Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AIsa-team/agent-skills --skill prediction-market-arbitrage-zhgit clone --depth 1 https://github.com/AIsa-team/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-arbitrage-zh)<a href="https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-arbitrage-zh"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-arbitrage-zh/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-arbitrage-zh"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-arbitrage-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00096 | $0.01224 |
| Opus 5 | $0.00048 | $0.00612 |
| Sonnet 5 | $0.00019 | $0.00245 |
| Haiku 4.5 | $0.00010 | $0.00122 |
Grade A, and why
prediction-market-arbitrage-zh scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- prediction-market-data-zh — 86% identical, 103 lines differ
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
预测市场套利
通过 AIsa API 发现 Polymarket 和 Kalshi 之间的套利机会。
配置
export AISA_API_KEY="your-key"
在 aisa.one 获取 Key（$0.01/次查询，按量付费）。
工作流程
发现套利机会的步骤：
- 扫描匹配市场（
scan批量扫描，match分析特定市场） - 查看价差 — 工具自动计算跨平台价格差异
- 验证流动性 — 用
prediction_market_client.py orderbooks检查订单簿深度后再行动
快速示例
扫描某项运动的套利机会
# 扫描指定日期所有 NBA 市场 — 自动显示价差
python3 scripts/arbitrage_finder.py scan nba --date 2025-04-01
分析特定市场
# 通过 Polymarket slug
python3 scripts/arbitrage_finder.py match --polymarket-slug <slug>
# 通过 Kalshi ticker
python3 scripts/arbitrage_finder.py match --kalshi-ticker <ticker>
行动前验证流动性
# 检查两边的订单簿深度
python3 scripts/prediction_market_client.py polymarket orderbooks --token-id <id>
python3 scripts/prediction_market_client.py kalshi orderbooks --ticker <ticker>
命令参考
arbitrage_finder.py — 自动检测
python3 scripts/arbitrage_finder.py scan <运动类型> --date <YYYY-MM-DD> [--min-spread <百分比>] [--min-liquidity <美元>] [--json]
python3 scripts/arbitrage_finder.py match --polymarket-slug <slug> [--min-spread <百分比>] [--min-liquidity <美元>] [--json]
python3 scripts/arbitrage_finder.py match --kalshi-ticker <ticker> [--min-spread <百分比>] [--min-liquidity <美元>] [--json]
支持：nba、nfl、mlb、nhl、soccer、tennis。
prediction_market_client.py — 原始市场数据
用于手动价格检查和深入分析。
# 搜索市场
python3 scripts/prediction_market_client.py polymarket markets --search <关键词> --status open --limit 5
python3 scripts/prediction_market_client.py kalshi markets --search <关键词> --status open --limit 5
# 获取价格（使用 markets 输出中的 token_id / market_ticker）
python3 scripts/prediction_market_client.py polymarket price <token_id>
python3 scripts/prediction_market_client.py kalshi price <market_ticker>
# 跨平台体育市场匹配
python3 scripts/prediction_market_client.py sports by-date <运动类型> --date <YYYY-MM-DD>
python3 scripts/prediction_market_client.py sports matching (--polymarket-slug <slug> | --kalshi-ticker <ticker>)
# 订单簿深度
python3 scripts/prediction_market_client.py polymarket orderbooks --token-id <id>
python3 scripts/prediction_market_client.py kalshi orderbooks --ticker <ticker>
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 114 lines · 96 tokens per session scan A dc58f8c3b166
prediction-market-arbitrage-zh is a skill published in the GitHub repository AIsa-team/agent-skills (25 stars, last pushed 2d ago), licensed Apache-2.0. It adds 96 tokens to every session and 1,224 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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