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PythonReactSEOPDF
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 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

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

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

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...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/danyangliu-sandwichlab/ads-data-query-assistant
Version
—
Commit
0000c0032de12ef97e210dee1e0db07cc37f7827
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

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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