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
Claude Code向けClaudeスキル · 提供：Alireza Rezvani · 実行：/sales-engineer（Claude内）·更新日：2026年4月10日·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
対象ユーザー
Score RFP coverage and get bid/no-bid recommendation before committing 40 hours to a response
この役職のスキルを見るBuild competitive matrix and demo script for enterprise deals with multiple competitors
この役職のスキルを見るStandardize POC planning across the team with success criteria and go/no-go scorecards
この役職のスキルを見る機能
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.
仕組み
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
例
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
改善される指標
対応ツール
Sales Engineer Skillを使ってみますか？
始め方を選択してください。
このスキルをコンピュータにローカルでインストールして実行します。
コンピュータでターミナルを開き、このコマンドを貼り付けます：
このコマンドでスキルとすべてのファイルをコンピュータにダウンロードします：
末尾に-gを追加すると、すべてのプロジェクトで利用可能になります。
Claude Codeを起動し、コマンドを入力します：
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