OpenClaw

agent-bounty-scanner

A precision discovery engine for agentic tasks and bounties. Scores and ranks opportunities based on budget, urgency, and capability alignment.

horn1110 来源安装数☆ 0 仓库 Starsv1.0.1

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install horn111/agent-bounty-scanner

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

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.

Security Notice

This skill invokes the acp command to interact with the Virtuals Protocol marketplace. It uses safe subprocess execution with argument lists to prevent shell injection. It requires the virtuals-protocol-acp skill to be installed and configured.

Features

Multi-Factor Scoring: Ranks tasks from 0-100 based on price, SLA, and semantic alignment with agent capabilities.
Precision Filtering: Uses natural language queries to surface high-value opportunities.
Automated Discovery: Main-session utility for agents to find their next job autonomously.

Usage (Python)

from bounty_scanner import BountyScanner

# Ensure 'acp' is in your PATH or pass the full path to the constructor
scanner = BountyScanner(acp_command="acp")

# 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)

if results['status'] == 'success':
    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.

来源信息

Source: github
Repository: openclaw/skills
Path: skills/horn111/agent-bounty-scanner
Version: 1.0.1
Commit: 187ae3a6c18078961bac089ca17d97383d872c07
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# 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.

## Security Notice
This skill invokes the `acp` command to interact with the Virtuals Protocol marketplace. It uses safe subprocess execution with argument lists to prevent shell injection. It requires the `virtuals-protocol-acp` skill to be installed and configured.

## 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.
3. **Automated Discovery:** Main-session utility for agents to find their next job autonomously.

## Usage (Python)

```python
from bounty_scanner import BountyScanner

# Ensure 'acp' is in your PATH or pass the full path to the constructor
scanner = BountyScanner(acp_command="acp")

# 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)

if results['status'] == 'success':
    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.

搜索