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.

Security Scan

This instruction-only Ads Q&A skill is internally consistent with its description: it requests no credentials, performs no installs, and its runtime instructions stay within the advertised ads advisory scope.

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.

Assessment

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.

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