Daredevil NBA Sports Data for Openclaw

A specialized skill for fetching real-time NBA sports data and generating AI-powered game analyses via paid x402 requests.

project-aeris-disaster-agent
v1.0.0
Feb 21, 2026
0
0
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install nba-data-analytics

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install nba-data-analytics using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Daredevil NBA Sports Data?

The Daredevil NBA Sports Data skill enables AI agents to access a wealth of professional basketball information directly from the Daredevil seller. By integrating this into Openclaw Skills, developers can provide their agents with the ability to query everything from live scores and play-by-play updates to detailed team rosters and injury reports. The skill operates on a pay-per-request model using the x402 protocol, ensuring a decentralized and fair exchange of value for high-quality sports data.

Beyond simple data retrieval, this skill is designed for deep synthesis. Agents can combine raw data points—such as standings, recent boxscores, and injury lists—to generate sophisticated predictions and game opinions. This makes it an essential tool for building sports betting assistants, fantasy basketball advisors, or automated sports news bots within the Openclaw Skills ecosystem.

Daredevil NBA Sports Data Use Cases

  • Retrieving live NBA scores and play-by-play updates during active games.
  • Checking upcoming team schedules and next-game matchups for specific franchises.
  • Generating AI-driven game predictions and matchup analyses based on current standings and injury reports.
  • Accessing detailed player statistics and team rosters for fantasy basketball research.
  • Monitoring league-wide injury reports to stay updated on player availability.

How Daredevil NBA Sports Data Works

  1. The agent identifies a need for NBA data based on a user query (e.g., "Who is winning the Lakers game?").
  2. The agent sends an initial POST request to the /v1/data endpoint with the required parameters like dataType and teamName.
  3. The server responds with a 402 Payment Required status, providing the necessary x402 payment details.
  4. The agent's wallet signs the payment payload on the Base network (Sepolia or Mainnet).
  5. The agent retries the request with the signed x402 payment headers.
  6. Upon successful payment, the server returns the requested NBA data in a structured JSON format.
  7. If an analysis was requested, the agent's LLM synthesizes the raw data into a human-readable response.

Daredevil NBA Sports Data Setup

To use this skill, ensure you have an x402-compatible environment. You can use the following Node.js setup to handle paid requests:

npm install @x402/core

Configure your agent to point to the Base URL: https://daredevil-acp-seller-production.up.railway.app. Ensure your wallet has funds on Base Mainnet or Base Sepolia to cover the small per-query fees required by Openclaw Skills.

Daredevil NBA Sports Data Data Schema & Taxonomy

The skill returns a standard JSON response containing the data type and the result string.

Field Type Description
dataType String The type of data requested (e.g., standings, boxscore).
result JSON String The actual payload containing NBA statistics or schedules.
timestamp ISO8601 The time the data was retrieved.
gameStatus String (Optional) Current status for live games.

Supported data types include schedule, next_game, boxscore, live_score, play_by_play, standings, injuries, team_roster, and player_stats.

Daredevil NBA Sports Data Advanced Features

  • Multi-data synthesis: Combine multiple API calls (standings + injuries + next_game) for comprehensive AI-generated predictions.
  • Support for both Base Mainnet and Base Sepolia testnet for flexible development.
  • Real-time play-by-play streaming capabilities for live game tracking.
  • Flexible filtering by team aliases (e.g., LAL, BOS) or full team names.
  • Automated x402 payment handling for seamless integration into autonomous agent workflows.

SKILL.md


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