auto-target-tracker

Name: auto-target-tracker
Availability: InStock
Author: ashesoftheundead

Extract progress metrics from images into structured markdown goal journals.

Updated Jul 9, 2026

Search Tags:#automation #productivity #goal-tracking #habit-tracker #vlm #data-logging

Ready to run

npx skills add https://github.com/AshesOfTheUndead/rezurxlib --skill auto-target-tracker-ashesoftheundead

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: auto-target-tracker
Source: https://github.com/AshesOfTheUndead/rezurxlib/tree/main/skills/auto-target-tracker
Command: npx skills add https://github.com/AshesOfTheUndead/rezurxlib --skill auto-target-tracker-ashesoftheundead

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the friction of manual progress logging by automatically detecting goal-related images and extracting key metrics to update your daily journals.

Core Features & Use Cases

Intelligent VLM Recognition: Automatically identifies learning notes, fitness records, work progress, and habit streaks from images.
Structured Logging: Parses extracted data into clean, readable tables and summaries for your daily notes.
Use Case: After a gym session, simply upload a photo of your workout log; the skill will extract your sets, reps, and weights, calculate your total volume, and record it into your fitness journal.

Quick Start

Upload a photo of your progress or notes and ask the assistant to record the details into your daily target journal.

Frequently Asked Questions about auto-target-tracker

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

FAQPage Schema

How do I automate goal tracking and progress logging from images?▼

Automate goal tracking by uploading progress photos, which Vision Language Models parse to extract key metrics and update your daily journals with structured markdown logs.

Can I use a VLM to extract fitness records and workout logs from a photo?▼

Yes, a VLM can extract fitness records from photos, parsing details like sets, reps, and weights, calculating total volume, and recording it directly into your fitness journal.

What is the best way to log daily progress from visual data into a markdown journal?▼

The best way to log progress from visual data is using VLM recognition to automatically identify metrics from your images and parse them into clean, readable tables for markdown journals.

Does automated habit tracking work with learning notes and work progress images?▼

Automated habit tracking works with learning notes and work progress images by intelligently recognizing diverse visual data domains and structuring the extracted metrics into daily logs.

Do I need local file editing capabilities to maintain persistent progress records?▼

Yes, local file editing capabilities are required to maintain accurate, persistent progress records, allowing the skill to update your personal goal journals with structured markdown logs.

What types of visual data can be parsed into structured logs for personal goals?▼

Visual data types including learning notes, fitness records, work progress, and habit streaks can be parsed into structured markdown tables and summaries for personal goal journals.