sales-engineer

Automate RFP analysis, competitive feature matrices, and proof-of-concept planning.

1|Updated Feb 19, 2026
One-click install
npx skills add https://github.com/mcauduro0/Macro_Trading --skill sales-engineer-mcauduro0
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sales-engineer
Source: https://github.com/mcauduro0/Macro_Trading/tree/main/.claude/skills/alireza-sales-engineer
Command: npx skills add https://github.com/mcauduro0/Macro_Trading --skill sales-engineer-mcauduro0

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the pre-sales engineering process by automating RFP analysis, competitive positioning, and proof-of-concept planning, enabling faster deal cycles and higher win rates.

Core Features & Use Cases

  • RFP Analysis: Identifies coverage gaps and provides bid/no-bid recommendations.
  • Competitive Matrix: Builds feature comparisons and highlights differentiators.
  • POC Planning: Generates structured plans for proof-of-concept engagements.
  • Use Case: A sales team receives a complex RFP. They use this Skill to quickly analyze requirement coverage, identify key competitive advantages, and generate a solid plan for a customer proof-of-concept.

Quick Start

Use the sales-engineer skill to analyze the RFP document located at '/mnt/data/rfp_response.json'.

Frequently Asked Questions about sales-engineer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze an RFP document to identify requirement coverage gaps?▼

RFP analysis identifies requirement coverage gaps by evaluating the document against your capabilities, scoring the competitive landscape, and generating bid/no-bid recommendations to guide pre-sales strategy.

What is the best way to generate a competitive feature matrix for a technical proposal?▼

Generating a competitive feature matrix builds feature comparisons and highlights key differentiators, enabling sales teams to clearly map competitive advantages and structure technical proposals effectively.

How do I structure a proof-of-concept plan for a pre-sales engagement?▼

Structuring a proof-of-concept plan generates structured validation engagements by identifying technical requirements and organizing execution steps to validate solution fit for the customer.

Can I use Python scripts for deterministic RFP analysis and structured markdown output?▼

Yes, this approach utilizes Python scripts for deterministic analysis of RFP responses and uses markdown templates to output structured pre-sales engineering deliverables like competitive matrices.

Does this approach support bid/no-bid recommendations for complex technical proposals?▼

Yes, analyzing technical proposals identifies coverage gaps and scores competitive landscapes, directly supporting bid/no-bid recommendations to optimize resource allocation during the sales cycle.

When do I need automated competitive intelligence for proof-of-concept planning?▼

You need automated competitive intelligence when preparing proof-of-concept engagements to quickly highlight product differentiators, map requirement coverage, and accelerate complex deal cycles.