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AlvaroLaraFF
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strava-sync

Sync Strava activity data into a local SQLite cache via Python CLI.

Updated Apr 12, 2026
Search Tags:#analytics#cli#sqlite#sync#etl#data-ingestion#strava
One-click install
npx skills add https://github.com/AlvaroLaraFF/strava-coach --skill strava-sync
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: strava-sync
Source: https://github.com/AlvaroLaraFF/strava-coach/tree/main/.claude/skills/strava-sync
Command: npx skills add https://github.com/AlvaroLaraFF/strava-coach --skill strava-sync

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Pull Strava activity data into a local SQLite cache for offline analytics.

Core Features & Use Cases

  • Supports three sync levels (summary, details, streams) to progressively enrich the local dataset for reporting and modeling.
  • Enables downstream skills to operate on either lightweight summaries or full activity payloads, including per-second streams.
  • Works with a Python CLI, allowing scripted orchestrations and automation in training pipelines.

Quick Start

Run the Strava sync CLI to pull the latest activities into your local cache and prepare data for analysis.

Frequently Asked Questions about strava-sync

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I sync Strava activity data to a local SQLite database for offline analytics?▼

To sync Strava activity data for offline analytics, you can use a Python CLI to pull your activities into a local SQLite cache. This allows you to run queries and reporting without needing continuous API access.

What levels of Strava data can I pull into a local SQLite cache?▼

You can pull three levels of Strava data into a local SQLite cache: summary, details, and streams. This multi-level ingestion progressively enriches your dataset for diverse reporting and modeling needs.

Can I use a Python CLI to automate Strava data ingestion in training pipelines?▼

Yes, you can use a Python CLI to automate Strava data ingestion in training pipelines. The CLI interface supports scripted orchestrations, allowing you to schedule and execute syncs automatically within your workflows.

Does this Strava sync tool support ingesting per-second activity streams locally?▼

Yes, the Strava sync tool supports ingesting per-second activity streams locally. By pulling stream data into your SQLite cache, downstream skills can operate on full activity payloads for granular analysis.

What is the best way to prepare Strava data for local modeling and reporting?▼

The best way to prepare Strava data for local modeling is to ingest it into a SQLite cache using a multi-level sync workflow. This provides safe defaults and allows downstream operations on either lightweight summaries or full payloads.

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