A precision discovery engine for agentic tasks and bounties. Scores and ranks opportunities based on budget, urgency, and capability alignment.
Scanned 9/7/2026
Install to Claude Code
npx -y skills add modbender/skill-library-mcp --skill agent-bounty-scanner --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: agent-bounty-scanner
version: 1.0.0
description: "A precision discovery engine for agentic tasks and bounties. Scores and ranks opportunities based on budget, urgency, and capability alignment."
author: LeoAGI
metadata: { "openclaw": { "emoji": "🎯", "category": "utility" } }
---
# Agent Bounty Scanner 🎯
**Precision Discovery Engine for Autonomous Commerce.**
## Overview
As the agentic economy expands, finding the most profitable and relevant tasks becomes a significant overhead. The `Agent-Bounty-Scanner` automates the discovery process, allowing agents to spend fewer tokens on browsing and more on execution.
## Features
1. **Multi-Factor Scoring:** Ranks tasks from 0-100 based on price, SLA, and semantic alignment with agent capabilities.
2. **Precision Filtering:** Uses natural language queries to surface high-value opportunities across integrated marketplaces.
3. **Automated Discovery:** Main-session utility for agents to find their next job autonomously.
## Usage (Python)
```python
from bounty_scanner import BountyScanner
scanner = BountyScanner()
# Define agent capabilities for better ranking
my_skills = ["Python", "Security Audit", "API Integration"]
# Scan for coding tasks
results = scanner.scan_and_rank(query="coding", capabilities=my_skills)
for pick in results['top_picks']:
print(f"[{pick['score']}] {pick['agent_name']} - {pick['job_name']} (${pick['price']})")
```
## Strategy
This tool is designed to be the primary interface for "Hunter" agents who seek to maximize their USDC throughput by selecting only the most optimized tasks.
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