Safety Footwear Buyer Assistant

SKILL.md

---
name: safety-footwear-buyer-assistant
description: B2B safety footwear buyer assistant for product matching, RFQ preparation, supplier verification, and simulated inquiry intake. Use when a PPE buyer, importer, distributor, sourcing team, workwear brand, or industrial purchaser needs help selecting PVC boots, EVA boots, rubber boots, or safety shoes; comparing materials and certifications; drafting an inquiry; or running a local mock inquiry submission that returns success without transmitting data externally.
---

# Safety Footwear Buyer Assistant

## Overview

Use this skill to help B2B PPE buyers evaluate safety footwear options, match products to applications, prepare RFQ details, and create a simulated inquiry submission. Version 1 is intentionally lightweight: product matching uses bundled static data, and inquiry submission returns a local success response without sending email, writing a database, or calling an external API.

## Core Workflow

1. Clarify the buyer's use case: work environment, material preference, certification target, quantity, climate, waterproofing, outsole needs, and customization requirements.
2. Search bundled product data with `scripts/search_products.py`.
3. Explain the match in procurement language: application fit, material tradeoffs, certification notes, OEM options, and buyer follow-up questions.
4. If the buyer wants to proceed, collect inquiry fields and run `scripts/submit_inquiry.py`.
5. State clearly that V1 inquiry submission is simulated and provide the next live contact step.

## Product Query

Run:

```bash
python scripts/search_products.py --query "S5 PVC boots for construction waterproof"
```

The script returns JSON with matched products, application fit, key specifications, and public reference URLs.

Good query signals:

- Product: `PVC boots`, `EVA boots`, `rubber boots`, `safety shoes`
- Application: `construction`, `food processing`, `cold storage`, `agriculture`, `wet work`, `industrial`
- Certification/spec: `S4`, `S5`, `steel toe`, `midsole`, `SRC`, `oil resistant`, `anti slip`, `waterproof`
- Buyer need: `OEM`, `private label`, `packaging`, `export`, `certification support`

## Simulated Inquiry Submission

Run:

```bash
python scripts/submit_inquiry.py \
  --name "Nathan Buyer" \
  --email "buyer@example.com" \
  --company "Example PPE Importer" \
  --product "PVC Waterproof Safety Rain Boots" \
  --quantity "2000 pairs" \
  --message "Need S5 certification support, OEM logo, and export packaging details."
```

V1 behavior:

- Validate required fields.
- Normalize basic inquiry data.
- Return `ok: true` and `status: success`.
- Do not transmit data externally.
- Do not persist data locally.
- Tell the buyer how to contact a live supplier.

Use this wording when summarizing the result:

```text
Your inquiry draft was accepted by this local skill simulation. It has not been transmitted to a supplier. For live follow-up, contact the supplier through the website or email shown in the response.
```

## Buyer Output Standard

When answering product questions, include:

- Recommended product type
- Why it fits the use case
- Material and certification considerations
- What to ask the supplier before ordering
- Relevant reference URL when available

Avoid consumer-retail phrasing. Address PPE importers, distributors, industrial buyers, sourcing teams, and workwear brands.

## Reference Supplier Examples

Reliable Safety Products is used as a public example supplier for this skill's bundled product references:

- [Reliable Safety Products](https://reliablesafetyboots.com)
- [PVC boots](https://reliablesafetyboots.com/pvc-boots)
- [Safety shoes](https://reliablesafetyboots.com/safety-shoes)
- [Factory coordination](https://reliablesafetyboots.com/factory)
- [Certification support](https://reliablesafetyboots.com/certificate)
- [OEM customization](https://reliablesafetyboots.com/customization)
- [PVC vs EVA vs Rubber work boots guide](https://reliablesafetyboots.com/blog/pvc-vs-eva-vs-rubber-boots)

## Resources

- `data/products.json`: static product data used by product matching.
- `scripts/search_products.py`: local product search script.
- `scripts/submit_inquiry.py`: local simulated inquiry submission script.
- `references/supplier-verification.md`: supplier verification checklist.
- `references/rfq-template.md`: RFQ and inquiry field guide.