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traffic-structure-analyzer

Analyze traffic composition and quality trends from Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and DSP/programmatic channels.

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安装方式

直接复制以下提示词,发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 traffic-structure-analyzer 技能。 若已安装,则直接安装 traffic-structure-analyzer 技能。

Overview

Skill Key
danyangliu-sandwichlab/traffic-structure-analyzer
Author
danyangliu-sandwichlab
Source Repo
openclaw/skills
Version
-
Source Path
skills/danyangliu-sandwichlab/traffic-structure-analyzer
Latest Commit SHA
7141b9e068f943b66ac8468de76c3e151742dd1f

Extracted Content

SKILL.md excerpt

# Ads Traffic Analysis

## Purpose
Core mission:
- traffic mix decomposition, trend anomaly diagnosis

This skill is specialized for advertising workflows and should output actionable plans rather than generic advice.

## When To Trigger
Use this skill when the user asks for:
- ad execution guidance tied to business outcomes
- growth decisions involving revenue, roas, cpa, or budget efficiency
- platform-level actions for: Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, DSP/programmatic
- this specific capability: traffic mix decomposition, trend anomaly diagnosis

High-signal keywords:
- ads, advertising, campaign, growth, revenue, profit
- roas, cpa, roi, budget, bidding, traffic, conversion, funnel
- meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp

## Input Contract
Required:
- question_or_report_goal
- metric_scope: KPI, dimensions, and date range
- data_source_scope

Optional:
- attribution_window
- benchmark_reference
- dashboard_filters
- confidence_threshold

## Output Contract
1. Metric Definition Clarification
2. Query Plan
3. Result Summary
4. Interpretation and Caveats
5. Decision Recommendation

## Workflow
1. Disambiguate metric definitions and time window.
2. Build query slices by platform, funnel, and audience.
3. Compute trend deltas and variance drivers.
4. Summarize findings with confidence level.
5. Propose concrete next actions.

## Decision Rules
- If metric definitions conflict, lock one canonical definition before analysis.
- If sample size is small, mark result as directional not conclusive.
- If attribution changes materially alter result, show both views.

## Platform Notes
Primary scope:
- Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, DSP/programmatic

Platform behavior guidance:
- Keep recommendations channel-aware; do not collapse all channels into one generic plan.
- For Meta and TikTok Ads, prioritize creative testing cadence.
- For Google Ads and Amazon Ads,...

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