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ryanfrigo/kalshi-ai-trading-bot

The honest edge layer for Kalshi prediction markets - an agent-native toolkit (CLI, MCP server, Claude skill) that measures whether you actually beat the book instead of claiming it.

Python ◇ agentic-ai MIT
★650STARS
⑂205FORKS
!35ISSUES
🏆#10,850GLOBAL RANK
🔥4DAYS TRENDING
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⚡ Executive Summary & Quick Facts

Authoritative Source

kalshi-ai-trading-bot is kalshi-ai-trading-bot is an open-source project written in Python: The honest edge layer for Kalshi prediction markets - an agent-native toolkit (CLI, MCP server, Claude skill) that measures whether you actually beat the book instead of claiming it..

Direct Citation for AI & Research:
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), ryanfrigo/kalshi-ai-trading-bot has accumulated 650 GitHub stars and 205 forks. It is written in Python, licensed under MIT, and ranks #10,850 globally. It is actively maintained with the latest commit recorded on Nov 9, 2026.”
Repository ryanfrigo/kalshi-ai-trading-bot ↗
Primary Category agentic ai
Language & Stack Python
Software License MIT
Community Traction ★ 650 stars · ⑂ 205 forks · #10,850 globally
Maintenance ● Active (Last commit: Nov 9, 2026) · 35 open issues
Target Audience Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.

🛡️ Repository Maintenance & Health Audit (2026)

Health Score: 97/100 · Grade A+
✅
Is kalshi-ai-trading-bot actively maintained in 2026?
Verdict: Actively Maintained & Highly Recommended

Yes, kalshi-ai-trading-bot is actively maintained. Continuous telemetry recorded the last code commit on Nov 9, 2026 (4 days ago). Supported by 650 stars and 205 community forks, this repository holds a calculated health index of 97/100, reflecting very active (commits within last 14 days) and healthy issue cadence.

Commit Recency
Nov 9, 2026
4 days since last push
Issue Backlog
35 Open Issues
Healthy Issue Cadence
Community Backing
205 Forks
650 Stars Recorded
Software License
MIT
Permissive & Inspectable

Star History

Continuous Observations
Interactive star growth chart for ryanfrigo/kalshi-ai-trading-bot
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Momentum

+16

STARS · LAST 30 DAYS

1

PER DAY

#1,521

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+7+16+90
Per day111
Forks gained+1+4+10

kalshi-ai-trading-bot gained 16 stars in the last 30 days, about 1 a day, and now has 650. It is about 1 year old and has averaged roughly 650 stars a year. It ranks #1,521 among Python repositories and #10,850 across all languages on GitHubRepo.

Trending Record

kalshi-ai-trading-bot has maintained a continuous presence across global trending indexes, peaking at #13425. Below is the 30-day activity profile:

💡 Overview

kalshi-ai-trading-bot is an open-source project written in Python: The honest edge layer for Kalshi prediction markets - an agent-native toolkit (CLI, MCP server, Claude skill) that measures whether you actually beat the book instead of claiming it.

Engineered for speed, consistency, and developer ease, it solves common hurdles in agentic-ai, ai-agents, ai-trading. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Python for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ pip install kalshi-ai-trading-bot

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

kalshi-ai-trading-bot coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with kalshi-ai-trading-bot.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install kalshi-ai-trading-bot using your package manager: `pip install kalshi-ai-trading-bot`

2

Initialize your project workspace or configuration file for kalshi-ai-trading-bot.

3

Import kalshi-ai-trading-bot into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `kalshi-ai-trading-bot --help` to verify successful setup.

👍 Strengths

Active community backing with 650 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in Python for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Python and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

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👥 Who Should Use This

Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

ryanfrigo/kalshi-ai-trading-bot is currently ranked #10,850 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#10,841 sebaslogen/resaca Kotlin ★ 651 Compare ↗
#10,841 pumPCin/HMAL Kotlin ★ 651 Compare ↗
#10,841 themidnightgospel/Imposter C# ★ 651 Compare ↗
#10,841 qhkm/zeptoclaw Rust ★ 651 Compare ↗
#10,841 moonbai-studio/tungsten-edge Swift ★ 651 Compare ↗
#10,850 ryanfrigo/kalshi-ai-trading-bot This Project Python ★ 650
#10,850 mjul/docjure Clojure ★ 650 Compare ↗
#10,850 editorconfig-checker/editorconfig-checker Go ★ 650 Compare ↗
#10,850 open-edge-platform/dlstreamer C++ ★ 650 Compare ↗
#10,850 smallnest/ringbuffer Go ★ 650 Compare ↗
#10,850 cvut/qtrvsim C++ ★ 650 Compare ↗
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Frequently Asked Questions

What does kalshi-ai-trading-bot do? +

The honest edge layer for Kalshi prediction markets - an agent-native toolkit (CLI, MCP server, Claude skill) that measures whether you actually beat the book instead of claiming it.

Is kalshi-ai-trading-bot actively maintained in 2026? +

Yes, kalshi-ai-trading-bot is actively maintained. The latest code push was recorded on Nov 9, 2026 (4 days ago). It holds a calculated Maintenance Health Score of 97/100 (A+ rating) with 650 stars and 35 open issues.

What language is kalshi-ai-trading-bot written in? +

The primary language is Python. Topics include: agentic-ai, ai-agents, ai-trading, automated-trading, edge-measurement.

How many stars does kalshi-ai-trading-bot have? +

kalshi-ai-trading-bot has 650 stars and 205 forks on GitHub.

How does kalshi-ai-trading-bot rank among GitHub repositories? +

With 650 stars, ryanfrigo/kalshi-ai-trading-bot is ranked #10,850 globally across all repositories tracked on GitHubRepo and #1,521 among Python projects.

What license is kalshi-ai-trading-bot distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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