sales-engineer

Analyzes RFP coverage, builds competitive matrices, and plans POC engagements for pre-sales workflows.

1|Updated May 6, 2026
One-click install
npx skills add https://github.com/surfingalien/FinSurfing --skill sales-engineer-surfingalien
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sales-engineer
Source: https://github.com/surfingalien/FinSurfing/tree/main/business-growth/skills/sales-engineer
Command: npx skills add https://github.com/surfingalien/FinSurfing --skill sales-engineer-surfingalien

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve? Responding to RFPs, comparing products against competitors, and running proof-of-concept evaluations are time-consuming pre-sales tasks that often rely on ad-hoc spreadsheets and gut feel. This Skill structures the entire sales engineering workflow into five phases with deterministic Python scoring tools, so bid decisions, competitive positioning, and POC go/no-go calls are based on quantified criteria rather than intuition. ## Core Features & Use Cases - RFP Response Analysis: Parse RFP/RFI requirements, compute weighted coverage scores (Must-Have 3x, Should-Have 2x, Nice-to-Have 1x), identify gaps, and generate bid/no-bid recommendations with effort estimates. - Competitive Matrix Building: Score features across products (Full/Partial/Limited/None), calculate weighted category scores, and surface differentiators, vulnerabilities, and win themes. - POC Planning: Generate phased POC plans (Setup, Core Testing, Advanced Testing, Evaluation) with resource hour estimates, success criteria, evaluation scorecards, risk registers, and go/no-go decision frameworks. - Use Case: A sales engineer receives a 21-requirement RFP from a financial services prospect. They run the analyzer against the requirement JSON, get an 84.5% coverage score with a BID recommendation, then use the competitive matrix to position against two rivals and the POC planner to structure a 5-week evaluation. ## Quick Start Ask the assistant to analyze the sample RFP data in this Skill and produce a coverage score with a bid/no-bid recommendation.

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 response for coverage gaps?▼

Format the RFP requirements as JSON following the sample schema, then run rfp_response_analyzer.py against it. The script scores each requirement as Full, Partial, Planned, or Gap, applies priority weighting, and outputs a coverage percentage with a bid/no-bid recommendation.

How do I build a competitive feature comparison matrix?▼

Create a JSON file listing categories, features, and per-product scores, then run competitive_matrix_builder.py. It computes weighted competitive scores, identifies differentiators where your product leads, vulnerabilities where competitors lead, and generates win themes.

What criteria determine a bid versus no-bid decision?▼

The analyzer recommends Bid when coverage exceeds 70% with three or fewer must-have gaps, Conditional Bid for 50-70% coverage, and No-Bid when coverage falls below 50% or must-have gaps exceed three. Strategic value and effort estimates also inform the decision.

How long should a proof of concept run?▼

The default framework spans five weeks: one week of setup, two weeks of core testing, one week of advanced testing, and one week of evaluation. Low-complexity POCs can compress to three weeks, while high-complexity ones may extend to eight weeks maximum.

What input format do the sales engineering scripts require?▼

All three scripts accept JSON files as input. The RFP analyzer expects requirements with priority and coverage status, the matrix builder expects categories with per-product feature scores, and the POC planner expects a poc_name plus optional scope items, stakeholders, and complexity.

When should a deal not proceed to a POC?▼

Avoid POCs when there is no identified champion or decision-maker, no defined success criteria, no budget process underway, or when the request is effectively a free trial with no evaluation commitment. The POC planner flags stakeholder and timeline risks automatically.