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danyangliu-sandwichlab

Ads Account Health

by danyangliu · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install ad-account-health-checker
Description
Assess ad account readiness and risk status across Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and DSP/programmatic.
README (SKILL.md)

Ads Account Health

Purpose

Evaluate account structure, permissions, policy risk, billing state, and launch readiness.

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: account checklist, risk scan, launch readiness score

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: account checklist, risk scan, launch readiness score.
  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, DSP/programmatic

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 to be an advisory/account-checklist tool and does not attempt to access ad platforms automatically — it expects the user to provide context and metrics. Before installing or using: 1) confirm you understand it will not perform live API audits (no credentials requested); if you want automated checks, use a different skill that explicitly requests and documents platform API credentials and scopes. 2) Do not paste live credentials, access tokens, or sensitive billing data into the free-text 'context' field—sanitize or share minimal safe examples. 3) Because the source/homepage is unknown, prefer testing on non-production examples and ask the provider for provenance if you plan to integrate it into workflows that will handle secrets or trigger downstream automation. 4) If you later connect this skill to downstream automation that does require credentials, grant least privilege tokens and audit where those tokens are stored and used.
Capability Analysis
Type: OpenClaw Skill Name: ad-account-health-checker Version: 1.0.0 The skill bundle is benign. The `SKILL.md` file provides clear, well-defined instructions for an AI agent to perform an 'ad-account-health-checker' task, focusing on analysis and recommendation generation. There are no instructions for data exfiltration, malicious execution, persistence, or any form of prompt injection designed to subvert the agent's intended purpose. In fact, the 'Constraints And Guardrails' section explicitly instructs the agent to avoid fabricating data or making irreversible changes, which actively mitigates potential risks.
Capability Assessment
Purpose & Capability
The name/description claim to assess ad account readiness across many ad platforms. The SKILL.md is consistent with an advisory/checklist-style capability that relies on user-supplied context rather than performing live API checks. This is coherent if the intent is advisory work; it would be mismatched only if the user expects the skill to connect to platform APIs (the skill requests no credentials or API access).
Instruction Scope
The runtime instructions are focused and scoped to normal advisory tasks: normalizing requests, validating inputs, producing findings and action plans, and emitting a handoff payload. The SKILL.md does not instruct the agent to read unrelated files, access system environment variables, or send data to external endpoints beyond normal output. It includes guardrails against fabricating data and escalation rules.
Install Mechanism
No install specification and no code files are present (instruction-only). This is the lowest-risk model: nothing is written to disk or executed automatically by an installer.
Credentials
The skill requests no environment variables, credentials, or config paths, which is proportionate for an advisory checklist. Note: the 'context' input may contain sensitive account details if pasted by the user — the skill does not ask for secrets, but user-provided context could include them.
Persistence & Privilege
The skill is not always-enabled and does not request persistent system privileges or modifications to other skills. Model invocation is allowed (the platform default), which is expected for a user-invocable skill.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ad-account-health-checker
  3. After installation, invoke the skill by name or use /ad-account-health-checker
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release – assess ad account health, risks, and launch readiness across major ad platforms. - Supports Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and DSP/programmatic. - Evaluates account structure, permissions, policy risk, billing status, and readiness to launch or scale campaigns. - Standardizes inputs and outputs with clear contracts for goals, KPIs, constraints, and platform preferences. - Delivers concise findings, prioritized next steps, risks/guardrails, and a handoff payload for downstream use. - Includes decision rules for missing data, compliance risks, and platform ambiguity. - Provides platform-specific recommendations and actionable examples.
Metadata
Slug ad-account-health-checker
Version 1.0.0
License
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Ads Account Health?

Assess ad account readiness and risk status across Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and DSP/programmatic. It is an AI Agent Skill for Claude Code / OpenClaw, with 304 downloads so far.

How do I install Ads Account Health?

Run "/install ad-account-health-checker" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Ads Account Health free?

Yes, Ads Account Health is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Ads Account Health support?

Ads Account Health is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Ads Account Health?

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

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