Build integrated IS/BS/CF financial workbooks in Excel.
中文简介正在准备中。当前显示原文说明。
Use for autonomous bug-hunt: scan, reproduce, fix, bounty.
中文简介正在准备中。当前显示原文说明。
安装前可以查看交给 AI 代理的指令内容。
Self-finding + self-fixing bug bounty system. Scans multiple sources, reproduces bugs, generates fixes, awards bounty points, and maintains a leaderboard.
scripts/bug-bounty.py
# Scan all sources for new bugs (no fixing)
python scripts/bug-bounty.py --scan
# Hunt one bug: find → reproduce → fix → award bounty
python scripts/bug-bounty.py --hunt
# Show leaderboard
python scripts/bug-bounty.py --leaderboard
# Show statistics (found/fixed/trend)
python scripts/bug-bounty.py --stats
| Code | Meaning |
|---|---|
| 0 | No bugs found |
| 1 | Bugs found (not fixed) |
| 2 | Bugs fixed + bounty awarded |
| Source | Description |
|---|---|
| GitHub Issues | Open issues with bug label (via gh CLI) |
| Cron Logs | Error patterns in cron output files (+ last_error fields in jobs.json) |
| Self-Healer Memory | Recurring issues (3+ occurrences) from self-healer's memory.json |
| Code Quality | Static analysis: bare except: clauses, TODO/FIXME markers |
| Severity | Base Points |
|---|---|
| Critical | 10 |
| High | 7 |
| Medium | 5 |
| Low | 3 |
| Info | 1 |
Bonuses: +2 for reproducible, +1-3 for source difficulty, +/-1 variance.
| File | Purpose |
|---|---|
~/.bug-bounty/state.json | Seen/fixed bugs, stats, scan history |
~/.bug-bounty/leaderboard.json | Bounty entries (fixer, points, bug) |
~/.bug-bounty/hunts.json | Detailed hunt log |
~/.bug-bounty/fix_*.md | Fix reports |
~/.bug-bounty/repro_*.txt | Reproduction output |
# Scan every 4 hours
openamer cronjob create \
--schedule 'every 240m' \
--script scripts/bug-bounty.py -- --scan \
--name 'Bug Bounty Scanner'
bugbot.py — GitHub Issues to PR pipeline (complementary: bugbot creates PRs, bug-bounty awards points)self-healer.py — daemon-level error recovery还没有评价。欢迎分享你的使用感受。
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Build integrated IS/BS/CF financial workbooks in Excel.
中文简介正在准备中。当前显示原文说明。
Run and grow the OpenAmer Agent-to-Agent swarm: identity, trust, node-to-node ask, signed skill/insight sharing, and the autonomous self-learning loop.
中文简介正在准备中。当前显示原文说明。
Use for A/B experiments on OpenAmer configs and skills.
中文简介正在准备中。当前显示原文说明。
Roleplay a hostile user to find and triage UX pain points.
中文简介正在准备中。当前显示原文说明。
Agent mesh: master/worker nodes, HTTP delegation, heartbeat.
中文简介正在准备中。当前显示原文说明。
Use for agentic commerce payments tasks. Candidate synthesized from trend radar; awaiting trial promotion.
中文简介正在准备中。当前显示原文说明。