Skip to main content

content-flagging

Establishes a comprehensive framework for evaluating, classifying, and disposing of flagged content within the platform's content moderation ecosystem.

설치로 이동

소스 정보

저장소
vivekhaldar/proceda
최근 소스 활동
2026년 3월 22일 05:59
감지된 SKILL.md 언어
영어
스타
16
포크
2

설치 방법

기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.

소스 파일 검토

설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.

파일 탐색기
2 개 파일

SKILL.md 표시 중

SKILL.md
소스 지침 · 읽기 전용 미리보기
name
content-flagging
description
Establishes a comprehensive framework for evaluating, classifying, and disposing of flagged content within the platform's content moderation ecosystem.
required_tools
["calculateBotProbabilityIndex","calculate_user_trust_score","calculateContentSeverityIndex","determineFinalDecision"]
### Step 1: Calculate Bot Probability Index Utilize the `calculateBotProbabilityIndex` tool to assess the likelihood of automated activity, incorporating device consistency validation. This tool will take the following inputs: - `userid` from content metadata - `is_possible_bot` (initial bot assessment) - `Captcha_tries` (number of captcha attempts) - `device_type` from device information - `os` (operating system) from device information - `browser` (browser specification) from device information The outputs will be the `bot_probability_index` and the `device_consistency_score`. ### Step 2: Calculate User Trust Score Compute the user's overall trust coefficient using the `calculate_user_trust_score` tool, factoring in historical behavior, geographic risk, and device consistency. This tool requires: - `userid` from content metadata - `NumberofPreviousPosts` (user's total post count) - `CountofFlaggedPosts` (count of user's previously flagged posts) - `Latitude` and `Longitude` from content metadata (geolocation coordinates) - `bot_probability_index` obtained from Step 1 - `device_consistency_score` obtained from Step 1 The output will be the `user_trust_score`. ### Step 3: Assess Content Severity Determine the severity of the content violation using the `calculateContentSeverityIndex` tool, integrating primary and secondary violation analyses. Provide the following inputs: - `content_id` from content metadata - `PrimaryViolationType` from violation data - `SecondaryViolationType` from violation data (if applicable) - `PrimaryViolation_Confidence` from violation data - `SecondaryViolation_Confidence` from violation data (if applicable) The output will be the `content_severity_index`. ### Step 4: Determine Final Content Disposition Utilize the `determineFinalDecision` tool to combine all moderation metrics and establish the final action for the flagged content. This tool needs: - `content_id` from content metadata - `user_trust_score` obtained from Step 2 - `content_severity_index` obtained from Step 3 - `bot_probability_index` obtained from Step 1 - `NumberofPreviousPosts` (user's total post count) - `CountofFlaggedPosts` (count of user's previously flagged posts) The tool will output the final disposition (e.g., `removed`, `warning`, `user_banned`, `allowed`). [APPROVAL REQUIRED]
GitHub에서 보기