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-data-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-data-zh)<a href="https://agentmods.dev/skills/aisa-team/agent-skills/prediction-market-data-zh"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-data-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-data-zh"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/prediction-market-data-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00108 | $0.01469 |
| Opus 5 | $0.00054 | $0.00734 |
| Sonnet 5 | $0.00022 | $0.00294 |
| Haiku 4.5 | $0.00011 | $0.00147 |
Grade A, and why
prediction-market-data-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.
This is a copy
86% identical to prediction-market-arbitrage-zh — 103 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
预测市场数据
通过 AIsa API 查询 Polymarket 和 Kalshi 预测市场。
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
查询预测市场数据的步骤：
- 搜索市场获取 ID（必须从这一步开始）
- 从返回结果中提取 ID（
token_id、condition_id或market_ticker） - 用 ID 查询详情（价格、订单簿、K线等）
快速示例
Polymarket：搜索 → 获取价格
# 第一步：搜索市场，提取 token_id（side_a.id 或 side_b.id）
python3 scripts/prediction_market_client.py polymarket markets --search "election" --status open --limit 5
# 第二步：用第一步的 token_id 获取价格
python3 scripts/prediction_market_client.py polymarket price <token_id>
Kalshi：搜索 → 获取价格
# 第一步：搜索市场，提取 market_ticker
python3 scripts/prediction_market_client.py kalshi markets --search "fed rate" --status open --limit 5
# 第二步：用第一步的 market_ticker 获取价格
python3 scripts/prediction_market_client.py kalshi price <market_ticker>
跨平台体育市场
python3 scripts/prediction_market_client.py sports by-date nba --date 2025-04-01
ID 参考
大多数命令需要从 markets 返回中获取 ID，务必先搜索。
| 平台 | ID 字段 | 获取位置 |
|---|---|---|
| Polymarket | token_id |
markets 输出中的 side_a.id 或 side_b.id |
| Polymarket | condition_id |
markets 输出中的 condition_id |
| Kalshi | market_ticker |
markets 输出中的 market_ticker |
命令参考
Polymarket
python3 scripts/prediction_market_client.py polymarket markets [--search <关键词>] [--status open|closed] [--min-volume <数值>] [--limit <数值>]
python3 scripts/prediction_market_client.py polymarket price <token_id> [--at-time <unix时间戳>]
python3 scripts/prediction_market_client.py polymarket activity --user <钱包地址> [--market-slug <slug>] [--limit <数值>]
python3 scripts/prediction_market_client.py polymarket orders [--market-slug <slug>] [--token-id <id>] [--user <钱包地址>] [--limit <数值>]
python3 scripts/prediction_market_client.py polymarket orderbooks --token-id <id> [--start <毫秒>] [--end <毫秒>] [--limit <数值>]
python3 scripts/prediction_market_client.py polymarket candlesticks <condition_id> --start <unix时间戳> --end <unix时间戳> [--interval 1|60|1440]
python3 scripts/prediction_market_client.py polymarket positions <钱包地址> [--limit <数值>]
python3 scripts/prediction_market_client.py polymarket wallet (--eoa <地址> | --proxy <地址>) [--with-metrics]
python3 scripts/prediction_market_client.py polymarket pnl <钱包地址> --granularity <day|week|month>
What ships with it
1 file 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 · 121 lines · 108 tokens per session scan A b171fb6f31b8
prediction-market-data-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 108 tokens to every session and 1,469 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to prediction-market-arbitrage-zh, differing in 103 lines, and is treated as a copy.
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