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xintu1314/content-boom-monitor

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Codex Skill for Xiaohongshu and Douyin keepword and contact-account monitoring with Just One API and Feishu Base

Overview

It collects open content data through Just One API, completes standardization, weighting, account relative performance and priority content screening, and settles the results to the flybook multi-dimensional forms. The goal is to transform the search keywords into a stable data flow, with only a small number of outcomes of concern. - At the same time, monitor small red books and shivering keywords; - Monitor the recent work assigned to the account numbers; - Harmonize the work, author and interactive fields of the different platforms; - Heavy by Platform + Production ID; Calculating Platform Differentiated Interactive Values; - Calculate Relative Performance by Middle Number of Account History R; - Mark T1 Potential / T2 Demolition / T3 Disorder Level, etc.; - Generate monitoring briefs containing key word performance, account abnormalities, Top 10 and data restrictions; - Enable Codex to automatically open up to 10 candidates in production mode with an evidentiary boundary of AI; - Preview and release to the Flying Book Content Library; - Read key words and account numbers in flying books and minimize human input. For example, by entering an AI tool, the system allows a little red book to search for close to seven days of content by heat, tremor and a little bit of praise, and then to return to the highest-priority candidate for the key word to calculate the interactive value based on the acclaims, collections, comments and sharing that have been obtained. It is not responsible for disseminating new topics and does not package the results of a search into a web-based blast certification. Key-word results are marked as "key-word-explosive candidates " , no historical baseline of accounts is required; account number results are used to calculate relative performance using the same account-based baseline. The two sets of judgement rules are not interchangeable. Stable and remnant links are completed by process; content that requires semantic understanding is disassembled to AI; compliance with business is ultimately judged. 1. Read undisused and unsuspensed accounts from the Flying Book "Record Account" form; 2. Identify small red books or shivering from the home page link and interpret platform accounts ID; 3. Call for an account interface with a maximum of 8 recent entries per account; 4. Convert the works of the two platforms into unified fields; 5. Reload with Platform + work ID: New works are prepared and new ones are ready to be updated; 6. Calculate the interactive value of each work; obtain R by comparing this work with the median of the interactive value of other work available on the same account line with R; 8. Generate the report in order of the T1/T2/T3 grade, and include it in the flying book. For example, a median of 100 for other works in the current cycle and 850 for a new one, R = 8.5. When it reaches the absolute interactive evidentiary threshold at the same time, it is marked as a T3 phenomenon level, giving priority to a reset。

Overview (machine translated)

A Cordex Skill for monitoring ** Little Red Book / Dancing Keyword** with ** Account Account Number**.

It collects open content data through Just One API, completes standardization, weighting, account relative performance and priority content screening, and settles the results to the flybook multi-dimensional forms.

The goal is to transform the search keywords for ablaze and the targeting of account number abnormalities into stable data processes, allowing only a small number of outcomes of concern to be addressed.

What can I do

  • The monitoring of small red books and quivering keywords;
  • Monitoring of recent work on the assigned account number;
  • Harmonization of works, authors and interactive fields from different platforms;
  • To weigh 平台 + 作品ID across sources;
  • Calculate the Platform ’ s differential interactive values;
  • Calculate relative performance using historical medians of accounts [[T1];
  • Mark [[T2] peer review level;
  • Generating surveillance briefs with keyword representations, account anomalies, Top 10 and data limitations;
  • Allow Codex to automatically decomposete up to 10 candidates at the level of evidence in production patterns;
  • Preview and release to the collection of flying books;
  • Read the key words and account page in the flyer ’ s book to minimize human input.

Two surveillance engines

Question to answer. Question to main purpose |-|-|-|-| ♪ Keyword monitoring ♪ ♪ Searching for the keyword, which notes/videos are the candidates for the bomb? • Return high-interactive content associated with keywords for disassembly and choice Which one of these accounts is clearly above normal? ♪ Discovering little account number anomalies and avoiding only absolute traffic ♪

For example, by entering [[T3], the system allows a small red book to search for close to seven days of content by heat, shivering and a little groaning, and then returns the candidate for the blast that deserves the highest priority under the keyword based on the acclaims, collections, comments and sharing. It is not responsible for disseminating new topics and does not package the results of a search into a web-based blast certification.

Key-word results are marked as “key word boom candidates” and no historical baseline of accounts is required; account number results are used to calculate relative performance using the same account basis [[T4]. The two sets of judgement rules are not interchangeable.

Workflow

Stable and remnant links are completed by process; content that requires semantic understanding is disassembled to AI; compliance with business is ultimately judged.

How the monitoring of the account numbers works

Each operation carries out the following definitive link:

  1. Read undefended and unsuspensed accounts from the “reciprocal account” form;
  2. Identification of small red books or shivering from links to the home page and deciphering the Platform account ID;
  3. Call the account file interface with a maximum of 8 articles per account;
  4. Conversion of the work of the two platforms into a unified field;
  5. Use [(T5] to weigh: new works are ready to be added and existing ones are ready to be updated;
  6. Calculation of the interactive value of each work;
  7. Comparison of this work with the median of the interactive value of other work available in the current account cycle received [(T6];
  8. By T1/T2/T3 classification, produce reports and write flying books.

For example, the median number of interactions for other works in a given account cycle is 100 and for a new work is 850, the [T7]。

This page was translated automatically. Technical details may differ from the original.

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Install

npx skillfish add xintu1314/content-boom-monitor
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