markets

Name: markets
Author: machina-sports

645installs27forks

How to install markets?

machina-sports/sports-skills/markets

$npx -y skills add machina-sports/sports-skills --skill markets

Installs into the current project.

Summary

Markets orchestration — connects ESPN live schedules with Kalshi and Polymarket prediction markets. Unified dashboards, odds comparison, entity search, and bet evaluation across platforms. Use when: user wants to see prediction market odds alongside ESPN game schedules, compare o

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SKILL.md

1	# Markets Orchestration
2
3	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.
4
5	## Quick Start
6
7	```bash
8	sports-skills markets get_todays_markets --sport=nba
9	sports-skills markets search_entity --query="Lakers" --sport=nba
10	sports-skills markets compare_odds --sport=nba --event_id=401234567
11	sports-skills markets get_sport_markets --sport=nfl
12	sports-skills markets get_sport_schedule --sport=nba
13	sports-skills markets normalize_price --price=0.65 --source=polymarket
14	sports-skills markets evaluate_market --sport=nba --event_id=401234567
15	sports-skills markets match_markets --sport=mlb --date=2026-06-06
16	sports-skills markets get_market_price --venue=kalshi --ticker=KXMENWORLDCUP-26-FR
17	sports-skills markets get_price_history --venue=kalshi --ticker=KXMENWORLDCUP-26-FR --interval=1d
18	```
19
20	Python SDK:
21	```python
22	from sports_skills import markets
23
24	markets.get_todays_markets(sport="nba")
25	markets.search_entity(query="Lakers", sport="nba")
26	markets.compare_odds(sport="nba", event_id="401234567")
27	markets.get_sport_markets(sport="nfl")
28	markets.get_sport_schedule(sport="nba", date="2025-02-26")
29	markets.normalize_price(price=0.65, source="polymarket")
30	markets.evaluate_market(sport="nba", event_id="401234567")
31	markets.match_markets(sport="mlb", date="2026-06-06")
32	markets.get_market_price(venue="kalshi", ticker="KXMENWORLDCUP-26-FR", at_time="2026-05-01T12:00:00+00:00")
33	markets.get_price_history(venue="polymarket", token_id="<token_id>", interval="1h")
34	```
35
36	## CRITICAL: Before Any Query
37
38	CRITICAL: Before calling any orchestration command, verify:
39	- A `sport` code is provided for sport-aware commands (`get_todays_markets`, `compare_odds`, `get_sport_markets`, `evaluate_market`).
40	- Price sources are identified correctly before normalization: `espn` = American odds, `polymarket` = 0-1 probability, `kalshi` = 0-100 integer.
41
42	## Important Notes
43
44	- Sport context is passed through. `--sport=nba` maps automatically to the correct Polymarket sport code and Kalshi series ticker.
45	- Both platforms use sport-aware search. Polymarket uses `sport` → series_id; Kalshi uses `KXNBA`, `KXNFL`, etc.
46	- Prices are normalized. Everything is converted to implied probability for comparison.
47
48	## Workflows
49
50	### Today's NBA Dashboard
51
52	```bash
53	sports-skills markets get_todays_markets --sport=nba
54	```
55	Returns each game with ESPN info, DraftKings odds, matching Kalshi markets, and matching Polymarket markets.
56
57	### Find Arb on a Specific Game
58
59	1. Get the ESPN event ID: `get_sport_schedule --sport=nba`
60	2. Compare odds: `compare_odds --sport=nba --event_id=<id>`
61	3. If arbitrage detected, response includes allocation percentages and guaranteed ROI.
62
63	### Full Bet Evaluation
64
65	1. `evaluate_market --sport=nba --event_id=<id>`
66	2. Fetches ESPN odds and matching prediction market price
67	3. Pipes through `betting.evaluate_bet`: devig → edge → Kelly
68	4. Returns fair probability, edge, EV, Kelly fraction, and recommendation
69
70	### Same Game on Both Venues
71
72	1. `match_markets --sport=mlb --date=2026-06-06`
73	2. Each match pairs the Kalshi event (with market tickers) and the Polymarket event (with moneyline token IDs) for the same game — joined deterministically on date + team codes, fuzzy title match as fallback.
74	3. Feed `kalshi.market_tickers[i]` and `polymarket.markets[i].token_ids[j]` straight into `get_market_price` to compare prices.
75
76	### Price Movement Over Time
77
78	1. `get_market_price --venue=kalshi --ticker=<ticker> --at_time=2026-05-01` for a single point-in-time price (both `yes`/`no` sides, 0-1).
79	2. `get_price_history --venue=kalshi --ticker=<ticker> --interval=1d` for the full series — same `{timestamp, price}` shape on either venue.
80
81	## Examples
82
83	Example 1: Today's games with prediction market odds
84	User says: "What NBA games are on today and what are the prediction market odds?"
85	Actions:
86	1. Call `get_todays_markets(sport="nba")`
87	Result: Unified dashboard with each game's ESPN info and Kalshi/Polymarket prices
88
89	Example 2: Cross-platform team search
90	User says: "Find

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markets

645installs27forks

View on GitHub

How to install markets?

machina-sports/sports-skills/markets

$npx -y skills add machina-sports/sports-skills --skill markets

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Markets Orchestration
2
3	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.
4
5	## Quick Start
6
7	```bash
8	sports-skills markets get_todays_markets --sport=nba
9	sports-skills markets search_entity --query="Lakers" --sport=nba
10	sports-skills markets compare_odds --sport=nba --event_id=401234567
11	sports-skills markets get_sport_markets --sport=nfl
12	sports-skills markets get_sport_schedule --sport=nba
13	sports-skills markets normalize_price --price=0.65 --source=polymarket
14	sports-skills markets evaluate_market --sport=nba --event_id=401234567
15	sports-skills markets match_markets --sport=mlb --date=2026-06-06
16	sports-skills markets get_market_price --venue=kalshi --ticker=KXMENWORLDCUP-26-FR
17	sports-skills markets get_price_history --venue=kalshi --ticker=KXMENWORLDCUP-26-FR --interval=1d
18	```
19
20	Python SDK:
21	```python
22	from sports_skills import markets
23
24	markets.get_todays_markets(sport="nba")
25	markets.search_entity(query="Lakers", sport="nba")
26	markets.compare_odds(sport="nba", event_id="401234567")
27	markets.get_sport_markets(sport="nfl")
28	markets.get_sport_schedule(sport="nba", date="2025-02-26")
29	markets.normalize_price(price=0.65, source="polymarket")
30	markets.evaluate_market(sport="nba", event_id="401234567")
31	markets.match_markets(sport="mlb", date="2026-06-06")
32	markets.get_market_price(venue="kalshi", ticker="KXMENWORLDCUP-26-FR", at_time="2026-05-01T12:00:00+00:00")
33	markets.get_price_history(venue="polymarket", token_id="<token_id>", interval="1h")
34	```
35
36	## CRITICAL: Before Any Query
37
38	CRITICAL: Before calling any orchestration command, verify:
39	- A `sport` code is provided for sport-aware commands (`get_todays_markets`, `compare_odds`, `get_sport_markets`, `evaluate_market`).
40	- Price sources are identified correctly before normalization: `espn` = American odds, `polymarket` = 0-1 probability, `kalshi` = 0-100 integer.
41
42	## Important Notes
43
44	- Sport context is passed through. `--sport=nba` maps automatically to the correct Polymarket sport code and Kalshi series ticker.
45	- Both platforms use sport-aware search. Polymarket uses `sport` → series_id; Kalshi uses `KXNBA`, `KXNFL`, etc.
46	- Prices are normalized. Everything is converted to implied probability for comparison.
47
48	## Workflows
49
50	### Today's NBA Dashboard
51
52	```bash
53	sports-skills markets get_todays_markets --sport=nba
54	```
55	Returns each game with ESPN info, DraftKings odds, matching Kalshi markets, and matching Polymarket markets.
56
57	### Find Arb on a Specific Game
58
59	1. Get the ESPN event ID: `get_sport_schedule --sport=nba`
60	2. Compare odds: `compare_odds --sport=nba --event_id=<id>`
61	3. If arbitrage detected, response includes allocation percentages and guaranteed ROI.
62
63	### Full Bet Evaluation
64
65	1. `evaluate_market --sport=nba --event_id=<id>`
66	2. Fetches ESPN odds and matching prediction market price
67	3. Pipes through `betting.evaluate_bet`: devig → edge → Kelly
68	4. Returns fair probability, edge, EV, Kelly fraction, and recommendation
69
70	### Same Game on Both Venues
71
72	1. `match_markets --sport=mlb --date=2026-06-06`
73	2. Each match pairs the Kalshi event (with market tickers) and the Polymarket event (with moneyline token IDs) for the same game — joined deterministically on date + team codes, fuzzy title match as fallback.
74	3. Feed `kalshi.market_tickers[i]` and `polymarket.markets[i].token_ids[j]` straight into `get_market_price` to compare prices.
75
76	### Price Movement Over Time
77
78	1. `get_market_price --venue=kalshi --ticker=<ticker> --at_time=2026-05-01` for a single point-in-time price (both `yes`/`no` sides, 0-1).
79	2. `get_price_history --venue=kalshi --ticker=<ticker> --interval=1d` for the full series — same `{timestamp, price}` shape on either venue.
80
81	## Examples
82
83	Example 1: Today's games with prediction market odds
84	User says: "What NBA games are on today and what are the prediction market odds?"
85	Actions:
86	1. Call `get_todays_markets(sport="nba")`
87	Result: Unified dashboard with each game's ESPN info and Kalshi/Polymarket prices
88
89	Example 2: Cross-platform team search
90	User says: "Find

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