A synchronization tool that fetches daily WakaTime-compatible coding statistics from Wakapi and saves them as structured local CSV files.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install wakapi-sync-skill
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install wakapi-sync-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The wakapi-sync utility is designed for developers who want to maintain a local, portable history of their coding productivity. By leveraging Openclaw Skills, this tool interfaces with any Wakapi-compatible instance to retrieve daily summaries including total active time, project-specific metrics, and language usage.
Instead of relying solely on a web interface, this skill converts your technical activity into structured data, allowing for private data ownership, custom dashboarding, and long-term trend analysis. It acts as a bridge between your automated time-tracking server and your local filesystem, ensuring your productivity data is always accessible in a standard format.
To deploy this skill within your environment, ensure you are running Node.js 18 or higher. Configure the required environment variables to point to your instance:
# Required Configuration
export WAKAPI_URL="https://your-wakapi-instance.com"
export WAKAPI_API_KEY="your_secret_api_key"
export WAKAPI_OUT_DIR="/path/to/your/storage"
# Optional: Customize the amount of data captured
export WAKAPI_TOP_N_PROJECTS=10
export WAKAPI_TOP_N_LANGUAGES=10
Execute the sync process with the following command:
node scripts/wakapi-daily-summary.mjs
The skill organizes data into three distinct CSV files with the following structures:
date: The log date (YYYY-MM-DD).total_seconds / total_hours: Cumulative time spent coding.projects_count / languages_count: Variety of work performed.rank: Order by time spent.project: Name of the specific project.seconds / hours / percent: Duration and relative weight of the project.language: The programming language detected.rank / seconds / hours / percent: Usage metrics per language.Loading
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