lcrm-deal-closer

Original：🇨🇳 Chinese

Translated

First obtain customer information and follow-up records, determine the product matching path, and output targeted sales strategies. Supports two product lines: Pre-sales Digital Employee and Langtum Platform.

2installs

Sourcer-earth-or/lcrm_skills

Added on2026-02-25

NPX Install

npx skill4agent add r-earth-or/lcrm_skills lcrm-deal-closer

SKILL.md Content (Chinese)

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Sales Deal Assistant

Goal

For customers already being followed up, combine CRM follow-up records to determine the product matching path and output executable sales solutions.

Knowledge Base References

Load the following documents (relative to this skill directory):

Product System Overview:
```
knowledge/claude.md
```

Pre-sales Digital Employee Product Description:

knowledge/数字员工/售前数字员工产品说明书.md

Langtum Platform Introduction:
```
knowledge/langtum/什么是langtum.md
```

Langtum Platform Architecture:

knowledge/langtum/Langtum平台架构.md

Langtum Use Cases:

knowledge/langtum/Langtum使用场景.md

Dependencies

```
lcrm-search
```
skill: Obtain customer business records (follow-up history)

Workflow

Step 1: Obtain Customer Information

Proactively ask the user:

What is the customer name?
What are the known needs or scenarios?
Are there any follow-up records to reference?

If follow-up records need to be referenced, call the

lcrm-search

skill to obtain the customer's business records:

Script:

node scripts/search.mjs customer-business-records --customer-id "<customerId>"

If the customerId is unknown, first use:

node scripts/search.mjs customers --company-name "<customer name>" --limit 5

Step 2: Determine Product Matching Path

Customer Characteristics	Recommended Path
Complex SKUs/Frequent bidding/B2B/Direct sales team	Pre-sales Digital Employee Sales Strategy
Does not fit the above profile, but has AI needs or business process optimization needs	Langtum Platform Sales Strategy

Step 3: Output Sales Strategy

Pre-sales Digital Employee Path

Based on 5 core capabilities + customer scenarios, output:

Output Item	Content
Matching Degree Rating	High/Medium/Low + matching point analysis (product features/sales model/industry)
Core Entry Points	Up to 3, sorted by priority, each with script
Objection Handling	Address 3 main possible objections from customers
Next Actions	1-2 clear promotion actions

Reference for the 5 core capabilities:

① Deep Knowledge Ingestion & Precise Q&A → Applicable: Many SKUs, sales can't remember parameters
② Consultative Demand Guidance → Applicable: Vague needs, rely on senior expert experience
③ Deterministic Logical Reasoning & Calculation → Applicable: Compatibility verification, high cost of misconfiguration
④ Strong Compliance & Tender Document Generation → Applicable: Frequent bidding, time-consuming tender writing
⑤ Solution & Quotation Closure → Applicable: Complex configuration lists, cross-departmental verification

Langtum Platform Path

Based on customer business pain points, output:

Output Item	Content
Core Pain Points	Inefficient links in customer business processes
Platform Capability Matching	Chatbot/Multi-Agent/Workflow/Knowledge Base/Plugin System
Custom Scenario Suggestions	Which module to use specifically to solve which problem
Entry Script	Opening remarks + value proposition
Next Actions	1-2 clear promotion actions

Output Style Requirements

Structured: Use tables and lists, no large paragraphs of text
Direct conclusions: Core views first
Plain language: Avoid AI jargon, use customer business language
Quantified value: Each value point must have numbers
Executable: Provide clear next actions