# bannzai/Gecco

Simply highlight items for your tutorial walkthrough, written in Swift

Repository: https://github.com/bannzai/Gecco
Canonical: https://ross.abutalabs.com/products/bannzai-gecco
Language: Swift
License: MIT
License Family: permissive
Last push: 2024-12-22T04:17:09+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3883, "days_push": 619, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1882, forks 167 (observed 2026-08-28T04:05:48.731356+00:00)

## What it is
Gecco is a Swift library for iOS that highlights UI elements with spotlight overlays to guide users through tutorial walkthroughs. It provides a SpotlightViewController with oval, rectangle, and rounded-rectangle spotlight shapes plus delegate hooks for customization.

## Use cases
- highlight a button during an app onboarding tour
- create coach marks for a first-launch tutorial
- dim the screen and spotlight a specific UI element
- build step-by-step feature walkthroughs in an iOS app
- add spotlight overlays with oval or rounded rect shapes

## When to choose
- you need a lightweight UIKit-based spotlight/coach-mark overlay for iOS
- you want simple Swift integration via CocoaPods with customizable spotlight shapes

## When to avoid
- you need onboarding tours on Android or cross-platform apps
- you want a full-featured onboarding framework with screens, videos, or analytics

## Facets
- artifact type: library
- maturity: maintenance
- function: ui-components, animation
- domain: mobile-development, developer-tools, education
- platform: -
- tags: spotlight-overlay, tutorial-walkthrough, onboarding, coach-marks, uikit, ios, swift, mobile

## Member repositories
- bannzai/Gecco (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:48.731356+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:13:47.217085+00:00, confidence not recorded.
  - readme: https://github.com/bannzai/Gecco (fetched 2026-08-28T04:05:48.731356+00:00, sha 134dfb7dc167)
- Data as of 2026-08-30T08:39:29.467469+00:00.