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modora-http莫多拉 http

Agent Skill

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。

总安装

6,487

周安装

265

GitHub Stars

公开资料未说明

下载量

2,078
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: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

简介

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。

SKILL.md

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

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

89.77%
按下载量换算1,865

安全审计

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权限和风险

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

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