人行征信开 工🔥 报单提供 名字-身份证-手机号 工作日1-3天回货 包含房贷、车贷、信用卡、网贷记录 人民银行征信报告有哪些欠款记录就体现哪些记录 用途:婚前调查,相亲对象,男女朋友,奔着结婚目的。还有一些合作伙伴, 一定要查一下,现在很多人都有网贷,不要被那些假大款骗了 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC

Channel
好旺人工(付费)查询样板
@Sgkminad
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
1,851subscribers
+0 since we began measuring on 31 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
Register entry
| Telegram ID | -1001779866415 |
|---|---|
| Type | Channel |
| Username | @Sgkminad |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 31 August 2026 |
| Last confirmed live | 31 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/Sgkminad |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 31 Aug 2026, 04:15 | 1,851 | no change |
| 31 Aug 2026, 04:00 | 1,851 | first reading |
Engagement
18 posts held, back to 7 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 6.28%
- avg views ÷ 1,851 subscribers
- Avg views / post
- 116
- 16 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 18
- of 18 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
| Window | Rolling 30 days · latest post in window 31 August 2026 |
|---|---|
| Posts held | 18 (7 August 2026 – 31 August 2026) |
| Views total | 1,861 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 31 Aug 2026, 04:15 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
- Photos
- 13
Lifetime counters from Telegram’s own channel header, read 31 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Recent posts
带定位链接手机轨迹(价格不贵) 直接带定位链接(直接点就出位置) 地址更精准(街道/村) 出单率更高 回单格式:文档 只出三个月内的 20-30条 够五条出单 凌晨发车上车 隔天回 已和快递外卖对比过多单 手机轨迹 识别基于WIFI IP GPS APP软件 基站等 多重识别方式 结果直接导出未经过人为编辑,所以个别位置会有误导识别现象,产生经纬跳跃 结果以总体较多出现的位置为准。 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC
抖音号——反查绑定手机身份证🪪稳定出货中。未出不收费🫶
三网运营商定位 稳定出货中。 30分钟以内回单 锁定目标当前位置 认准靠谱商家·避免低价假单 出必准 出单率高 (包售后) (开机出当前位置)(关机出关机前位置)靠谱 精准 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC
民政婚姻带结离 正常当天隔天回最稳的板子。 目前最真最稳无遗漏民政局版本婚姻,空单的是民政局没有登记, 没有离婚记录但离婚的是没有过民政局系统,法院判离。 工作日当天15.00前报单的当天回,之后隔天回 ————————————————————————————— 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC
带定位链接手机轨迹(价格不贵) 直接带定位链接(直接点就出位置) 地址更精准(街道/村) 出单率更高 回单格式:文档 只出三个月内的 20-30条 够五条出单 凌晨发车上车 隔天回 已和快递外卖对比过多单 手机轨迹 识别基于WIFI IP GPS APP软件 基站等 多重识别方式 结果直接导出未经过人为编辑,所以个别位置会有误导识别现象,产生经纬跳跃 结果以总体较多出现的位置为准。 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC
公网一体卡公司车辆 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC
带定位链接手机轨迹(价格不贵) 直接带定位链接(直接点就出位置) 地址更精准(街道/村) 出单率更高 回单格式:文档 只出三个月内的 20-30条 够五条出单 凌晨发车上车 隔天回 已和快递外卖对比过多单 手机轨迹 识别基于WIFI IP GPS APP软件 基站等 多重识别方式 结果直接导出未经过人为编辑,所以个别位置会有误导识别现象,产生经纬跳跃 结果以总体较多出现的位置为准。 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC
选择好旺.你的好助手 帮您解决一切问题 高效.信誉 一站式服务⚠️⚠️⚠️⚠️⚠️ 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC
全国房产,稳定出货。🫡🫡🫡 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC
长期招聘内部合作伙伴(各种内部工作人员) 公安 · 银行 · 运营商 · 民政局 · 房管局 · 快递客户等能接触到查询系统 🌎(最好拥有某些系统的全国查询权限) 云搜部门普通、高级权限 → 月保底30万起 反诈高级权限 → 月保底30万起 👮♂️ 网安部门权限 → 月保底30万起 🏫 法院执行部门 → 月保底20万起 🏦 银行柜台高级权限 → 月保底20万起 📦 各类快递全国权限 → 月保底10万起 👩❤️👨 民政部门普通权限 → 月保底10万起 害怕出事?害怕系统留痕迹? 我们能提供的安全保障(来自合作7年+的老民警经验) 完整去除公安水印、系统日志痕迹、查询记录 内部老同志亲传的系统漏洞利用 & 痕迹清理方法 突发事件应急预案(被约谈/查岗/异常告警时的标准话术 & 脱身流程) 现金变现方法 现金变现全链路:USDT混币 → 暗网币 → 多层桥…
三网运营商定位 稳定出货中。 30分钟以内回单 锁定目标当前位置 认准靠谱商家·避免低价假单 出必准 出单率高 (包售后) (开机出当前位置)(关机出关机前位置)靠谱 精准 认准(好旺)👉 @HaoWangDaiCha 机器人👉 @HaoWangDaiChaBottetris_bot 永久频道 👉 @HaoWangDC
Showing the 12 most recent of 18 posts we hold for @Sgkminad. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank
Citation-graph rank — 398,767 of 1,629,518 entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 31 August 2026 — this entry's latest reading, not the date you are reading this.
“好旺人工(付费)查询样板” (@Sgkminad), 1,851 subscribers as measured 31 August 2026. Telegram Register, tgregister.com/channel/Sgkminad.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.