A specialized skill for analyzing PDF documents through a remote MoDora HTTP service using secure, environment-based credential management.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install modora-http
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install modora-http using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is MoDora PDF Analysis Skill?
MoDora is a high-performance skill designed to interface with deployed MoDora services over HTTP. It enables AI agents to process complex PDF documents, perform OCR-adjacent reasoning, and conduct interactive Q&A sessions. Built with a security-first approach, this Openclaw Skills integration ensures that sensitive credentials like API keys are never stored in static configuration files, relying instead on environment variables.
The skill is optimized for developers who need to integrate deep document intelligence into their workflows without relying on a local frontend. By utilizing multimodal-capable models, it bridges the gap between raw document data and actionable AI insights, providing a robust pipeline for document preprocessing and retrieval-augmented generation.
MoDora PDF Analysis Skill Use Cases
- Automating the extraction of insights from lengthy PDF reports and technical manuals.
- Performing OCR-enhanced reasoning on scanned documents using multimodal AI models.
- Verifying the availability and health of remote MoDora service endpoints.
- Integrating document-based Q&A into automated terminal-based research workflows using Openclaw Skills.
How MoDora PDF Analysis Skill Works
- The user provides a non-secret settings.json file to define pipeline routing and model instances.
- Connectivity is verified by hitting the health endpoint of the MoDora service.
- The PDF document is uploaded via a secure POST request to the remote backend.
- The skill polls the task status endpoint, waiting for document preprocessing to reach a completed state.
- Once processed, the user sends natural language queries to the chat endpoint to extract specific information from the document.
MoDora PDF Analysis Skill Setup
To get started with this skill, ensure python3 is installed and set your environment variables:
export MODORA_BASE_URL="https://api.modora.pro"
export MODORA_USER_API_KEY="your_api_key_here"
export MODORA_USER_ENDPOINT="https://api.openai.com/v1"
export MODORA_USER_MODEL="gpt-4o"
Initialize your settings by copying the template:
cp skill/settings.template.json skill/settings.json
# Edit skill/settings.json to define your model instances
MoDora PDF Analysis Skill Data Schema & Taxonomy
The skill relies on a specific organizational structure for routing and identification:
| Component | Format | Description |
|---|---|---|
| Settings File | JSON | Contains non-secret pipeline routing (e.g., modelInstance IDs). |
| Credentials | Env Vars | MODORA_USER_API_KEY and endpoint configurations. |
| Identifiers | String | Uses filenames as unique keys for polling status and starting chats. |
| Client Header | Header | Sends X-Modora-Client: skill to distinguish from web UI traffic. |
MoDora PDF Analysis Skill Advanced Features
- Multi-stage automation: The analyze_pdf.py script wraps the entire health-upload-wait-chat lifecycle into a single command.
- Strict Security Boundaries: Requires explicit user acknowledgement (
--allow-remote-credentials) before transmitting data to remote services. - Multimodal Pipeline Support: Specifically designed to leverage models capable of both text and visual reasoning for superior OCR accuracy.
- Flexible Routing: Supports custom MODORA_BASE_URL overrides for self-hosted or private MoDora instances within Openclaw Skills.
SKILL.md
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