Atlas / Skills / leoyeai / Sales Engineer

Sales EngineerSAFE

skills/leoyeai/sales-engineer

🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
1 documented
License
MIT
Stars
2,160
01

Overview

🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai

Read from source at commit 4f3b4a2a472eOBSERVED · 2026-10-08
02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
openclawmentioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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    
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeWARN
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (3)

MEDIUMObfuscation / stealth · obf.base64_blob · CWE-506, CWE-94
skills/compdf-conversion-cli/scripts/license.xml:9
<key>k5Ey9KFlkqpj+SDkUw+5ED9lTA3En/qUi0zdrydUCH3kMWTE3Eh65NXnFCaxlY2omY2JHnlEoK7Li7oOEvM7eG5VPdcO/sFlMfoCRdnLYdepJ+uLzYwOWR8W4yQVve/clxVFTVRL4DFleKInGdpAxIbHZT2yi4ADAMENls1N1XSLojRuqXePXDeAT/4Mv4TTx0s
LOWPrompt injection · prompt.credential_read · CWE-94, CWE-1427
assets/demo_script_template.md:209
- [ ] Share demo environment access credentials (if applicable)
Why it matters. asks the agent to read credentials
LOWPrompt injection · prompt.credential_read · CWE-94, CWE-1427
references/poc-best-practices.md:84
- Request customer IT support for integration access and credentials
Why it matters. asks the agent to read credentials

Gates applied: no_behavioural_pass.

Audited 2026-10-08 · audit v0.4.1 · source sha 4f3b4a2a472efull audit observations/trust-audit/skill/leoyeai__sales-engineer.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-084f3b4a2a472eSAFEB89first audit
06

Questions

What does the Sales Engineer skill do?

🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai

Is Sales Engineer safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Sales Engineer access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does Sales Engineer work with?

Its documentation mentions openclaw. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (4f3b4a2a472e), read on 2026-10-08. The repository is watched, and a new audit runs when it changes — this is the first audit.

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