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// Skill profile

Ads Traffic Analysis

Name: Ads Traffic Analysis
Author: danyangliu-sandwichlab

name: traffic-structure-analyzer

by danyangliu-sandwichlab · published 2026-03-22

数据处理自动化任务加密货币

Total installs

Stars

★ 0

Last updated

2026-03

// Install command

$ claw add gh:danyangliu-sandwichlab/danyangliu-sandwichlab-traffic-structure-analyzer

View on GitHub

// Full documentation

---

name: traffic-structure-analyzer

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

---

# 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, prioritize demand-capture and query/listing intent.

For DSP/programmatic, prioritize audience control and frequency governance.

Constraints And Guardrails

Never fabricate metrics or policy outcomes.

Separate observed facts from assumptions.

Use measurable language for each proposed action.

Include at least one rollback or stop-loss condition when spend risk exists.

Failure Handling And Escalation

If critical inputs are missing, ask for only the minimum required fields.

If platform constraints conflict, show trade-offs and a safe default.

If confidence is low, mark it explicitly and provide a validation checklist.

If high-risk issues appear (policy, billing, tracking breakage), escalate with a structured handoff payload.

Code Examples

Query Spec Example

metric: roas

dimensions: [platform, campaign]

date_range: last_30d

Result Schema

{

"platform": "Meta",

"spend": 12000,

"revenue": 42000,

"roas": 3.5

}

Examples

Example 1: Daily report automation

Input:

Need 9AM daily summary for key campaigns

KPI: spend, cpa, roas

Output focus:

report schema

anomaly highlights

top next actions

Example 2: Attribution window comparison

Input:

1d click vs 7d click disagreement

Decision needed for budget shift

Output focus:

side-by-side metric table

interpretation caveats

decision recommendation

Example 3: Traffic structure diagnosis

Input:

Revenue flat but traffic rising

Suspected quality decline

Output focus:

source mix decomposition

quality signal changes

corrective action plan

Quality Checklist

[ ] Required sections are complete and non-empty

[ ] Trigger keywords include at least 3 registry terms

[ ] Input and output contracts are operationally testable

[ ] Workflow and decision rules are capability-specific

[ ] Platform references are explicit and concrete

[ ] At least 3 practical examples are included

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