OpenClaw

ads-data-query-assistant

Run natural-language data query workflows for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads reports.

danyangliu-sandwichlab0 来源安装数☆ 0 仓库 Stars

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install danyangliu-sandwichlab/ads-data-query-assistant

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Ads Data Query

Purpose

Translate questions into precise metric pulls and decision-ready summaries.

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: query translation, metric extraction, decision summary

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: query translation, metric extraction, decision summary.
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...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/danyangliu-sandwichlab/ads-data-query-assistant
Version: —
Commit: 0000c0032de12ef97e210dee1e0db07cc37f7827
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# Ads Data Query

## Purpose
Translate questions into precise metric pulls and decision-ready summaries.

## 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: query translation, metric extraction, decision summary

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: query translation, metric extraction, decision summary.
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...

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