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Agent Skill · 效率

modora-http(莫多拉 http)

modora-http 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

modora-http 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 8,986。

总安装 6,487周安装 265GitHub Stars 公开资料未说明下载 2,078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
MIT-0
版本
0.1.3

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:modora-http(莫多拉 http)
来源仓库:https://github.com/wu-uk/modora-http
安装命令:
openclaw skills install modora-http
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 modora-http

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

通过MoDora HTTP服务远程分析PDF文档内容。凭证由环境变量管理,保障密钥安全。modora-http 属于效率类 Skill,可作为该场景下的辅助能力补充。适用于自动化文档解析与数据提取任务。安装命令:openclaw skills install modora-http。

需预先配置API密钥并遵守服务商调用频率限制。

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 OpenClaw;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 openclaw skills install modora-http;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

modora-http 怎么安装?

在终端执行 openclaw skills install modora-http。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

modora-http 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

modora-http 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。

modora-http 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

modora-http 用的人多吗?

公开数据是累计安装 6,487 次,近一周安装 265 次,下载 2,078 次。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。

modora-http 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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。
  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

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。
  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
modora-http

莫多拉 http · 本页

6,487—接触敏感数据MIT-0通过

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

name
modora
description
Use this skill to analyze PDFs with a remote MoDora HTTP service. Credentials are managed through declared environment variables and are not stored in the settings file.
user-invocable
true
metadata
openclaw
requires
env
bins
primaryEnv
MODORA_USER_API_KEY

MoDora

Use this skill to work with a deployed MoDora service over HTTP.

This skill is for external skill access, not for the logged-in MoDora web UI.

Security Model

This skill uses a local settings.json only for non-secret pipeline routing. Credential values come from environment variables declared in metadata.openclaw.

The skill sends documents and questions to a remote MoDora service, and that trust boundary is still real. For non-local endpoints, the skill requires HTTPS.

Only use this skill if you trust the operator of the target MoDora server. If you do not trust that server, do not use this skill and deploy MoDora locally instead.

This skill is appropriate when the user wants to:

  • upload a PDF to MoDora
  • wait for document preprocessing to complete
  • ask questions about one uploaded document
  • verify that the public MoDora service is reachable

This skill assumes the MoDora backend is exposed as an HTTP base URL. Set MODORA_BASE_URL before running scripts. For public endpoints, use https://. Example:

export MODORA_BASE_URL="https://api.modora.pro"
export MODORA_USER_API_KEY="sk-..."
export MODORA_USER_ENDPOINT="https://api.openai.com/v1"
export MODORA_USER_MODEL="gpt-4o"

If MODORA_BASE_URL is unset, scripts default to https://api.modora.pro.

The scripts are implemented in Python so they work across Linux, macOS, Windows, and WSL as long as python3 is available.

Skill access is separate from the logged-in frontend:

  • skill requests send X-Modora-Client: skill
  • skill requests do not use the frontend login session
  • skill requests must provide a user-owned non-secret settings JSON file
  • skill requests cannot use server default model instance IDs such as local-default or remote-default
  • if the user does not provide a valid settings file, the skill must stop instead of falling back to server defaults
  • skill credentials are provided through environment variables, not through the settings file
  • skill scripts require explicit acknowledgement before contacting the remote MoDora service

Required settings file

Every skill invocation that uploads a document or asks a question must provide a user-owned settings.json.

Start from skill/settings.template.json and fill in the pipeline routing values.

The settings file must:

  • be provided by the skill user, not copied from the server UI defaults
  • include pipelines.<module>.modelInstance for each pipeline module
  • avoid secret fields such as api_key, base_url, Authorization, or token values
  • avoid server default model instance IDs such as local-default and remote-default
  • use multimodal-capable model instances for the MoDora pipeline

Credentials must be supplied through:

  • MODORA_USER_API_KEY
  • MODORA_USER_ENDPOINT
  • MODORA_USER_MODEL

MoDora requires multimodal models. Do not choose text-only models for OCR-adjacent reasoning, enrichment, retrieval, metadata generation, or QA.

If the user does not provide this file, stop and report the requirement. Do not continue with upload or QA.

Preferred workflow

  1. Prepare a settings.json file owned by the skill user.

A good starting point is skill/settings.template.json.

  1. Run python skill/scripts/health.py to verify the backend is alive.
  2. Export MODORA_USER_API_KEY, MODORA_USER_ENDPOINT, and MODORA_USER_MODEL.
  3. Confirm that you trust the remote MoDora service operator and explicitly allow remote access.
  4. Run python skill/scripts/upload.py /absolute/path/to/file.pdf --settings-file /path/to/settings.json --allow-remote-credentials to upload a document.
  5. Run python skill/scripts/wait.py <filename> until processing reaches completed.
  6. Run python skill/scripts/chat.py <filename> "<question>" --settings-file /path/to/settings.json --allow-remote-credentials to ask a question.

For the common one-shot flow, prefer:

python skill/scripts/analyze_pdf.py /absolute/path/to/file.pdf "Your question" --settings-file /path/to/settings.json --allow-remote-credentials

Rules

  • Always use an absolute file path when uploading.
  • Always provide a user-owned non-secret settings JSON file.
  • Always provide credentials through declared environment variables instead of the settings file.
  • Explicitly confirm remote service access before running upload or chat commands.
  • Never fall back to server-side defaults when the settings file is missing.
  • Do not call chat.py before the task status becomes completed.
  • Do not use server default model instance IDs such as local-default or remote-default.
  • Use multimodal-capable model instances across the MoDora pipeline.
  • If the backend returns an error, surface the response body instead of hiding it.
  • If the service is unreachable, tell the user the MoDora public backend is not available.
  • If the user supplies a different service URL, set MODORA_BASE_URL for that command.
  • For non-local endpoints, require https://.

Script summary

  • scripts/health.py: GET /health
  • scripts/upload.py: POST /api/upload after explicit remote credential acknowledgement
  • scripts/wait.py: poll GET /api/task/status/{filename}
  • scripts/chat.py: POST /api/chat after explicit remote credential acknowledgement
  • scripts/analyze_pdf.py: health -> upload -> wait -> chat with explicit remote credential acknowledgement

平台分布

OpenClaw

89.77%
按下载量换算1,865

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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