# Tina的代码日记 (@26281379332) on xiaohongshu

- id: koinon:creator:xiaohongshu_26281379332
- url: https://koinonlink.com/kol/xiaohongshu/26281379332
- schema_version: 1.4

## Identity
- platform: xiaohongshu
- handle: 26281379332
- platform_url: https://www.xiaohongshu.com/user/profile/67222b7f000000001c018151
- country: China
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 2800
- posts_observed: 1
- verified: false
- size_tier: nano

## Engagement
- status: not_collected
- status_note: Engagement has not been collected for this creator yet. This is a gap in our collection, NOT a statement that the creator has no engagement. Follower count is known, so it is measurable.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: software
- subcategory: devtools
- category_confidence: 0.9
- category_source: derived_from_recent_content
- topics: Python Excel自动化与数据处理, 微信自动化脚本与消息回复, 办公自动化脚本三步教学, 零基础Python实用技巧, 合同生成、邮件发送等批量脚本
- bio: 10年软件开发，专注用Python简化办公难题！
每天分享：Excel自动化｜报表一键生成｜文件批量处理
🌟 适合零基础 | 实用技巧 | 职场效率利器 🌟
领取代码/脚本，私信“666”

## Audience (inferred)
- status: present
- description: office professionals, administrative staff, and data handlers who are beginners looking to use Python to automate Excel tasks and repetitive work
- roles: automation
- seniority: learner
- pain_points: Time-consuming and tedious manual work like Excel data filtering and report generation, Need to automate office tasks but lack programming skills, Low efficiency in manually replying to WeChat messages and processing files in bulk, Lack of practical Python automation examples and ready-to-use code samples
- posts_analysed: 31
- confidence: 0.75

## Commercial (inferred)
- audience_buyer_fit: 0.8
- promotion_intent: 0.7
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 58
- authenticity_basis: platform_default
- credibility_score: 37
- flagged_for_review: false
- koinon_bd_grade: A — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [xiaohongshu_26281379332#68813378] #python[话题]#  #技术分享[话题]# #办公自动化[话题]# 三步走，让你轻松使用python对你的Excel进行数据筛选 #跟我学编程[话题]# #程序员[话题]# #办公技巧[话题]# / 如何用python来操作微信自动发消息呢？ 纯干货教学！包会系列！ (https://www.xiaohongshu.com/user/profile/67222b7f000000001c018151)
- [xiaohongshu_26281379332#1b27a506] #python[话题]# #编程[话题]# #计算机[话题]# #大学生[话题]# #微信[话题]# #程序员[话题]# #学习[话 / Python动态爱心  当代码遇上浪漫，一颗颗粒子也能组成爱的形状~ #编程[话题]# #代码[话题]# #Python[话题]# #大学生[话题]# #学习[话题]# #干货分享[话题]# #办公技 / 简单三步，教你做一个自动脚本 / 三步教你做自动化脚本，重复工作立马搞定#软件开发[话题]# #自动脚本[话题]##脚本定制[话题]##编程[话题]##重复操作[话题]# #剪辑工具[话题]# #小程序制作[话题]#
- [xiaohongshu_26281379332#3d05c1e1] #软件设计与开发[话题]# #开发[话题]# #编程[话题]# #办公技巧[话题]# #excel技巧[话题]# #python[话题]# #程序员[话题]# #学习[ / Python 处理办公自动化的十大场景！#编程[话题]# #学习[话题]# #知识分享[话题]# #大学生[话题]# #办公技巧[话题]# #编程[话题]# #软件设计与开发[话题]# #办公自动化[ / 这个我愿称之为年度伟大发现 / 【Python自动化】教你用Python实现微信自动化回复 代码简单，零基础也能轻松制作运行，附源码#python[话题]# #python编程[话
- [xiaohongshu_26281379332#d1e37635] #手机技巧[话题]# #干货分享[话题]# #涨知识[

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.75, freshness_days=55, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.75, freshness_days=55, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.75, freshness_days=55, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=55, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=55, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=108, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.25, freshness_days=55, method=Fixed value 58, pending engagement collection. Not a measurement. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=108, method=llm_partner_fit_classifier + fit_score >= 0.5 => A; >= 0.35 => B; else C. authenticity is not an input. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=108, method=platform_profile

## Freshness
- profile_checked_days_ago: 108
- content_analysed_days_ago: 55
- audience_updated_days_ago: 55

## AI retrieval
- indexing_requests: 9
- user_triggered_requests: 1
- last_user_triggered_day: 2026-09-01
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=xiaohongshu_26281379332
- Request removal: https://koinonlink.com/claim?k=xiaohongshu_26281379332
- Terms: https://koinonlink.com/for-ai