A comprehensive golf performance management skill for tracking rounds, handicaps, and tailored improvement strategies.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install golf
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install golf 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 Golf?
The Golf skill is a sophisticated performance tracking tool designed for Openclaw Skills users who want to transform their AI agent into a digital caddie and data-driven coach. By maintaining a structured local memory of every round, club distance, and course detail, the skill enables precise handicap management and personalized feedback. It moves beyond basic scorekeeping by analyzing specific play patterns—such as miss tendencies and putting efficiency—to offer strategic advice that is unique to the user's history and equipment bag.
This skill provides a centralized hub for all golfing data, allowing your AI to identify technical weaknesses and suggest tailored practice routines based on your actual performance on the course. Whether you are a scratch golfer or a high-handicapper, it provides the technical infrastructure to turn raw round data into actionable improvement plans.
Golf Use Cases
- Logging detailed round statistics including total scores, Greens in Regulation (GIR), Fairways in Regulation (FIR), and putts.
- Managing a personalized club bag with verified yardages for every iron, wood, and wedge.
- Automatically calculating and tracking handicap index progress using official differential formulas.
- Identifying consistent miss patterns like slices or hooks to receive targeted swing and practice recommendations.
- Storing and retrieving course-specific notes to prepare for future rounds at previously played locations.
How Golf Works
- The AI agent initializes the local environment by establishing the
~/golf/directory structure for persistent data storage. - It references the
memory.mdfile to understand the player's current baseline, including handicap, club distances, and specific goals. - After a game, the user provides round details which the agent logs into a structured table within
rounds.md. - The agent calculates the handicap differential for the round using the provided course rating and slope.
- It analyzes historical logs to identify trends, such as performance in scoring zones or short-game efficiency.
- The agent generates personalized practice suggestions, specifically addressing the weaknesses identified in the most recent rounds.
Golf Setup
To install the Golf skill within your Openclaw Skills environment, execute the following command:
clawhub install golf
Once installed, initialize your tracking files in your home directory:
mkdir -p ~/golf/archive
touch ~/golf/memory.md ~/golf/rounds.md ~/golf/courses.md
Use the memory-template.md provided with the skill to populate your initial club distances and current handicap index.
Golf Data Schema & Taxonomy
The skill organizes golf data using a tiered memory system within the ~/golf/ directory:
| Component | File | Description |
|---|---|---|
| Hot Memory | memory.md |
Stores current handicap, club distances, goals, and active focus areas. |
| Warm Memory | rounds.md |
A detailed log of all rounds including dates, courses, tees, and key stats. |
| Course Library | courses.md |
A repository for saved course details, ratings, slopes, and strategic notes. |
| Cold Storage | archive/ |
A directory for archiving data from past seasons to maintain performance. |
Golf Advanced Features
- Automated handicap differential calculation using the standard formula: (Score - Rating) x 113 / Slope.
- Cross-skill integration with other Openclaw Skills such as
planfor golf trips andremindfor managing tee times. - Detailed pattern recognition that identifies consistent misses and scoring trends across par 3s, 4s, and 5s.
- Condition-aware recommendations that factor in external variables like wind, altitude, and turf conditions.
- Multi-seasonal archiving capabilities to track long-term skill acquisition and performance trends over years of play.
SKILL.md
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