exclusive semantics. Negative indexes count from the end.

When to use

  • Generate PDFs from HTML templates, uploaded assets, or remote URLs.
  • Convert Office, HTML, image, and PDF files between supported formats.
  • OCR scans and extract text, tables, or key-value pairs.
  • Redact PII, watermark, sign, fill forms, merge, split, rotate, flatten, or encrypt PDFs.
  • Produce delivery targets like PDF/A, PDF/UA, optimized PDFs, or linearized PDFs.
  • Check credits before large, batch, or AI-heavy runs.

Tool preference

  1. Prefer scripts/*.py for covered single-operation workflows.
  2. Use assets/templates/custom-workflow-template.py for multi-step jobs that should still run through the Python client.
  3. Use the modular references/ docs and direct API payloads for capabilities that do not yet have a dedicated helper script, especially HTML/URL generation and compliance tuning.
  4. Use local PDF utilities only for lightweight inspection. Use Nutrient when output fidelity or compliance matters.

Single-operation scripts

  • convert.py -> convert between pdf, pdfa, pdfua, docx, xlsx, pptx, png, jpeg, webp, html, and markdown
  • merge.py -> merge multiple files into one PDF
  • split.py -> split one PDF into multiple PDFs by page ranges
  • add-pages.py -> append blank pages
  • delete-pages.py -> remove specific pages
  • duplicate-pages.py -> reorder or duplicate pages into a new PDF
  • rotate.py -> rotate selected pages
  • ocr.py -> OCR scanned PDFs or images
  • extract-text.py -> extract text to JSON
  • extract-table.py -> extract tables
  • extract-key-value-pairs.py -> extract key-value pairs
  • watermark-text.py -> apply a text watermark
  • redact-ai.py -> detect and apply AI-powered redactions
  • sign.py -> digitally sign a local PDF
  • password-protect.py -> write encrypted output PDFs
  • optimize.py -> apply optimization and linearization-style options via JSON

Multi-Step Workflow Rule

Do not add new committed pipeline scripts under scripts/.

When the user asks for multiple operations in one run:

  1. Copy assets/templates/custom-workflow-template.py to a temporary location such as /tmp/ndp-workflow-<task>.py.
  2. Implement the combined workflow in that temporary script.
  3. Run it with uv run /tmp/ndp-workflow-<task>.py....
  4. Return generated output files.
  5. Delete the temporary script unless the user explicitly asks to keep it.

PDF Requirements

  • split.py requires a multi-page PDF and cannot extract ranges from a single-page document.
  • delete-pages.py must retain at least one page and cannot delete the entire document.
  • sign.py only accepts local file paths for the main PDF.

Decision rules

  • Prefer a helper script when one already covers the requested operation cleanly.
  • If you control the source markup, prefer HTML generation over browser print workflows.
  • Use remote file.url inputs when the source already lives at a stable URL and you want to avoid local uploads.
  • Use output.type for conversion and finalization targets. Use actions for transformations when building direct API payloads.
  • OCR before text extraction, key-value extraction, or semantic redaction on scans.
  • Prefer preset or regex redaction when the target is explicit. Use AI redaction only for contextual or natural-language requests.
  • Use the PDF manipulation reference for merge, split, rotate, flatten, and page-range workflows instead of inferring those payloads from conversion examples.
  • Treat PDF/A and PDF/UA as compliance targets, not cosmetic export formats. Choose the target up front and validate final artifacts when requirements are contractual.
  • For PDF/UA, clean born-digital inputs and structured HTML usually tag better than rasterized or flattened source PDFs.
  • For delivery optimization, linearize or optimize unsigned output artifacts instead of mutating already signed files.
  • When the user asks for multiple steps, keep destructive or final steps late in the sequence. Use the workflow recipes when ordering is ambiguous.

Anti-patterns

  • Do not OCR born-digital PDFs just because the task mentions extraction. Extract first and OCR only if the text layer is missing.
  • Do not flatten forms or annotations until the user confirms the artifact no longer needs to stay editable.
  • Do not sign, archive, or linearize intermediate working files. Keep those as final-delivery steps.
  • Do not promise PDF/A or PDF/UA compliance without a validation step when the requirement is contractual.
  • Do not commit temporary workflow scripts under scripts/.

Reference map

Read only what you need:

  • references/request-basics.md -> endpoint model, auth, multipart vs JSON, credits, limits, and errors
  • references/generation-and-conversion.md -> HTML/URL generation and format conversion
  • references/pdf-manipulation.md -> merge, split, page-range, rotate, and flatten workflows
  • references/extraction-and-ocr.md -> OCR, text extraction, tables, and key-value workflows
  • references/security-signing-and-forms.md -> redaction, watermarking, signatures, forms, and passwords
  • references/compliance-and-optimization.md -> PDF/A, PDF/UA, optimization, and linearization
  • references/workflow-recipes.md -> end-to-end sequencing patterns for common business document workflows

Rules

  • Fail fast when required arguments are missing.
  • Write outputs to explicit paths and print created files.
  • Do not log secrets.
  • All client methods are async and should run via asyncio.run(main()).
  • If import fails, install dependency with uv add nutrient-dws.

Security Hardening Addendum

  • Prefer a pinned, preinstalled MCP server binary over runtime package fetches.

- Preferred: npm i -g @nutrient-sdk/dws-mcp-server@<pinned-version> - Avoid unpinned runtime fetch in production paths.

  • Never store NUTRIENT_DWS_API_KEY in committed JSON config files.

- Use process env injection at runtime (shell/export, secrets manager, or host env).

  • Restrict file access with SANDBOX_PATH to the minimum required working directory.
  • Before enabling MCP mode in production, verify package provenance and lock version.

平台分布

Codex

35.22%
按下载量换算458

Claude

31.76%
按下载量换算413

Cursor

18.88%
按下载量换算245

Gemini CLI

9.29%
按下载量换算121

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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