Agent skill

Kalshi

by machina-sports in machina-sports/sports-skills

Kalshi prediction markets — events, series, markets, trades, and candlestick data.

Install Kalshi

skills CLI

$ npx skills add machina-sports/sports-skills --skill kalshi -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install machina-sports/sports-skills kalshi --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/machina-sports/sports-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/kalshi .claude/skills/kalshi && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "kalshi" agent skill from https://github.com/machina-sports/sports-skills/tree/main/skills/kalshi into .claude/skills/kalshi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kalshi", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/machina-sports/sports-skills/tree/main/skills/kalshi

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add machina-sports/sports-skills --skill kalshi -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install machina-sports/sports-skills kalshi --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/machina-sports/sports-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/kalshi .agents/skills/kalshi && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "kalshi" agent skill from https://github.com/machina-sports/sports-skills/tree/main/skills/kalshi into .agents/skills/kalshi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kalshi", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add machina-sports/sports-skills --skill kalshi -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install machina-sports/sports-skills kalshi --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/machina-sports/sports-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/kalshi .cursor/skills/kalshi && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "kalshi" agent skill from https://github.com/machina-sports/sports-skills/tree/main/skills/kalshi into .cursor/skills/kalshi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kalshi", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/machina-sports/sports-skills.git --path skills/kalshi

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add machina-sports/sports-skills --skill kalshi -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install machina-sports/sports-skills kalshi --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/machina-sports/sports-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/kalshi .gemini/skills/kalshi && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "kalshi" agent skill from https://github.com/machina-sports/sports-skills/tree/main/skills/kalshi into .gemini/skills/kalshi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kalshi", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install machina-sports/sports-skills kalshi

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add machina-sports/sports-skills --skill kalshi -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/machina-sports/sports-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/kalshi .github/skills/kalshi && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "kalshi" agent skill from https://github.com/machina-sports/sports-skills/tree/main/skills/kalshi into .github/skills/kalshi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kalshi", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add machina-sports/sports-skills --skill kalshi -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install machina-sports/sports-skills kalshi --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/machina-sports/sports-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/kalshi .opencode/skills/kalshi && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "kalshi" agent skill from https://github.com/machina-sports/sports-skills/tree/main/skills/kalshi into .opencode/skills/kalshi/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kalshi", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: kalshi
GitHub stars: 245
Token cost: ~1.9k tokens
SKILL.md length: 710 words
Files: 6 (incl. scripts, references)
Skills in repo: 23
Repo updated: Oct 10, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Kalshi prediction markets — events, series, markets, trades, and candlestick data.

Works in 3 steps: search_markets --sport=nba — finds all… → Optionally add --query="Lakers" to… → Results include yes_bid, no_bid, volume…
: user asks about Kalshi-specific markets
SKILL.md covers Quick Start, CRITICAL: Before Any Query, Important Notes and Workflows, plus 4 more sections
Runs Shell scripts from its folder

What it does

Kalshi is an agent skill from machina-sports/sports-skills. Kalshi prediction markets — events, series, markets, trades, and candlestick data. Public API, no auth required for reads. US-regulated exchange (CFTC). Covers football (EPL, UCL, La Liga), basketball, baseball, tennis, NFL, hockey event contracts. Use when: user asks about Kalshi-specific markets, event contracts, CFTC-regulated prediction markets, or candlestick/OHLC price history on sports outcomes. Don't use when: user asks about actual match results, scores, or statistics — use the sport-specific skill…

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `references/api-reference.md`, `references/api.md` and `references/commands.md`).

It sits in Data & Analytics, covering Statistics. It works with Kalshi and Polymarket. The repository describes itself as: Open-source agent skills for live sports data and prediction markets. Football, F1, Kalshi, Polymarket. Zero API keys. SKILL.md format. The licence is MIT.

When your agent uses it

: user asks about Kalshi-specific markets
Event contracts
CFTC-regulated prediction markets
Candlestick/OHLC price history on sports outcomes

Example prompts

“t use for general”
“/kalshi”

Requirements

Python 3
A Bash shell

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

search_markets --sport=nba — finds all open NBA markets.
Optionally add --query="Lakers" to filter by keyword.
Results include yes_bid, no_bid, volume for each market.

What it can do on your machine

Read from SKILL.md and the folder at commit 0420a7c. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Shell), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Kalshi loads about 1.9k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 238 tokens; SKILL.md has 710 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~238
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from machina-sports/sports-skills at commit 0420a7c, republished under its MIT licence (© machina-sports). 710 words, ~1,876 tokens.

Download SKILL.mdSave it as .claude/skills/kalshi/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.

name: kalshi
description: Kalshi prediction markets — events, series, markets, trades, and candlestick data. Public API, no auth required for reads. US-regulated exchange (CFTC). Covers football (EPL, UCL, La Liga), basketball, baseball, tennis, NFL, hockey event contracts. Use when: user asks about Kalshi-specific markets, event contracts, CFTC-regulated prediction markets, or candlestick/OHLC price history on sports outcomes. Don't use when: user asks about actual match results, scores, or statistics — use the sport-specific skill: football-data (soccer), nfl-data (NFL), nba-data (NBA), wnba-data (WNBA), nhl-data (NHL), mlb-data (MLB), tennis-data (tennis), golf-data (golf), cricket-data (cricket), cfb-data (college football), cbb-data (college basketball), or fastf1 (F1). Don't use for general "who will win" questions unless Kalshi is specifically mentioned — try polymarket first (broader sports coverage). Don't use for news — use sports-news instead.
license: MIT
metadata.author: machina-sports
metadata.version: 0.2.0

Kalshi — Prediction Markets

Before writing queries, consult references/api-reference.md for sport codes, series tickers, and command parameters.

Quick Start

Prefer the CLI — it avoids Python import path issues:

bash

sports-skills kalshi search_markets --sport=nba
sports-skills kalshi get_todays_events --sport=nba
sports-skills kalshi get_sports_config
sports-skills kalshi get_markets --series_ticker=KXNBA --status=open

Python SDK (alternative):

python

from sports_skills import kalshi

kalshi.search_markets(sport='nba')
kalshi.search_markets(sport='nba', query='Lakers')
kalshi.get_todays_events(sport='nba')
kalshi.get_sports_config()
kalshi.get_markets(series_ticker="KXNBA", status="open")

CRITICAL: Before Any Query

CRITICAL: Before calling any market endpoint, verify:

The sport parameter is always passed to search_markets and get_todays_events for single-game markets.
Prices are on a 0-100 integer scale (20 = 20% implied probability) — do not treat as American odds.
status="open" is used when querying markets to exclude settled/closed markets.

Without the sport parameter:

WRONG: search_markets(query="Leeds")           → 0 results
RIGHT: search_markets(sport='epl', query='Leeds') → returns all Leeds markets

Important Notes

On Kalshi, "Football" = NFL. For football/soccer (EPL, La Liga, etc.), use sport codes: epl, ucl, laliga, bundesliga, seriea, ligue1, mls, worldcup.
Formula 1 uses sport code f1 (drivers'/constructors' champion plus per-Grand-Prix race, podium, pole, fastest-lap, head-to-head and sprint series).
Market tickers are not always <event_ticker>-<suffix>. Kalshi mints some with a different stem, e.g. KXATP-26-SHA sits inside event KXATP-26USO (2026 US Open men's singles) next to KXATP-26USO-SIN. That is Kalshi's real ticker: pass it verbatim to get_market, and group markets by their event_ticker field, never by parsing the ticker.
Prices are probabilities. A last_price of 20 means 20% implied probability. Scale is 0-100 (not 0-1 like Polymarket).
Always use status="open" when querying markets, otherwise results include settled/closed markets.
Shared interface with Polymarket: search_markets(sport=...), get_todays_events(sport=...), and get_sports_config() work the same way on both platforms.

Workflows

Sport Market Search (Recommended)

search_markets --sport=nba — finds all open NBA markets.
Optionally add --query="Lakers" to filter by keyword.
Results include yes_bid, no_bid, volume for each market.

Today's Events

get_todays_events --sport=nba — open events with nested markets.
Present events with prices (price = implied probability, 0-100 scale).

Futures Market Check

get_markets --series_ticker=<ticker> --status=open
Sort by last_price descending.
Present top contenders with probability and volume.

Market Price History

Get market ticker from search_markets --sport=nba.
get_market_candlesticks --series_ticker=<s> --ticker=<t> --start_ts=<start> --end_ts=<end> --period_interval=60
Present OHLC with volume.

Commands

See references/api-reference.md for the full command list with parameters.

Command	Description
`get_sports_config`	Available sport codes and series tickers
`get_todays_events`	Today's events for a sport with nested markets
`search_markets`	Find markets by sport and/or keyword
`get_esports_odds`	Esports markets (cs2/lol/dota2): prices in cents (0-100) plus `implied_probability` (0-1) and `decimal_odds`
`get_markets`	Market listing (raw API)
`get_event`	Event details
`get_market`	Market details
`get_trades`	Recent trades
`get_market_candlesticks`	OHLC price history

Show full SKILL.md (333 more words)Show less

Examples

Example 1: NBA market search User says: "What NBA markets are on Kalshi?" Actions:

Call search_markets(sport='nba') Result: All open NBA markets with yes/no prices and volume

Example 2: EPL game markets User says: "Show me Leeds vs Man City odds on Kalshi" Actions:

Call search_markets(sport='epl', query='Leeds') Result: Leeds EPL markets across all EPL series with prices and volume

Example 3: Today's EPL events User says: "What EPL games are available on Kalshi?" Actions:

Call get_todays_events(sport='epl') Result: Today's EPL events with nested markets

Example 4: Champions League futures User says: "Who will win the Champions League?" Actions:

Call search_markets(sport='ucl') or get_markets(series_ticker="KXUCL", status="open")
Sort by last_price descending (price = implied probability) Result: Top UCL contenders with yes_sub_title, last_price (%), and volume

Example 5: Market price history User says: "Show me the price history for this NBA game" Actions:

Get market ticker from search_markets(sport='nba')
Call get_market_candlesticks(series_ticker="KXNBA", ticker="...", start_ts=..., end_ts=..., period_interval=60) Result: OHLC price data with volume

Commands that DO NOT exist — never call these

~~get_odds~~ — does not exist. Use search_markets or get_markets to find market prices.
~~get_team_schedule~~ — does not exist. Kalshi has markets, not schedules. Use the sport-specific skill for schedules.
~~get_scores~~ / ~~get_results~~ — does not exist. Kalshi is a prediction market. Use the sport-specific skill.

If a command is not listed in references/api-reference.md, it does not exist.

Troubleshooting

Error: search_markets returns 0 results Cause: The sport parameter is missing — without it, search only returns high-volume futures and misses single-game markets Solution: Always pass sport='<code>' to search_markets. Check references/api-reference.md for valid sport codes

Error: Markets returned include settled/expired contracts Cause: status parameter is not set Solution: Always pass status="open" to filter to open markets only

Error: Series ticker returns no results Cause: The series ticker may be incorrect or have no open markets Solution: Call get_series_list() to discover available tickers, or check references/series-tickers.md

Error: Football/soccer markets not found when searching "Football" Cause: On Kalshi, "Football" refers to NFL — soccer uses league-specific codes Solution: Use sport='epl', sport='ucl', sport='laliga', etc. for soccer leagues

Files

SKILL.md and 5 other files (scripts, references) in skills/kalshi of machina-sports/sports-skills.

SKILL.md
references/api-reference.md
references/api.md
references/commands.md
references/series-tickers.md
scripts/validate_params.sh

Open the folder on GitHubat commit 0420a7c

Compare with similar skills

Kalshi next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Kalshi compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Kalshi this skillmachina-sports/sports-skills	245	—	~1.9k	Automated safety check: Pass	MIT	today
Forecast AnalysisNVIDIA-AI-Blueprints/deep-researcher-agent	886	—	~820	Automated safety check: Pass	Apache-2.0	yesterday
Prediction MarketsBlockRunAI/blockrun-mcp	391	—	~3.7k	Automated safety check: Pass	MIT	3 days ago
Predexon Prediction Market DataBlockRunAI/ClawRouter	6.6k	—	~4.7k	Automated safety check: Pass	MIT	6 days ago
Surf Crypto Data APIBlockRunAI/blockrun-mcp	391	—	~1.7k	Automated safety check: Pass	MIT	3 days ago
Sandbox Benchvercel/next.js	143k	—	~4.1k	Automated safety check: Pass	MIT	today

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Questions about Kalshi

What does Kalshi do?

Kalshi prediction markets — events, series, markets, trades, and candlestick data. Kalshi is an agent skill from machina-sports/sports-skills. Kalshi prediction markets — events, series, markets, trades, and candlestick data.

When should I use Kalshi?

Kalshi fits situations like: : user asks about Kalshi-specific markets; event contracts; CFTC-regulated prediction markets; candlestick/OHLC price history on sports outcomes.

How do I install Kalshi in Claude Code?

Run `npx skills add machina-sports/sports-skills --skill kalshi -a claude-code`. Or copy the skill folder (skills/kalshi in machina-sports/sports-skills) into .claude/skills/kalshi in your project. Claude Code loads it when a task matches its description.

How do I install Kalshi in Codex?

Run `npx skills add machina-sports/sports-skills --skill kalshi -a codex`. Or copy the skill folder (skills/kalshi in machina-sports/sports-skills) into .agents/skills/kalshi in your project. Codex loads it when a task matches its description.

Can I use Kalshi in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add machina-sports/sports-skills --skill kalshi -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/kalshi, .gemini/skills/kalshi, .github/skills/kalshi and .opencode/skills/kalshi in your project.

What does Kalshi need to run?

Going by SKILL.md and its folder, Kalshi needs a shell for the scripts in its folder. Our summary lists: Python 3; A Bash shell.

Does Kalshi access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Kalshi safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Kalshi use?

Kalshi is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Kalshi use?

About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2k tokens, read only when the agent opens those files.

What are the alternatives to Kalshi?

Skills that share tags, products or a category with Kalshi: Forecast Analysis (NVIDIA-AI-Blueprints/deep-researcher-agent, 886 stars), Prediction Markets (BlockRunAI/blockrun-mcp, 391 stars), Predexon Prediction Market Data (BlockRunAI/ClawRouter, 6.6k stars) and Surf Crypto Data API (BlockRunAI/blockrun-mcp, 391 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Kalshi?

machina-sports (a GitHub organization) maintains it in machina-sports/sports-skills, which has 245 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 10, 2026.

Source: machina-sports/sports-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Kalshi

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Kalshi — Prediction Markets

Quick Start

CRITICAL: Before Any Query

Important Notes

Workflows

Sport Market Search (Recommended)

Today's Events

Futures Market Check

Market Price History

Commands

Examples

Commands that DO NOT exist — never call these

Troubleshooting

Files

Compare with similar skills

Similar skills

More from machina-sports/sports-skills

Related

Questions about Kalshi