技能详情（站内镜像，无评论）
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 · 193 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：danyangliu-sandwichlab/ad-account-health-checker
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
This is an instruction-only, advisory skill (checklist and recommendations) that does not request credentials or install anything and is internally consistent for providing manual/account-review guidance rather than performing automated API-driven audits.
目的
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).
说明范围
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.
安装机制
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.
证书
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.
持久
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.
综合结论
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 credenti…
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 Account Health」。简介：Assess ad account readiness and risk status across Meta (Facebook/Instagram), G…。
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/ad-account-health-checker/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: 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.
---
# 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