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WEcoS Product Recommendar

A suite of Distributor Lubricant Engineer (DLE) skills for all the fluid product categories.

License: PolyForm Noncommercial 1.0.0 Author AI-assisted Skills


What is this?

WEcoS Product Recommendar is a suite of five Distributor Lubricant Engineer (DLE) skills that produce equivalent / alternative lubricant, coolant, diesel, AdBlue/DEF, and grease recommendations for an incumbent third-party product. It is the cumulative methodology of Aung Khaing Htun, CLS (STLE Certified Lubrication Specialist), refined through years of in-the-field experience across commercial bus, heavy-duty truck, mining, marine, and general industrial applications.

The skills are designed for two audiences:

  • DSRs (Distributor Sales Representatives) who need to cross-reference a competitor product to the right in-house brand / grade, with a defensible technical rationale to share with the end customer.
  • End customers who need a like-for-like equivalent with verified approvals against the latest producer PDS / TDS / SDS.

Why does it exist?

Most DLE workflows suffer from three recurring problems:

  1. Stale specifications. Lubricant producers regularly consolidate, rename, or replace SKUs. A 2022 PDS may still be reachable on a distributor mirror, but the producer has already moved on. The suite enforces a mandatory product-currency check before any recommendation.
  2. Single-pick recommendations. The end-customer often wants to know not just the equivalent, but the upgraded option — and the technical reason. The suite defaults to Standard + Upgraded output for fleet recommendations.
  3. Thickener / chemistry confusion. Greases look the same on the container but behave very differently in service. The suite includes a DIN 51502 / ISO 6743-9 designation decoder plus the ExxonMobil 7×7 thickener compatibility chart (C / M / I matrix) so the recommendation is grounded in chemistry, not brand.

The five skills

# Skill Scope Skill path
1 lubricant-recommender Engine oils, gear oils, hydraulic oils, compressor oils, turbine oils, refrigeration-compressor oils, PAG fluids, heat-transfer fluids lubricant-recommender/SKILL.md
2 coolant-recommender Engine coolants / antifreeze (light-duty, HD diesel, off-highway, marine, stationary gen-set, OEM concentrates) coolant-recommender/SKILL.md
3 diesel-recommender ULSD / EN 590, off-road / mining / construction diesel, additized premium diesel, marine distillate fuels (ISO 8217 DMA / DMZ / DMB) diesel-recommender/SKILL.md
4 adblue-def-recommender AdBlue / DEF / ARLA 32 (ISO 22241 AUS 32 urea solution) for SCR-equipped diesel adblue-def-recommender/SKILL.md
5 grease-recommender Industrial, automotive, food-grade (NSF H1), marine, mining / heavy-load, electric-motor, refrigeration-compressor, central-lube, railway axlebox, high-temperature grease-recommender/SKILL.md

Quick start

Each skill is a standalone module with the same entry contract: provide the incumbent product, application, OEM/model, and operating conditions (where applicable), and the skill produces a Standard + Upgraded recommendation with verified PDS citations.

1. Open a skill

cd lubricant-recommender        # or any of the other 4
cat SKILL.md                     # read the methodology + hard rules

2. Drive the skill from a MuleRun / WEcoS Agent session

In any WEcoS Agents / MuleRun Agent session, just say:

Recommend a Mobil equivalent for Shell Rimula R5 E 10W-40 for a Euro 5 MAN bus operating in Singapore.

The agent loads the relevant SKILL.md, runs §0b currency check, fetches the producer's current PDS, applies the six-axis filter, returns tiered Standard + Upgraded picks, and emits a DSR-ready business email.

3. Read the methodology lineage

For a deep dive on why the pipeline is the way it is — the hard rules, the warning matrix, the tiered output structure, the reference- ledger integration — read:

  • CONTRIBUTORS.md — per-skill authorship + 2026 methodology extensions
  • NOTICE — attribution format + AI-assist credits

Repository structure

wecos-product-recommendar/
├── LICENSE                      # PolyForm Noncommercial 1.0.0 (master)
├── NOTICE                       # attribution format + AI-assist credits
├── CONTRIBUTORS.md              # per-skill authorship lineage
├── README.md                    # you are here
├── CONTRIBUTING.md              # how to contribute
├── .gitignore                   # exclude /output, /__pycache__, etc.
│
├── lubricant-recommender/
│   ├── SKILL.md                 # 233 lines, methodology + hard rules
│   ├── LICENSE                  # pointer to ../LICENSE
│   ├── references/              # sop-flow.md, supplier_catalogs.md, etc.
│   ├── scripts/                 # render_pdf.py, append_record.py, ...
│   ├── templates/               # report_template.md, ...
│   ├── output/                  # generated recommendations (gitignored)
│   └── requirements.txt
│
├── coolant-recommender/        # same internal layout
├── diesel-recommender/         # same internal layout
├── adblue-def-recommender/     # same internal layout
└── grease-recommender/         # same internal layout

Methodology — high-level

Each skill follows the same spine, with branches for the 10 product-line scenarios inside grease-recommender. The full spine is documented in each SKILL.md; the high-level flow is:

User request
   │
   ▼
§0  Hard rules (8 mandatory, no exceptions)
   │
   ▼
§0b Product currency check — confirm SKU is current on producer PDS index
   │
   ▼
§2  Intake — incumbent product, application, OEM, operating conditions
   │
   ▼
§3  Fetch incumbent PDS / TDS / SDS — six attributes + DIN/ISO code
   │
   ▼
§4  Sequential filter — application / base oil / ISO VG / NLGI /
                         thickener / performance + OEM approvals
   │                    (DIN/ISO fallback if no 5+ candidate)
   ▼
§6  Special-case warnings — purge-out-old-grease, base-oil vs NLGI,
                            over-greasing, OEM-specific compatibility,
                            vertical-mount NLGI 3, water exposure, ...
   │
   ▼
§0c Tiered output — Standard Y + Upgraded Y+ with technical rationale
                    (drop point, OEM approval set, drain interval)
   │
   ▼
§7  Deliver — chat report + PDF + Excel row
   │
   ▼
§8  Disclaimer appended verbatim
   │
   ▼
§11 Reference-ledger cross-check (MEM-AUNG-YYYY-NNN format)
   │
   ▼
§11b DSR business email (Gemini-style DDMMYY subject, disclaimer verbatim)

Source-material lineage

Era Source
2024-2025 Base pack: T-SOP-002-1 / 002-2 / 002-3 / 002-4 / 002-5 series (MuleRun Fluids Suite starter kit)
Jul 2026 Methodology extensions (current session): §0b currency check, §0c tiered output, §11 reference-ledger integration, §11b DSR business email template
Jul 2026 Customer corrections (this session): §6 warning ordering (over-greasing first), §6 vertical-mount NLGI 3, §6 shelf-life advisory (cite PDS, no hardcoding), §6 always-on purge standard phrase, §10/§11 ledger + email template additions

AI assistance: WEcoS Agents · MuleRun Agent · Mavis by MiniMax (DLR.1 / Mavis, session #414668884336737, Jul 2026).

See CONTRIBUTORS.md for the full per-skill lineage.


License

This suite is licensed under the PolyForm Noncommercial License 1.0.0.

You are free to:

  • Use the skills for personal study, academic research, internal training, individual professional use, evaluation, contribution back to the upstream project, and integration into non-commercial open-source workflows.
  • Copy, modify, and improve the skills (with attribution to the original author).
  • Contribute back to the upstream project via pull request.

You are not free to use the suite for commercial purposes (sale, OEM integration, paid SaaS deployment, etc.) without a separate written license. See Commercial licensing below.

Canonical license text: polyformproject.org/licenses/noncommercial/1.0.0


Commercial licensing

To use the WEcoS Product Recommendar suite in a commercial product, OEM deployment, paid SaaS workflow, or any revenue-generating context, open a GitHub Issue at:

github.com/AKHtun/wecos-product-recommendar/issues

with the "Commercial licensing" issue template and we'll get back to you within 5 business days.


Contributing

We welcome pull requests. See CONTRIBUTING.md for the PR template, contribution-license agreement, and review process.

In short:

  1. Fork the repo
  2. Branch off main
  3. Commit with a clear message naming the skill + the change
  4. Push and open a PR against main
  5. Sign off your commit (git commit -s) agreeing to license your contribution under the same PolyForm Noncommercial 1.0.0

Trademarks & acknowledgements

All product names, OEM names, and standards-body names mentioned in this suite (e.g., Mobil, Shell, Caltex, TotalEnergies, SPC, Volvo, MAN, MB, Mack, Renault, Scania, DAF, IVECO, MTU, Deutz, Caterpillar, Cummins, Detroit Diesel, ACEA, API, ISO, EN, NEA, ASTM, DIN, IPOS) are the property of their respective owners and are used here in their descriptive sense only. No endorsement or affiliation is implied.

Source-material lineage: ExxonMobil Grease Compatibility Paper (ASTM D6185); DIN 51502 / ISO 6743-9 designation codes; ACEA / API service categories; EN 590; ISO 22241; Volvo VDS / VOLVO 97718; etc.


Author

Aung Khaing Htun, CLS — sole author of the methodology and the integrated WEcoS Product Recommendar suite.


License at a glance

Permission Status
Personal study, academic research, internal training ✅ Yes
Individual professional use ✅ Yes
Contribution back to upstream (PR) ✅ Yes
Modification with attribution ✅ Yes
Commercial use (sale, OEM integration, paid SaaS) ❌ Requires separate written license — open a GitHub Issue
Re-licensing under MIT / Apache / similar permissive license ❌ No
Re-licensing under any closed-source commercial license ❌ No

See LICENSE for the full legal text.

About

Suite of Lubricant Engineer skills for the product recommendation for Lubricants, Fuel, DEF, Engine Coolant, and Grease for Industrial Applications, Commercial Vehicles, and Passenger Vehicles — by Aung Khaing Htun, CLS

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