Sales Helper

v1.0.0

Parse client URLs and requirements to generate ad proposals, ROI estimates, persuasion logic, and CRM-based close probability forecasting for Meta (Facebook/...

1· 533·3 current·3 all-time

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for danyangliu-sandwichlab/sales-ads-helper.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Sales Helper" (danyangliu-sandwichlab/sales-ads-helper) from ClawHub.
Skill page: https://clawhub.ai/danyangliu-sandwichlab/sales-ads-helper
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Canonical install target

openclaw skills install danyangliu-sandwichlab/sales-ads-helper

ClawHub CLI

Package manager switcher

npx clawhub@latest install sales-ads-helper
Security Scan
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high confidence
Purpose & Capability
Name/description (ad proposals, ROI, persuasion, CRM forecasting) align with the inputs declared (prospect_url, prospect_need_summary, proposed_service_scope, crm_stage_data). No extraneous environment variables, binaries, or config paths are requested that would be unrelated to generating proposals.
Instruction Scope
SKILL.md stays within sales/forecasting scope and specifies required inputs and outputs. One ambiguity: 'Parse URL and infer business model' implies the agent may fetch and analyze remote site content (reasonable for the task) — the instructions do not explicitly describe whether or how to fetch or cache that content nor address handling of sensitive PII in CRM data. Recommend clarifying network fetch behavior and data minimization.
Install Mechanism
No install spec and no code files — lowest-risk delivery model. Nothing is downloaded or written to disk by the skill itself.
Credentials
The skill declares no environment variables, credentials, or config paths. It only requests domain-relevant inputs (CRM fields, prospect URL, optional win rates/terms), which is proportionate to the stated purpose.
Persistence & Privilege
always is false and the skill does not request persistent system-level presence or to modify other skills. Autonomous invocation is allowed by default but is not combined with broad credential access here.
Assessment
This skill appears coherent and low-risk, but before installing consider: 1) Only provide the minimum CRM fields needed and avoid dumping raw PII or full customer records into the skill. 2) Clarify whether the agent will fetch the prospect URL (network access) and whether that request will include sensitive headers or cookies. 3) Expect the skill to produce estimates based on assumptions you supply—verify ROI numbers and close-probability logic before acting on them. 4) If you want the skill to operate on live ad accounts (create campaigns, read ad account metrics), it currently requests no ad-platform credentials—so it cannot perform those actions; adding credentials later would merit a separate security review.

Like a lobster shell, security has layers — review code before you run it.

latestvk97ftxev5mtcqag2a6kdznta5x8299y7
533downloads
1stars
1versions
Updated 1mo ago
v1.0.0
MIT-0

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

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