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sales-ads-helper销售广告助手

Agent Skill

sales-ads-helper 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

16,252

周安装

691

GitHub Stars

1

下载量

5,694
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:sales-ads-helper(销售广告助手)
来源仓库:https://github.com/danyangliu-sandwichlab/sales-ads-helper
安装命令:
openclaw skills install sales-ads-helper
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install sales-ads-helper

简介

sales-ads-helper 解析客户 URL 并生成广告提案与投资回报率预测。

  • 适用于 Meta、Google、TikTok 等平台广告投放与开发支持任务。
  • 通过 clawhub 安装后,可自动生成说服逻辑与接近概率分析报告。
  • 使用前需确认 CRM 系统对接权限及广告账户访问安全性。
  • 建议核对投放平台最新政策以避免违规推广内容。

SKILL.md

name
sales-ads-helper
description
Parse client URLs and requirements to generate ad proposals, ROI estimates, persuasion logic, and CRM-based close probability forecasting for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads services.

Sales Helper

Purpose

Core mission:

  • Convert customer URL and needs into a launch proposal and ROI estimate.
  • Output persuasion strategy and closing logic.
  • Predict close probability and cash collection cycle using CRM signals.
  • Generate sales daily follow-up and retrospective reports.

When To Trigger

Use this skill when the user asks for:

  • proposal drafting for ads services
  • ROI estimate for prospect conversion
  • close strategy for uncertain deals
  • daily sales report or follow-up summary

High-signal keywords:

  • sales, sell, closer, leads, customers
  • ads, campaign, roi, roas, cpa
  • report, dashboard, revenue, acquire

Input Contract

Required:

  • prospect_url
  • prospect_need_summary
  • proposed_service_scope
  • crm_stage_data

Optional:

  • historical_win_rate
  • contract_terms
  • payment_terms
  • competitor_quote

Output Contract

  1. Proposal Summary (scope + value)
  2. ROI Estimate (assumptions + model)
  3. Persuasion and Objection Strategy
  4. Close Probability and Collection Cycle Forecast
  5. Sales Daily/Follow-up/Retrospective Template

Workflow

  1. Parse URL and infer business model.
  2. Map pain points to ads service package.
  3. Build ROI estimate with explicit assumptions.
  4. Choose persuasion path by decision-maker type.
  5. Score deal probability from CRM stage features.
  6. Output follow-up and close action list.

Decision Rules

  • If prospect urgency is high, prioritize short pilot with rapid proof plan.
  • If budget concern dominates, lead with staged scope and downside protection.
  • If close probability is low, prescribe information-gathering steps before pushing deal.
  • If payment risk is high, optimize term structure before scaling scope.

Platform Notes

Primary scope:

  • Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads

Platform behavior guidance:

  • Proposals should tie channel choice to measurable business outcome.
  • Keep ROI model channel-aware, not one blended black-box number.

Constraints And Guardrails

  • Never fabricate past case studies or performance numbers.
  • Keep ROI estimates assumption-driven and auditable.
  • Separate sales narrative from guaranteed delivery claims.

Failure Handling And Escalation

  • If CRM stage data is missing, return low-confidence range and required fields.
  • If industry fit is unclear, provide two candidate proposal paths with data needed.
  • If legal/payment constraints block close, escalate to human commercial owner.

Code Examples

ROI Estimate Payload

{ "service_fee": 12000, "planned_spend": 50000, "assumed_roas": 2.4, "projected_revenue": 120000, "gross_profit_estimate": 36000 }

Close Probability Formula

close_score = stage_weight + urgency_score + budget_fit + stakeholder_alignment if close_score >= 75: close_probability = "high"

Examples

Example 1: New inbound lead

Input:

  • URL submitted + basic requirement

Output focus:

  • first proposal draft
  • ROI estimate range
  • next follow-up question

Example 2: Stalled opportunity

Input:

  • Deal stuck in negotiation
  • Objection: ROI uncertainty

Output focus:

  • persuasion strategy
  • revised offer structure
  • close plan

Example 3: Sales daily report

Input:

  • CRM updates for 12 opportunities

Output focus:

  • probability movement
  • expected cash collection window
  • rep action priorities

Quality Checklist

  • [ ] Required sections are complete and non-empty
  • [ ] Trigger keywords include at least 3 registry terms
  • [ ] Input and output contracts are operationally testable
  • [ ] Workflow and decision rules are capability-specific
  • [ ] Platform references are explicit and concrete
  • [ ] At least 3 practical examples are included

适合场景

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02

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03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

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能力 2

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能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

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能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

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按下载量换算4,469

安全审计

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通过

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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