5.0
4 条评分
★★★★★
2023年6月22日
2021年9月5日
更新内容
v1.9Thank you For using The Seven Sisters Frequencies App! Updates to Version 2.0.7 Include: BIG SALE Bug Fixes Image Updates
应用信息
- 开发者
- Seven7Sisters Prophecy LLC
- 分类
- Music
- 价格
- 免费
- 版本
- 1.9
- App ID
- 1546912372
简介
The Seven Sisters are revered throughout the world as a beacon of light and creation for humanity. Many cultures have celebrated these celestial star beings including the Celts and Hawaiians who call them makali’i, the Maori and aboriginal Australians who call them Matariki, the Persians and Arabs who call them Thurayya, the Chinese who call them Mao, to the Hindu they are known as Kartika. To the Quechua, the Japanese, the Maya, the Aztec, the Sioux, the Kiowa and the Cherokee they are celebrated.\n\nAll over the world this small little star cluster is revered and holds great mystery and power. This prophecy speaks of a Stargate in the pleiades that the 144000 future avatars travelled through from another galaxy to bring highly advanced intelligence to earth. the 7 sisters intelligence reflects itself into human forms to help raise the vibration of humanity and accelerate consciousness in all, Nurturing the Mother principle in the whole womb of creation. Birthing new vibrations of interstellar thought into the morphogenetic web that connects all through a golden thread. Weaving a beautiful star blanket throughout the rainbow people. The seven sisters are reflecting data in the form of creation light streams into this digital tool to catalyze a deep collective creative awakening and a higher understanding of the unified field. The gifts that are activated by the frequencies of the seven sisters are Creativity, Pineal gland awakening, access to the akashic records, time travel, inter dimensional viewing, precognition, telepathy, Quantum Teleportation and more. For the best Experience Please Listen With Headphones ONIESHA LLC ©2023 QFTNEXUS www.oniesha.com Contact: interface@qftnexus.com Privacy Policy http://www.oniesha.com/7-sisters.html
下载量预测
预估总下载量
4
低 / 月
5
预估 / 月
10
高 / 月
基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。
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