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ads-qa-assistant

Answer ads operations questions quickly for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads workflows.

danyangliu-sandwichlab0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install danyangliu-sandwichlab/ads-qa-assistant

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

Ads Q&A Assistant

Purpose

Provide fast, reliable answers for common ads, growth, and performance questions.

When To Trigger

Use this skill when the user asks to:

  • run ads or execute advertising campaigns with clear operational next steps
  • grow revenue or profit, improve roas, reduce cpa, or optimize budget and bidding
  • analyze market, traffic, conversion funnel, and campaign performance signals
  • apply this specific capability: rapid Q&A, playbook lookup, issue triage

Typical trigger keywords:

  • ads, advertising, campaign, growth, strategy
  • revenue, profit, roi, roas, cpa
  • budget, bidding, traffic, conversion, funnel
  • meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp

Input Contract

Required:

  • business_goal: primary objective (sales, leads, traffic, awareness, retention)
  • scope: campaign range, market, timeline, and platform scope
  • context: URL, account context, historical performance, or request text

Optional:

  • kpi_targets: target cpa, roas, revenue, roi, ltv, cvr
  • constraints: budget, policy, brand rules, timeline, resource limits
  • platform_preference: preferred channels and priority
  • baseline_metrics: existing benchmark metrics

Output Contract

Return an execution-ready result with:

  1. Intent Summary (goal, KPI, scope)
  2. Findings (key observations and assumptions)
  3. Action Plan (prioritized next steps)
  4. Risks and Guardrails (what can break and what to monitor)
  5. Handoff Payload (structured fields for downstream skills)

Workflow

  1. Normalize request and confirm objective.
  2. Validate available inputs and list missing critical data.
  3. Analyze according to this skill focus: rapid Q&A, playbook lookup, issue triage.
  4. Generate prioritized actions tied to KPI impact.
  5. Add platform-specific notes and constraints.
  6. Emit a compact handoff payload for execution.

Decision Rules

  • If KPI is missing, infer likely primary KPI from goal and mark assumption explicitly.
  • If data quality is low, return conservati...

Source information

Source
github
Repository
openclaw/skills
Path
skills/danyangliu-sandwichlab/ads-qa-assistant
Version
—
Commit
051ee684c2ddef0bfd22c4fa195a8f661fbf9677
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# Ads Q&A Assistant

## Purpose
Provide fast, reliable answers for common ads, growth, and performance questions.

## When To Trigger
Use this skill when the user asks to:
- run ads or execute advertising campaigns with clear operational next steps
- grow revenue or profit, improve roas, reduce cpa, or optimize budget and bidding
- analyze market, traffic, conversion funnel, and campaign performance signals
- apply this specific capability: rapid Q&A, playbook lookup, issue triage

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

## Input Contract
Required:
- business_goal: primary objective (sales, leads, traffic, awareness, retention)
- scope: campaign range, market, timeline, and platform scope
- context: URL, account context, historical performance, or request text

Optional:
- kpi_targets: target cpa, roas, revenue, roi, ltv, cvr
- constraints: budget, policy, brand rules, timeline, resource limits
- platform_preference: preferred channels and priority
- baseline_metrics: existing benchmark metrics

## Output Contract
Return an execution-ready result with:
1. Intent Summary (goal, KPI, scope)
2. Findings (key observations and assumptions)
3. Action Plan (prioritized next steps)
4. Risks and Guardrails (what can break and what to monitor)
5. Handoff Payload (structured fields for downstream skills)

## Workflow
1. Normalize request and confirm objective.
2. Validate available inputs and list missing critical data.
3. Analyze according to this skill focus: rapid Q&A, playbook lookup, issue triage.
4. Generate prioritized actions tied to KPI impact.
5. Add platform-specific notes and constraints.
6. Emit a compact handoff payload for execution.

## Decision Rules
- If KPI is missing, infer likely primary KPI from goal and mark assumption explicitly.
- If data quality is low, return conservati...

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