When an RFP lands Friday with a Monday deadline, /sales-engineer scores coverage and gives you a bid/no-bid call in 30 minutes. — Claude Skill
Un Skill de Claude para Claude Code por Alireza Rezvani — ejecutar /sales-engineer en Claude·Actualizado el 10 abr 2026·v1.0.0
Score RFPs, build competitive matrices, plan POCs in pre-sales
- RFP analyzer with coverage scoring (Full / Partial / Planned / Gap) and bid/no-bid recommendation: Bid (>70% + ≤3 must-have gaps), Conditional, No-Bid
- Competitive matrix builder: feature-by-feature scoring (Full=3, Partial=2, Limited=1, None=0), weighted competitive scores, differentiators, vulnerabilities, win themes
- POC planner with 5-week phased timeline, success criteria, evaluation scorecard (>60% to convert), and go/no-go recommendation framework
- 5-phase pre-sales workflow: Discovery → Solution Design → Demo → POC → Proposal & Closing
- Templates: technical proposal, demo script, POC scorecard, sample RFP data
Para quién es
Score RFP coverage and get bid/no-bid recommendation before committing 40 hours to a response
Ver skills para este rolBuild competitive matrix and demo script for enterprise deals with multiple competitors
Ver skills para este rolStandardize POC planning across the team with success criteria and go/no-go scorecards
Ver skills para este rolQué hace
50-page RFP just dropped and the SE team is debating bid vs no-bid. /sales-engineer scores requirement coverage (Must-Have ×3, Should-Have ×2, Nice-to-Have ×1), flags coverage gaps, and gives you a bid/no-bid call in 30 minutes — not 8 hours of arguing.
AE asks for a competitive battlecard before the demo. /sales-engineer builds a feature-by-feature comparison matrix with weighted scores, identifies your differentiators (where you score Full and they score Partial/None), and surfaces vulnerabilities to address.
Procurement requires a structured POC. /sales-engineer plans Setup (week 1), Core Testing (weeks 2-3), Advanced Testing (week 4), and Evaluation (week 5) with weekly success criteria and a go/no-go scorecard at the end.
VP asks why you lost the Acme deal. /sales-engineer reviews phase-by-phase: was it RFP coverage, competitive positioning, demo execution, or POC scoring — and which phase to invest in next quarter.
Cómo funciona
Phase 1 — Discovery: run rfp_response_analyzer on requirements JSON, get coverage score and must-have gap count
Phase 2 — Solution Design: run competitive_matrix_builder, get differentiators per priority and vulnerabilities to address
Phase 3 — Demo: build script from demo_script_template, validation checkpoint against must-have requirements
Phase 4 — POC: run poc_planner with phased timeline, success criteria, and weekly milestones
Phase 5 — Closing: technical proposal from template_proposal, win/loss analysis post-decision
Ejemplo
Acme Inc — RFP for Customer Data Platform 84 requirements: 22 Must-Have, 38 Should-Have, 24 Nice-to-Have Deadline: Monday 5pm (3 days) 3 known competitors: Segment, mParticle, RudderStack
Overall coverage: 73% (Bid threshold: >70%) Must-Have: 18 Full / 2 Partial / 1 Planned / 1 Gap (95% covered) Should-Have: 24 Full / 9 Partial / 5 Gap (87% covered) Nice-to-Have: 11 Full / 8 Partial / 5 Gap (79% covered)
✅ Coverage 73% (>70% threshold) ✅ Must-Have gaps: 1 (≤3 threshold) The one Must-Have gap is API rate limiting at 10K/sec — we support 5K/sec. Conditional bid possible if we commit to roadmap delivery in Q3.
GAP — Req #14: API rate limiting 10K/sec → propose Q3 roadmap commitment PARTIAL — Req #28: SOC 2 Type II → we have Type I, get attestation by deadline PARTIAL — Req #41: Custom retention rules → workaround via webhooks documented
Differentiator (Full vs competitor Partial/None): ✓ Real-time identity resolution (we Full, Segment Partial) ✓ EU data residency (we Full, mParticle None) ✓ Native warehouse sync (we Full, RudderStack Partial) Vulnerability: Throughput at 5K/sec (Segment Full at 50K/sec)
→ Day 1: Draft response sections 1-4 using technical_proposal_template → Day 2: Demo prep — focus on identity resolution + warehouse sync (differentiators) → Day 3: Final review with eng on rate limiting commitment, submit by 5pm
Métricas que mejora
Funciona con
Read RFP documents and store generated technical proposals
Pull deal context, opportunity stage, and competitor mentions for RFP scoring
Alternative CRM source for opportunity and deal data
Store technical proposals, demo scripts, and POC plans in Notion
¿Quieres usar Sales Engineer Skill?
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Inicia Claude Code, luego escribe el comando:
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.
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:
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.
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:
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.
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:
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:
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:
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