Gateway to the Machina Sports premium platform — packaged agent workflows ("templates"), licensed real-time data, betting odds, and zero-latency live streams.

MITAuto-check passedAgent Workflows

Install Machina

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

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

GitHub CLI
$ gh skill install machina-sports/sports-skills machina --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/machina .claude/skills/machina && 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/

Facts

Skill name
machina
GitHub stars
243
Token cost
~2.2k tokens
SKILL.md length
859 words
Files
1
Skills in repo
23
Repo updated
First seen
Licence
MIT

At a glance

Gateway to the Machina Sports premium platform — packaged agent workflows ("templates"), licensed real-time data, betting odds, and zero-latency live streams.

  • Works in 3 steps: Install the CLI → Authenticate → Select a project (required)
  • : the user asks for live odds
  • SKILL.md covers Quick Start, CRITICAL: Before Any Premium…, When to Use and Setup & Installation, plus 6 more sections
  • Calls pipx, python and uv; reaches raw.githubusercontent.com; needs MACHINA_API_TOKEN

What it does

Machina is an agent skill from machina-sports/sports-skills. Gateway to the Machina Sports premium platform — packaged agent workflows ("templates"), licensed real-time data, betting odds, and zero-latency live streams. This skill is prompt-only: it shells out to the separate machina-cli binary and routes the agent to a per-project Machina MCP server. Use when: the user asks for live odds, real-time telemetry, zero-latency match states, sub-second tick streams, packaged sports workflows (e.g., "Build a Bundesliga podcast bot", "Create a Polymarket arbitrage engine"), or…

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering MCP servers. It works with Model Context Protocol 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

  • : the user asks for live odds
  • Real-time telemetry
  • Zero-latency match states
  • Sub-second tick streams

Example prompts

  • “templates”
  • “Build a Bundesliga podcast bot”
  • “Create a Polymarket arbitrage engine”
  • “/machina”

Requirements

  • Python 3
  • A credential in MACHINA_API_TOKEN

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Install the CLI
  2. Authenticate
  3. Select a project (required)

What it can do on your machine

Read from SKILL.md and the folder at commit 09eb7e8. 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

    Shell commands in SKILL.md call:

    • pipx
    • python
    • uv
    • curl
    • bash
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • raw.githubusercontent.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • MACHINA_API_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Machina loads about 2.2k tokens when it runs. Until then it costs about 208 tokens; SKILL.md has 859 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~208
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from machina-sports/sports-skills at commit 09eb7e8, republished under its MIT licence (© machina-sports). 859 words, ~2,174 tokens.

Download SKILL.mdSave it as .claude/skills/machina/SKILL.md (or your agent's skills folder).
name
machina
description
Gateway to the Machina Sports premium platform — packaged agent workflows ("templates"), licensed real-time data, betting odds, and zero-latency live streams. This skill is prompt-only: it shells out to the separate `machina-cli` binary and routes the agent to a per-project Machina MCP server. Use when: the user asks for live odds, real-time telemetry, zero-latency match states, sub-second tick streams, packaged sports workflows (e.g., "Build a Bundesliga podcast bot", "Create a Polymarket arbitrage engine"), or when the open-source sports-skills are rate-limited or insufficient for the task. Don't use when: the user wants snapshot data from public APIs — use the sport-specific skill (nfl-data, polymarket, markets, …). Don't use to fetch data through raw HTTP — use the Machina MCP server, not a `requests` call.
license
MIT
metadata.author
machina-sports
metadata.version
0.3.0

Machina Sports Intelligence Layer

Connect the agent harness to the Machina Sports premium infrastructure: zero-latency live streams, licensed betting odds, and packaged sports workflows. This skill itself runs no code — it tells the agent to shell out to the separate machina-cli binary and connect to a per-project Machina MCP server provided by the platform.

Quick Start

bash
# 1. Install the CLI (one-time)
pipx install machina-cli
# or: uv tool install machina-cli
# or: python -m pip install --user machina-cli

# 2. Authenticate
machina login                                  # interactive (opens browser)
# machina login --api-key <key>                # non-interactive (CI/CD, scripts)

# 3. Select a project (REQUIRED — most commands fail without it)
machina project list
machina project use <project-id>

# 4. Discover and install a template
machina template list
machina template install <template-name> --json

# 5. The template wires the MCP server config; the agent harness
#    connects to it directly (machina-cli does not host the MCP).

CRITICAL: Before Any Premium Call

Before calling any machina <subcommand>, verify:

  • machina-cli is installed — check with which machina or machina version.
  • The user is authenticated — machina auth whoami returns a user.
  • A project is selected — machina project use <id> has been run at least once.

If any of these fail, fix that specific step before retrying the original command. Do not loop on the same failing command.

When to Use

  • The user asks for live odds, real-time telemetry, or zero-latency match states.
  • The user wants a pre-configured sports workflow (e.g., "Build a Bundesliga podcast bot", "Create a Polymarket arbitrage engine").
  • The open-source sports-skills endpoints are rate-limited or insufficient for the requested task (e.g., sub-second tick streams, licensed feeds, proprietary projections).
  • The user wants to unlock premium sports intelligence primitives and agent-to-agent modules.

Setup & Installation

1. Install the CLI
bash
pipx install machina-cli
# or
uv tool install machina-cli
# or
python -m pip install --user machina-cli

Run this in the developer's terminal if you have permission, or ask them to run it.

Inspect-before-run fallback

If a shell installer is required by the user's environment, never pipe it directly to a shell by default. Download it, inspect it, then run it only after the user approves:

bash
curl -fsSL https://raw.githubusercontent.com/machina-sports/machina-cli/main/install.sh -o /tmp/machina-install.sh
less /tmp/machina-install.sh
bash /tmp/machina-install.sh
2. Authenticate
bash
machina login                                  # interactive (opens browser)
machina login --api-key <project-api-key>      # non-interactive
machina login --with-credentials               # username/password

API keys are scoped per project. Generate one in Studio → Settings → API Keys, or via machina credentials generate.

3. Select a project (required)

Most premium commands (templates, workflows, credentials, connectors) require a project context. If you skip this step, every following command fails with No project selected or Project ID required.

bash
machina project list                # show projects under the current org
machina project use <project-id>    # set the default project
machina project status              # confirm

Discovering & Installing Agent Templates

Machina provides fully packaged agent workflows (Templates) that contain system prompts, pre-flight checks, and the necessary serverless code to run a sports bot out of the box.

bash
machina template list                                  # browse available templates
machina template install <template-path> --json        # provision + download

machina template install provisions cloud resources via API and downloads the local agent context into the current workspace. Use --json for structured output that the agent can parse.

Deploying Custom Agent Workflows

If you modify a template or create a new sports workflow locally, push it directly to the Machina Cloud Pod:

bash
machina template push ./<your-custom-folder>

This zips the local workspace, validates _install.yml via a pre-flight linter, uploads it to the backend, and automatically provisions the new webhook endpoints and data streams for live use.

Live Data via Machina MCP

The Machina platform provides a per-project MCP (Model Context Protocol) server that streams live data, betting odds, and zero-latency feeds. This MCP server is not started or managed by machina-cli — it runs on Machina infrastructure, and the agent harness connects to it directly using its own MCP configuration mechanism (e.g., .claude/mcp.json for Claude Code).

How it fits together:

  1. machina template install <name> provisions the server-side workflow and returns the MCP URL and any required headers in its JSON output.
  2. The agent harness's MCP config is updated to point to that URL.
  3. The agent calls MCP tools to read live streams. Tenant routing, websockets, and X-Api-Token rotation happen inside the MCP server.

Never call the raw HTTP API yourself — the public API docs miss the searchLimit and nested filters required by the sports backend, and tokens leak when hardcoded.

Show full SKILL.md (305 more words)Show less

Common Errors & Recovery

Error messageCauseRecovery
command not found: machinaCLI not installedpip install machina-cli
Not authenticated. Run \machina login` first.`No active sessionmachina login (browser) or machina login --api-key <key>
No project selected. Run \machina project use <id>` first.`Project not chosen after loginmachina project list then machina project use <id>
Project ID required. Set default or use --project.Same as aboveSame as above
Template install succeeds but agent can't reach MCPHarness has not reloaded MCP configAsk the user to restart / reload their agent harness so it re-reads the MCP config

If an auth whoami returns a user but commands still fail with Not authenticated, the token has expired — run machina login again.

Commands that DO NOT exist — never call these

  • python -m sports_skills machina ... — this skill has no CLI module under sports-skills. Shell out to machina-cli directly.
  • machina mcp start / machina mcp connect — there is no mcp subcommand. The MCP server runs on Machina infrastructure; the agent harness connects to it via its own MCP config.
  • machina sports ... — does not exist. Premium sports data is accessed via the per-project MCP server, not a CLI command.
  • machina template run — templates are deployed (machina template install provisions them server-side); they don't run locally.

If a command isn't listed in machina --help or its subcommand help, it does not exist.

Failures Overcome

  • Raw API Key Leaks: Never instruct the user to hardcode a MACHINA_API_TOKEN in their source code if using the MCP setup. The CLI handles shared context securely.
  • Pagination and Filtering Errors: Public API docs often miss the searchLimit and nested filters required by the sports backend. Installing a template automatically injects the correct workflow.json config.
  • Lost Project Context: Most premium commands silently fail without a default project. Always run machina project use <id> after a fresh login.

© machina-sports, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/machina of machina-sports/sports-skills.

Open the folder on GitHubat commit 09eb7e8

Compare with similar skills

Machina 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.

Machina compared with similar skills
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Polymarket Tennislivetennisapi/livetennisapi-mcp152—~3kAutomated safety check: PassMIT
PolyvisionLeoYeAI/openclaw-master-skills2.2k—~4.1kAutomated safety check: PassMIT
MCP Server Builderanthropics/skills180k63 repos~2.3kAutomated safety check: PassApache-2.0
MCP Server BuildershareAI-lab/learn-claude-code78k4 repos~1.2kAutomated safety check: PassMIT

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Categories

Questions about Machina

What does Machina do?

Gateway to the Machina Sports premium platform — packaged agent workflows ("templates"), licensed real-time data, betting odds, and zero-latency live streams. Machina is an agent skill from machina-sports/sports-skills. Gateway to the Machina Sports premium platform — packaged agent workflows ("templates"), licensed real-time data, betting odds, and zero-latency live streams.

When should I use Machina?

Machina fits situations like: : the user asks for live odds; real-time telemetry; zero-latency match states; sub-second tick streams.

How do I install Machina in Claude Code?

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

How do I install Machina in Codex?

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

Can I use Machina 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 machina -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/machina, .gemini/skills/machina, .github/skills/machina and .opencode/skills/machina in your project.

What does Machina need to run?

Going by SKILL.md and its folder, Machina needs the command-line tools its instructions call (pipx, python, uv, curl, bash and pip) and credentials named MACHINA_API_TOKEN. Our summary lists: Python 3; A credential in MACHINA_API_TOKEN.

Does Machina access the network?

SKILL.md names 1 domain. In commands or code: raw.githubusercontent.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Machina 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. Review the folder before installing.

What licence does Machina use?

Machina 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 Machina use?

About 2.2k tokens (SKILL.md is roughly 8.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Machina?

Skills that share tags, products or a category with Machina: Blockrun Debug (BlockRunAI/blockrun-mcp, 391 stars), Polymarket Tennis (livetennisapi/livetennisapi-mcp, 152 stars), Polyvision (LeoYeAI/openclaw-master-skills, 2.2k stars) and MCP Server Builder (anthropics/skills, 180k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Machina?

machina-sports (a GitHub organization) maintains it in machina-sports/sports-skills, which has 243 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 5, 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.