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Ads Q&A Assistant
作者
danyangliu
· GitHub ↗
· v1.0.0
337
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0
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0
当前安装
1
版本数
在 OpenClaw 中安装
/install ads-qa-assistant
功能描述
Answer ads operations questions quickly for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads workflows.
使用说明 (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:
- Intent Summary (goal, KPI, scope)
- Findings (key observations and assumptions)
- Action Plan (prioritized next steps)
- Risks and Guardrails (what can break and what to monitor)
- Handoff Payload (structured fields for downstream skills)
Workflow
- Normalize request and confirm objective.
- Validate available inputs and list missing critical data.
- Analyze according to this skill focus: rapid Q&A, playbook lookup, issue triage.
- Generate prioritized actions tied to KPI impact.
- Add platform-specific notes and constraints.
- 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
安全使用建议
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.
功能分析
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.
能力评估
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.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install ads-qa-assistant - 安装完成后,直接呼叫该 Skill 的名称或使用
/ads-qa-assistant触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
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.
元数据
常见问题
Ads Q&A Assistant 是什么?
Answer ads operations questions quickly for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads workflows. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 337 次。
如何安装 Ads Q&A Assistant?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install ads-qa-assistant」即可一键安装,无需额外配置。
Ads Q&A Assistant 是免费的吗?
是的,Ads Q&A Assistant 完全免费(开源免费),可自由下载、安装和使用。
Ads Q&A Assistant 支持哪些平台?
Ads Q&A Assistant 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Ads Q&A Assistant?
由 danyangliu(@danyangliu-sandwichlab)开发并维护,当前版本 v1.0.0。
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