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skill Claude Code

sales-engineer — Claude Code skill: what it does, how to install

Analyzes RFP and RFI requirements, builds competitor feature matrices, and structures POC plans for pre-sales engineering workflows.

Install into Claude Code · Plugin marketplace All methods and platforms ↓
/plugin marketplace add alirezarezvani/claude-skills
/plugin install business-growth-skills@claude-code-skills
Open on GitHub

What sales-engineer does

The skill establishes a structured 5-phase workflow for pre-sales teams: discovery, solution design, demo prep, POC execution, and technical proposal delivery. Each phase includes a checklist and validation checkpoints. Teams cannot advance without satisfying quantitative criteria.

It relies on dedicated Python scripts and markdown templates. The rfp_response_analyzer.py script calculates requirement coverage and outputs bid, conditional bid, or no-bid recommendations. The competitive_matrix_builder.py script highlights feature vulnerabilities against rivals, while poc_planner.py structures evaluation scorecards.

You need Python installed to run the analysis scripts against your JSON data files. This skill pays off for sales engineers handling formal tenders and technical software evaluations.

What it helps with

  • score customer RFP requirements and highlight gaps
  • generate bid or no-bid decisions based on coverage thresholds
  • build competitive feature matrices with differentiators
  • define POC timelines, scopes, and scoring criteria
  • draft demo scripts tailored to stakeholder priorities

Example prompts for the agent

  • Analyze RFP coverage in assets/sample_rfp_data.json using rfp_response_analyzer.py
  • Build a competitive comparison from competitive_data.json and highlight vulnerabilities
  • Generate a POC plan and scorecard from poc_data.json

How to install sales-engineer

1Plugin marketplace

/plugin marketplace add alirezarezvani/claude-skills
/plugin install business-growth-skills@claude-code-skills

This installs the whole business-growth-skills plugin with all its skills

2Skills CLI (Vercel)

npx skills add alirezarezvani/claude-skills --skill sales-engineer -a claude-code

3Manually: put the files in place

~/.claude/skills/sales-engineer/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/sales-engineer/

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Similar

Questions about sales-engineer

How do I install sales-engineer in Claude Code?

Run npx skills add alirezarezvani/claude-skills --skill sales-engineer -a claude-code or /plugin marketplace add alirezarezvani/claude-skills. Alternatively, add SKILL.md directly to ~/.claude/skills/sales-engineer/SKILL.md.

What does the sales-engineer skill do?

It guides a 5-phase pre-sales process covering discovery, architecture design, targeted demos, proof-of-concept testing, and technical closing proposals.

How does it determine bid or no-bid recommendations?

The rfp_response_analyzer.py script suggests Bid when coverage exceeds 70% with 3 or fewer must-have gaps. It triggers No-Bid when coverage drops below 50% or must-have gaps exceed 3.

Source text

SKILL.md · MIT
---
name: "sales-engineer"
description: Analyzes RFP/RFI responses for coverage gaps, builds competitive feature comparison matrices, and plans proof-of-concept (POC) engagements for pre-sales engineering. Use when responding to RFPs, bids, or proposal requests; comparing product features against competitors; planning or scoring a customer POC or sales demo; preparing a technical proposal; or performing win/loss competitor analysis. Handles tasks described as 'RFP response', 'bid response', 'proposal response', 'competitor comparison', 'feature matrix', 'POC planning', 'sales demo prep', or 'pre-sales engineering'.
---

# Sales Engineer Skill

## 5-Phase Workflow

### Phase 1: Discovery & Research

**Objective:** Understand customer requirements, technical environment, and business drivers.

**Checklist:**
- [ ] Conduct technical discovery calls with stakeholders
- [ ] Map customer's current architecture and pain points
- [ ] Identify integration requirements and constraints
- [ ] Document security and compliance requirements
- [ ] Assess competitive landscape for this opportunity

**Tools:** Run `rfp_response_analyzer.py` to score initial requirement alignment.

```bash
python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json --format json > phase1_rfp_results.json
```

**Output:** Technical discovery document, requirement map, initial coverage assessment.

**Validation checkpoint:** Coverage score must be >50% and must-have gaps ≤3 before proceeding to Phase 2. Check with:
```bash
python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json --format json | python -c "import sys,json; r=json.load(sys.stdin); print('PROCEED' if r['coverage_score']>50 and r['must_have_gaps']<=3 else 'REVIEW')"
```

---

### Phase 2: Solution Design

**Objective:** Design a solution architecture that addresses customer requirements.

**Checklist:**
- [ ] Map product capabilities to customer requirements
- [ ] Design integration architecture
- [ ] Identify customization needs and development effort
- [ ] Build competitive differentiation strategy
- [ ] Create solution architecture diagrams

**Tools:** Run `competitive_matrix_builder.py` using Phase 1 data to identify differentiators and vulnerabilities.

```bash
python scripts/competitive_matrix_builder.py competitive_data.json --format json > phase2_competitive.json

python -c "import json; d=json.load(open('phase2_competitive.json')); print('Differentiators:', d['differentiators']); print('Vulnerabilities:', d['vulnerabilities'])"
```

**Output:** Solution architecture, competitive positioning, technical differentiation strategy.

**Validation checkpoint:** Confirm at least one strong differentiator exists per customer priority before proceeding to Phase 3. If no differentiators found, escalate to Product Team (see Integration Points).

---

### Phase 3: Demo Preparation & Delivery

**Objective:** Deliver compelling technical demonstrations tailored to stakeholder priorities.

**Checklist:**
- [ ] Build demo environment matching customer's use case
- [ ] Create demo script with talking points per stakeholder role
- [ ] Prepare objection handling responses
- [ ] Rehearse failure scenarios and recovery paths
- [ ] Collect feedback and adjust approach

**Templates:** Use `assets/demo_script_template.md` for structured demo preparation.

**Output:** Customized demo, stakeholder-specific talking points, feedback capture.

**Validation checkpoint:** Demo script must cover every must-have requirement flagged in `phase1_rfp_results.json` before delivery. Cross-reference with:
```bash
python -c "import json; rfp=json.load(open('phase1_rfp_results.json')); [print('UNCOVERED:', r) for r in rfp['must_have_requirements'] if r['coverage']=='Gap']"
```

---

### Phase 4: POC & Evaluation

**Objective:** Execute a structured proof-of-concept that validates the solution.

**Checklist:**
- [ ] Define POC scope, success criteria, and timeline
- [ ] Allocate resources and set up environment
- [ ] Execute phased testing (core, advanced, edge cases)
- [ ] Track progress against success criteria
- [ ] Generate evaluation scorecard

**Tools:** Run `poc_planner.py` to generate the complete POC plan.

```bash
python scripts/poc_planner.py poc_data.json --format json > phase4_poc_plan.json

python -c "import json; p=json.load(open('phase4_poc_plan.json')); print('Go/No-Go:', p['recommendation'])"
```

**Templates:** Use `assets/poc_scorecard_template.md` for evaluation tracking.

**Output:** POC plan, evaluation scorecard, go/no-go recommendation.

**Validation checkpoint:** POC conversion requires scorecard score >60% across all evaluation dimensions (functionality, performance, integration, usability, support). If score <60%, document gaps and loop back to Phase 2 for solution redesign.

---

### Phase 5: Proposal & Closing

**Objective:** Deliver a technical proposal that supports the commercial close.

**Checklist:**
- [ ] Compile POC results and success metrics
- [ ] Create technical proposal with implementation plan
- [ ] Address outstanding objections with evidence
- [ ] Support pricing and packaging discussions
- [ ] Conduct win/loss analysis post-decision

**Templates:** Use `assets/technical_proposal_template.md` for the proposal document.

**Output:** Technical proposal, implementation timeline, risk mitigation plan.

---

## Python Automation Tools

### 1. RFP Response Analyzer

**Script:** `scripts/rfp_response_analyzer.py`

**Purpose:** Parse RFP/RFI requirements, score coverage, identify gaps, and generate bid/no-bid recommendations.

**Coverage Categories:** Full (100%), Partial (50%), Planned (25%), Gap (0%).  
**Priority Weighting:** Must-Have 3×, Should-Have 2×, Nice-to-Have 1×.

**Bid/No-Bid Logic:**
- **Bid:** Coverage >70% AND must-have gaps ≤3
- **Conditional Bid:** Coverage 50–70% OR must-have gaps 2–3
- **No-Bid:** Coverage <50% OR must-have gaps >3

**Usage:**
```bash
python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json            # human-readable
python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json --format json  # JSON output
python scripts/rfp_response_analyzer.py --help
```

**Input Format:** See `assets/sample_rfp_data.json` for the complete schema.

---

### 2. Competitive Matrix Builder

**Script:** `scripts/competitive_matrix_builder.py`

**Purpose:** Generate feature comparison matrices, calculate competitive scores, identify differentiators and vulnerabilities.

**Feature Scoring:** Full (3), Partial (2), Limited (1), None (0).

**Usage:**
```bash
python scripts/competitive_matrix_builder.py competitive_data.json              # human-readable
python scripts/competitive_matrix_builder.py competitive_data.json --format json  # JSON output
```

**Output Includes:** Feature comparison matrix, weighted competitive scores, differentiators, vulnerabilities, and win themes.

---

### 3. POC Planner

**Script:** `scripts/poc_planner.py`

**Purpose:** Generate structured POC plans with timeline, resource allocation, success criteria, and evaluation scorecards.

**Default Phase Breakdown:**
- **Week 1:** Setup — environment provisioning, data migration, configuration
- **Weeks 2–3:** Core Testing — primary use cases, integration testing
- **Week 4:** Advanced Testing — edge cases, performance, security
- **Week 5:** Evaluation — scorecard completion, stakeholder review, go/no-go

**Usage:**
```bash
python scripts/poc_planner.py poc_data.json              # human-readable
python scripts/poc_planner.py poc_data.json --format json  # JSON output
```

**Output Includes:** Phased POC plan, resource allocation, success criteria, evaluation scorecard, risk register, and go/no-go recommendation framework.

---

## Reference Knowledge Bases

| Reference | Description |
|-----------|-------------|
| `references/rfp-response-guide.md` | RFP/RFI response best practices, compliance matrix, bid/no-bid framework |
| `references/competitive-positioning-framework.md` | Competitive analysis methodology, battlecard creation, objection handling |
| `references/poc-best-practices.md` | POC planning methodology, success criteria, evaluation frameworks |

## Asset Templates

| Template | Purpose |
|----------|---------|
| `assets/technical_proposal_template.md` | Technical proposal with executive summary, solution architecture, implementation plan |
| `assets/demo_script_template.md` | Demo script with agenda, talking points, objection handling |
| `assets/poc_scorecard_template.md` | POC evaluation scorecard with weighted scoring |
| `assets/sample_rfp_data.json` | Sample RFP data for testing the analyzer |
| `assets/expected_output.json` | Expected output from rfp_response_analyzer.py |

## Integration Points

- **Marketing Skills** - Leverage competitive intelligence and messaging frameworks from `marketing-skill/`
- **Product Team** - Coordinate on roadmap items flagged as "Planned" in RFP analysis from `product-team/`
- **C-Level Advisory** - Escalate strategic deals requiring executive engagement from `c-level-advisor/`
- **Customer Success** - Hand off POC results and success criteria to CSM from `../customer-success-manager/`

---

**Last Updated:** February 2026
**Status:** Production-ready
**Tools:** 3 Python automation scripts
**References:** 3 knowledge base documents
**Templates:** 5 asset files

© Alireza Rezvani · MIT · alirezarezvani/claude-skills

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