A comprehensive suite of 24 specialized AI agents designed to automate business back-office operations through a unified API.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install digital-labour
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 digital-labour 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 Digital Labour?
Digital Labour is a powerful collection of 24 AI agents that function as an automated back-office for businesses and freelancers. By integrating this into Openclaw Skills, users gain access to specialized capabilities ranging from sales outreach and lead generation to bookkeeping and technical documentation.
Each agent is powered by leading LLMs like GPT-4o and Claude, ensuring high-quality outputs that undergo automated QA verification before delivery. This skill bridges the gap between raw AI and actionable business results by providing a management layer that handles context, quality control, and workflow scheduling.
Digital Labour Use Cases
- Automating end-to-end sales pipelines from lead generation to personalized email sequences.
- Scaling content marketing efforts by repurposing blog posts into social media updates and SEO-optimized landing pages.
- Streamlining operational tasks like web scraping, data entry, and CRM management.
- Generating professional business documents, including proposals, market research reports, and technical API documentation.
How Digital Labour Works
- The user configures the API environment and selects a specific agent based on the required business task.
- A command is issued via the Python-based helper script, passing parameters in a structured JSON format.
- The internal management layer orchestrates the request, selecting the optimal LLM provider and handling context.
- Every output is processed through a QA manager agent to verify quality and accuracy.
- The final structured JSON response is returned to the user for immediate use in their workflow.
Digital Labour Setup
Set the API endpoint in your environment:
export DIGITAL_LABOUR_API_URL="https://bitrage-labour-api-production.up.railway.app"
Verify the connection using the health check command:
python3 scripts/dl-api.py health
List all available agents and their required input schemas to use within Openclaw Skills:
python3 scripts/dl-api.py agents
Digital Labour Data Schema & Taxonomy
Digital Labour uses a structured JSON schema for both inputs and outputs to maintain consistency across all 24 agents.
| Field | Description |
|---|---|
| agent | The specific identifier for the AI agent (e.g., sales_outreach) |
| inputs | A JSON object containing task-specific parameters like keyword or company name |
| status | The execution status including QA verification results |
| output | The final structured content generated by the agent |
Digital Labour Advanced Features
- Multi-agent pipelines that chain tasks like market research, SEO content creation, and social media repurposing.
- Batch processing mode for executing multiple agent tasks sequentially from a single JSON configuration file.
- Intelligent management layer including context, QA, and production managers for high-reliability outputs.
- Cross-provider support leveraging GPT-4o, Claude, Gemini, and Grok for diverse technical requirements within the Openclaw Skills ecosystem.
SKILL.md
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