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danyangliu-sandwichlab

Ads Q&A Assistant

by danyangliu · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install ads-qa-assistant
Description
Answer ads operations questions quickly for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads workflows.
README (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 conservative recommendations and required follow-up checks.
  • If platform context is unclear, provide platform-agnostic baseline plus channel variants.
  • If policy or account risk appears high, require compliance or account checks before scale.
  • If urgency is high and uncertainty is high, prioritize reversible low-risk actions first.

Platform Notes

Primary platform scope:

  • Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads

Guidance:

  • Use platform-specific recommendations only when evidence supports them.
  • Keep naming explicit: Meta, Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, DSP.
  • If request is cross-channel, provide channel order and budget split rationale.

Constraints And Guardrails

  • Do not fabricate data, performance outcomes, or policy approvals.
  • Separate facts from assumptions in every recommendation.
  • Keep recommendations measurable and tied to explicit KPIs.
  • Avoid irreversible changes without validation checkpoints.

Failure Handling And Escalation

  • If required inputs are missing, request concise follow-up fields before final recommendation.
  • If data sources conflict, report conflict and provide a safe default path.
  • If request implies unsupported account actions, escalate with an exact handoff checklist.
  • If compliance risk is detected, route to Ads Compliance Review before launch.

Examples

Example 1: Meta ecommerce optimization

Input:

  • Goal: sales growth with lower cpa
  • Platform: Meta (Facebook/Instagram)

Output focus:

  • top blockers
  • prioritized fixes
  • week-1 actions and expected KPI movement

Example 2: Google Ads lead generation

Input:

  • Goal: improve lead quality and stabilize cpl
  • Platform: Google Ads

Output focus:

  • search intent structure
  • budget and bidding adjustments
  • lead-routing handoff fields

Example 3: TikTok plus YouTube scale test

Input:

  • Goal: scale traffic while protecting roas
  • Platforms: TikTok Ads and YouTube Ads

Output focus:

  • test matrix
  • risk guardrails
  • monitoring and rollback triggers

Quality Checklist

  • All required sections are present
  • At least 3 registry keywords appear in When To Trigger
  • Input and output contracts are explicit and actionable
  • Workflow is step-based and execution ready
  • Platform references are concrete when applicable
  • At least 3 examples are included
Usage Guidance
This skill appears coherent and low-risk, but exercise normal caution: do not paste actual account credentials or sensitive raw data into the skill; validate recommendations before applying changes to live campaigns; if the skill will be integrated into automation or handed off to other skills, verify those downstream skills separately and ensure any real account actions require explicit, credentialed approval. If you need stronger assurance, ask the publisher for a homepage or source repository and test the skill on non-production examples first.
Capability Analysis
Type: OpenClaw Skill Name: ads-qa-assistant Version: 1.0.0 The skill bundle is benign. The `SKILL.md` clearly defines the purpose, workflow, input/output contracts, and includes strong guardrails such as 'Do not fabricate data' and 'Avoid irreversible changes without validation checkpoints'. There are no instructions for data exfiltration, malicious execution, persistence, or any form of harmful prompt injection against the agent. All content is aligned with providing Q&A assistance for ads operations, and the 'execution' mentioned refers to generating a structured payload for downstream skills, not arbitrary command execution.
Capability Assessment
Purpose & Capability
The name/description (ads Q&A across Meta, Google, TikTok, YouTube, Amazon, Shopify) matches the SKILL.md content. The skill asks for business goals, scope, and campaign context — all reasonable and proportional for ad recommendations. It does not request unrelated access (cloud creds, system files, etc.).
Instruction Scope
SKILL.md contains operational guidance, input/output contracts, decision rules, platform notes, guardrails, and examples. It does not instruct the agent to read local files, access environment variables, call arbitrary external endpoints, or exfiltrate data. The 'handoff payload' is a structured data output intended for downstream execution, not an external transmission instruction.
Install Mechanism
No install spec and no code files — this is instruction-only, so nothing is written to disk or installed. This is the lowest-risk install profile.
Credentials
The skill declares no required environment variables, credentials, or config paths. That is proportional for an advisory Q&A skill which should not need account-level secrets to produce recommendations.
Persistence & Privilege
always is false and there are no installation or self-modifying steps. The skill does not request permanent presence or elevated privileges and does not modify other skills or system-wide settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ads-qa-assistant
  3. After installation, invoke the skill by name or use /ads-qa-assistant
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
ads-qa-assistant 1.0.0 - Initial release providing rapid Q&A and playbook lookup for Meta, Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads workflows. - Standardizes input and output contracts for actionable and measurable ad performance recommendations. - Includes decision rules for KPI inference, risk handling, and platform-agnostic guidance. - Features clear workflow steps, escalation paths, and real-world ad ops use case examples. - Implements guardrails against data fabrication and compliance risks.
Metadata
Slug ads-qa-assistant
Version 1.0.0
License
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Ads Q&A Assistant?

Answer ads operations questions quickly for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads workflows. It is an AI Agent Skill for Claude Code / OpenClaw, with 337 downloads so far.

How do I install Ads Q&A Assistant?

Run "/install ads-qa-assistant" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Ads Q&A Assistant free?

Yes, Ads Q&A Assistant is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Ads Q&A Assistant support?

Ads Q&A Assistant is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Ads Q&A Assistant?

It is built and maintained by danyangliu (@danyangliu-sandwichlab); the current version is v1.0.0.

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