Diagnostic Field Discovery Engineer

Problem

For ToB customer work, the usual gap is not a lack of tools, but fragmented industry data, weak competitive evidence, unclear requirement-to-capability mapping, and deliverables that miss architecture, ROI, POC, and reviewable docs. Diagnostic Field Discovery Engineer turns these tasks into a structured workflow, letting engineers produce an evaluation-ready solution package in an unfamiliar industry.

How It Works

The skill moves through phases and orchestrates sub-skills plus scripts:
- Discovery: use research-summarizer for industry reports, competitive-teardown for 12-dimension competitor scoring and SWOT, and product-discovery for customer assumption mapping.
- Requirements and capability matching: use product-manager-toolkit for RICE prioritization, then run capability_match.py and gap_analysis.py to mark coverage against Tencent Cloud capabilities.
- Solution output: generate Mermaid architecture diagrams, ROI estimates, Why-Us analysis, POC scope, Now/Next/Later roadmap, plus executive summary, deck, and technical proposal.

Fit and Caveats

It fits engineering or architecture collaboration where the ToB industry, customer, or scenario is already defined and the goal is to produce reviewable solution materials. It is not for pure code implementation, live ops, or open-ended brainstorming without business context. The more concrete the inputs—customer, pain points, competitors, budget—the more useful the output.