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

综合技能

作者:danyangliu @danyangliu-sandwichlab

许可证:MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本:v1.0.0

统计:⭐ 0 · 206 · 0 current installs · 0 all-time installs

0

安装量(当前) 0

🛡 VirusTotal :良性 · OpenClaw :良性

Package:danyangliu-sandwichlab/ads-qa-assistant

安全扫描(ClawHub)

  • VirusTotal :良性
  • OpenClaw :良性

OpenClaw 评估

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.

目的

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.).

说明范围

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.

安装机制

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.

证书

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.

持久

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.

综合结论

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, …

安装(复制给龙虾 AI)

将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「Ads Q&A Assistant」。简介:Answer ads operations questions quickly for Meta (Facebook/Instagram), Google A…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/danyangliu-sandwichlab/ads-qa-assistant/SKILL.md
(来源:yingzhi8.cn 技能库)

SKILL.md

打开原始 SKILL.md(GitHub raw)

---
name: 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.
---

# 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