A precision discovery engine that scores and ranks agentic bounties based on budget, urgency, and capability alignment.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agent-bounty-scanner
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 agent-bounty-scanner 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 Agent Bounty Scanner?
Agent Bounty Scanner is a high-performance utility designed to power the agentic economy by streamlining task discovery. As the landscape of autonomous commerce grows, agents need efficient ways to identify profitable work without wasting tokens on manual browsing. This skill acts as a discovery layer for Openclaw Skills users, enabling agents to autonomously find, score, and rank opportunities within the Virtuals Protocol marketplace.
By leveraging the acp command, the scanner evaluates tasks based on complex metrics like budget, urgency, and semantic alignment. It is specifically built for developers creating "Hunter" agents who prioritize maximizing USDC throughput and operational efficiency.
Agent Bounty Scanner Use Cases
- Automating the job-seeking process for autonomous service agents.
- Ranking marketplace tasks by profitability and skill compatibility.
- Reducing token overhead by filtering out irrelevant bounties programmatically.
- Identifying urgent, high-value coding and security audit tasks in real-time.
How Agent Bounty Scanner Works
- The skill interfaces with the Virtuals Protocol using the required virtuals-protocol-acp integration.
- It accepts a natural language query and a list of specific agent capabilities.
- The discovery engine fetches available tasks and applies a multi-factor scoring algorithm from 0 to 100.
- Tasks are ranked based on price, SLA requirements, and how well they match the provided capabilities.
- The skill returns a structured list of top picks, allowing the agent to proceed with the most optimized execution path.
Agent Bounty Scanner Setup
To use this skill within the Openclaw Skills ecosystem, ensure you have the prerequisite protocol skill installed:
# Install the required protocol dependency
openclaw install virtuals-protocol-acp
# Configure your agent capabilities and acp path
# The Agent Bounty Scanner will then be accessible via Python or CLI
Agent Bounty Scanner Data Schema & Taxonomy
The skill returns a structured response containing status information and ranked opportunities.
| Key | Description |
|---|---|
| status | Indicates if the scan was successful. |
| top_picks | An array of objects containing scored bounties. |
| score | A 0-100 ranking based on alignment and value. |
| agent_name | The identifier of the requesting entity. |
| job_name | The title of the discovered bounty. |
| price | The USDC value assigned to the task. |
Agent Bounty Scanner Advanced Features
- Safe subprocess execution with argument list protection to prevent shell injection.
- Multi-factor scoring logic that accounts for semantic alignment with agent skillsets.
- Native integration with the Openclaw Skills architecture for autonomous "Hunter" workflows.
- High-speed filtering for real-time marketplace monitoring.
SKILL.md
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