Bounty Hunter Agent#

Metadata#

• Name: bounty-hunter-agent
• Version: 1.0.0
• Author: lanxevo3
• Tags: github, bounty, automation, monetization, algora, opire
• License: MIT

Description#

Autonomous GitHub bounty hunting agent. Scans for paid issues across GitHub, Algora, and Opire, evaluates viability based on competition level and payout amount, and helps you prioritize and submit PRs automatically.

What It Does#

1. Scans repositories for bounty-labeled issues ( bounty, 💰, reward, paid, algora, opire)
2. Evaluates competition level by checking existing PRs and comments on each issue
3. Scores opportunities by payout amount, competition density, issue age, and repo activity
4. Prioritizes a ranked list of actionable bounties sorted by expected value
5. Tracks state in a local JSON file so you never re-scan the same issues
6. Spawns fix sessions — integrates with OpenClaw to kick off autonomous coding sessions for top-ranked bounties

Prerequisites#

• gh CLI authenticated ( gh auth status should succeed)
• Python 3.8+ (stdlib only — no pip dependencies)
• Optional: OpenClaw runtime for automated fix session spawning

Usage#

Quick Scan#

bash

python ~/.agents/skills/bounty-hunter-agent/scripts/bounty_scan.py

With OpenClaw#

When installed as a skill, invoke via:

text

/bounty-hunter-agent scan

The agent will:

• Search GitHub for bounty-labeled issues
• Check Algora and Opire for listed bounties
• Output a ranked JSON report to ~/.agents/skills/bounty-hunter-agent/state/bounties.json
• Print a human-readable summary to stdout

Configuration#

Set environment variables to customize behavior:

VariableDefaultDescriptionBOUNTY_MIN_PAYOUT``25Minimum payout in USD to considerBOUNTY_MAX_COMPETITION``5Max competing PRs before skippingBOUNTY_SCAN_LIMIT``100Max issues to scan per queryBOUNTY_STATE_DIR``~/.agents/skills/bounty-hunter-agent/stateWhere to store state

Output Format#

The scan produces a ranked list:

json

[
  {
    "rank": 1,
    "score": 87.5,
    "repo": "org/repo",
    "issue": 123,
    "title": "Add feature X",
    "payout_usd": 200,
    "competing_prs": 1,
    "url": "https://github.com/org/repo/issues/123",
    "labels": ["bounty", "💰 200"],
    "age_days": 3
  }
]

How Scoring Works#

text

score = payout_weight * (payout / max_payout)
      + competition_weight * (1 - competing_prs / max_competition)
      + freshness_weight * (1 - age_days / max_age)

Default weights: payout=50, competition=35, freshness=15

Lower competition + higher payout + newer issue = higher score.