markets by machina-sports/sports-skills
npx skills add https://github.com/machina-sports/sports-skills --skill markets将 ESPN 直播赛程(NBA、NFL、MLB、NHL、WNBA、CFB、CBB)与 Kalshi 和 Polymarket 预测市场进行桥接。在编写查询之前,请查阅 references/api-reference.md 以了解支持的体育代码、命令参数和价格标准化格式。
sports-skills markets get_todays_markets --sport=nba
sports-skills markets search_entity --query="Lakers" --sport=nba
sports-skills markets compare_odds --sport=nba --event_id=401234567
sports-skills markets get_sport_markets --sport=nfl
sports-skills markets get_sport_schedule --sport=nba
sports-skills markets normalize_price --price=0.65 --source=polymarket
sports-skills markets evaluate_market --sport=nba --event_id=401234567
Python SDK:
from sports_skills import markets
markets.get_todays_markets(sport="nba")
markets.search_entity(query="Lakers", sport="nba")
markets.compare_odds(sport="nba", event_id="401234567")
markets.get_sport_markets(sport="nfl")
markets.get_sport_schedule(sport="nba", date="2025-02-26")
markets.normalize_price(price=0.65, source="polymarket")
markets.evaluate_market(sport="nba", event_id="401234567")
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关键:在调用任何协调命令之前,请验证:
get_todays_markets、compare_odds、get_sport_markets、evaluate_market),已提供 sport 代码。espn = 美式赔率,polymarket = 0-1 概率,kalshi = 0-100 整数。--sport=nba 会自动映射到正确的 Polymarket 体育代码和 Kalshi 系列代码。sport → series_id;Kalshi 使用 KXNBA、KXNFL 等。sports-skills markets get_todays_markets --sport=nba
返回每场比赛的 ESPN 信息、DraftKings 赔率、匹配的 Kalshi 市场以及匹配的 Polymarket 市场。
get_sport_schedule --sport=nbacompare_odds --sport=nba --event_id=<id>evaluate_market --sport=nba --event_id=<id>betting.evaluate_bet 管道处理:去偏 → 优势 → 凯利准则示例 1:今日比赛及预测市场赔率 用户说:"今天有哪些 NBA 比赛,预测市场赔率是多少?" 操作:
get_todays_markets(sport="nba")
结果:统一仪表板,包含每场比赛的 ESPN 信息和 Kalshi/Polymarket 价格示例 2:跨平台球队搜索 用户说:"在 Kalshi 和 Polymarket 上找到湖人队的市场" 操作:
search_entity(query="Lakers", sport="nba")
结果:两个交易所上所有湖人队市场的价格和交易量示例 3:特定比赛的赔率比较 用户说:"比较一下这场凯尔特人队比赛在 ESPN 和 Polymarket 上的赔率" 操作:
get_sport_schedule(sport="nba") 获取 event_idcompare_odds(sport="nba", event_id="<id>")
结果:标准化的并排比较,并自动检查套利机会示例 4:完整市场评估 用户说:"酋长队的比赛有优势吗?" 操作:
get_sport_schedule(sport="nfl") 获取 event_idevaluate_market(sport="nfl", event_id="<id>")
结果:公平概率、优势百分比、期望值、凯利分数和投注推荐示例 5:浏览某个体育项目的所有市场 用户说:"给我看看所有 NFL 预测市场" 操作:
get_sport_markets(sport="nfl")
结果:Kalshi 和 Polymarket 上所有开放的 NFL 市场示例 6:价格转换 用户说:"将 Polymarket 的 65 美分价格转换为美式赔率" 操作:
normalize_price(price=0.65, source="polymarket")
结果:包含隐含概率(0.65)、美式赔率(-185.7)和十进制赔率(1.54)的通用结构get_oddscompare_odds 查看不同来源的赔率。search_marketssearch_entity。get_scheduleget_sport_schedule。如果某个命令未在 references/api-reference.md 中列出,则它不存在。
错误:未返回某个体育项目的市场
原因:体育代码可能缺失或不正确
解决方案:检查 references/api-reference.md 中的有效体育代码。使用确切的代码(例如 nba、epl、laliga)
错误:compare_odds 对某个赛事未返回数据
原因:event_id 不正确或比赛尚未被索引
解决方案:首先调用 get_sport_schedule(sport=...) 来获取正确的 event_id
错误:响应中某个来源显示警告 原因:Kalshi 或 Polymarket 暂时不可用 解决方案:模块返回部分结果 — 使用可用的部分。直接使用 kalshi 或 polymarket 技能单独重试不可用的来源
错误:normalize_price 返回意外的美式赔率值
原因:错误的 source 参数 — Kalshi 使用 0-100 整数,Polymarket 使用 0-1 小数
解决方案:验证来源。Kalshi 价格 65 需要 source="kalshi",Polymarket 价格 0.65 需要 source="polymarket"
每周安装量
75
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55
首次出现
2026年2月26日
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Bridges ESPN live schedules (NBA, NFL, MLB, NHL, WNBA, CFB, CBB) with Kalshi and Polymarket prediction markets. Before writing queries, consult references/api-reference.md for supported sport codes, command parameters, and price normalization formats.
sports-skills markets get_todays_markets --sport=nba
sports-skills markets search_entity --query="Lakers" --sport=nba
sports-skills markets compare_odds --sport=nba --event_id=401234567
sports-skills markets get_sport_markets --sport=nfl
sports-skills markets get_sport_schedule --sport=nba
sports-skills markets normalize_price --price=0.65 --source=polymarket
sports-skills markets evaluate_market --sport=nba --event_id=401234567
Python SDK:
from sports_skills import markets
markets.get_todays_markets(sport="nba")
markets.search_entity(query="Lakers", sport="nba")
markets.compare_odds(sport="nba", event_id="401234567")
markets.get_sport_markets(sport="nfl")
markets.get_sport_schedule(sport="nba", date="2025-02-26")
markets.normalize_price(price=0.65, source="polymarket")
markets.evaluate_market(sport="nba", event_id="401234567")
CRITICAL: Before calling any orchestration command, verify:
sport code is provided for sport-aware commands (get_todays_markets, compare_odds, get_sport_markets, evaluate_market).espn = American odds, polymarket = 0-1 probability, kalshi = 0-100 integer.--sport=nba maps automatically to the correct Polymarket sport code and Kalshi series ticker.sport → series_id; Kalshi uses KXNBA, KXNFL, etc.sports-skills markets get_todays_markets --sport=nba
Returns each game with ESPN info, DraftKings odds, matching Kalshi markets, and matching Polymarket markets.
get_sport_schedule --sport=nbacompare_odds --sport=nba --event_id=<id>evaluate_market --sport=nba --event_id=<id>betting.evaluate_bet: devig → edge → KellyExample 1: Today's games with prediction market odds User says: "What NBA games are on today and what are the prediction market odds?" Actions:
get_todays_markets(sport="nba") Result: Unified dashboard with each game's ESPN info and Kalshi/Polymarket pricesExample 2: Cross-platform team search User says: "Find me Lakers markets on Kalshi and Polymarket" Actions:
search_entity(query="Lakers", sport="nba") Result: All Lakers markets across both exchanges with prices and volumeExample 3: Odds comparison for a specific game User says: "Compare the odds for this Celtics game across ESPN and Polymarket" Actions:
get_sport_schedule(sport="nba")compare_odds(sport="nba", event_id="<id>") Result: Normalized side-by-side comparison with automatic arbitrage checkExample 4: Full market evaluation User says: "Is there edge on the Chiefs game?" Actions:
get_sport_schedule(sport="nfl")evaluate_market(sport="nfl", event_id="<id>") Result: Fair probability, edge percentage, EV, Kelly fraction, and bet recommendationExample 5: Browse all markets for a sport User says: "Show me all NFL prediction markets" Actions:
get_sport_markets(sport="nfl") Result: All open NFL markets across Kalshi and PolymarketExample 6: Price conversion User says: "Convert a Polymarket price of 65 cents to American odds" Actions:
normalize_price(price=0.65, source="polymarket") Result: Common structure with implied probability (0.65), American odds (-185.7), and decimal (1.54)get_oddscompare_odds to see odds across sources.search_marketssearch_entity instead.get_scheduleget_sport_schedule instead.If a command is not listed in references/api-reference.md, it does not exist.
Error: No markets returned for a sport Cause: Sport code may be missing or incorrect Solution: Check references/api-reference.md for valid sport codes. Use the exact code (e.g., nba, epl, laliga)
Error: compare_odds returns no data for an event Cause: The event_id is incorrect or the game has not been indexed yet Solution: Call get_sport_schedule(sport=...) to retrieve the correct event_id first
Error: One source shows warnings in the response Cause: Kalshi or Polymarket is temporarily unavailable Solution: The module returns partial results — use what is available. Retry the unavailable source separately using the kalshi or polymarket skill directly
Error: normalize_price returns unexpected American odds value Cause: Wrong source parameter — Kalshi uses 0-100 integers, Polymarket uses 0-1 decimals Solution: Verify the source. Kalshi price of 65 requires source="kalshi", Polymarket price of 0.65 requires source="polymarket"
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Repository
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Feb 26, 2026
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