research

name

research

description

Survey how best-in-class ERPs and point solutions implement a feature, and produce a findings file at .ai/research/{slug}.md. Use when designing a new feature, evaluating approaches, or answering "how do competitors / SAP / the industry do X". Required before designing any ERP-domain feature (accounting, costing, tax, inventory valuation, RMA, MRP, etc.). Do not use for UI styling questions (copy an existing Carbon screen instead) or for bugs (use root-cause).

research — competitor best-practice survey

Input: a feature or domain question. Output: .ai/research/{feature-slug}.md with consensus patterns and a recommendation for Carbon. This skill only researches and writes the findings file — it does not design, plan, or write code.

Announce at start: "Using the research skill — surveying how competitors handle {feature}."

Step 1: Classify the domain

Match the request against this table. A feature may match multiple rows (e.g. "shop floor inspections" → MES + Quality). Research every matching row.

Domain	Always	Also research	Keywords
Accounting	SAP	NetSuite	GL, AP, AR, invoicing, payments, accruals, journal entries, period close, financial reports
Discrete manufacturing	SAP	Epicor	job shops, work orders, BOMs, routing, job costing
MES / production tracking	SAP	Manufacturo, First Resonance	real-time tracking, dispatch, machine monitoring, scheduling
CNC parts / sheet metal	SAP	Fulcrum, Paperless Parts	quoting, estimating, nesting, RFQ
Quality	SAP	1factory, HighQA	inspection, SPC, FAI, PPAP, GD&T, NCR
Inventory	SAP	NetSuite, Fishbowl	valuation, lots, cycle counting, warehouses
Sales / CRM	SAP	NetSuite, Salesforce	quotes, orders, pricing, commissions
Purchasing	SAP	NetSuite, Coupa	POs, suppliers, receiving, procurement
Anything else	SAP	discover first	search best <domain> software and pick the top 2 leaders before deep research

SAP is always included — it is the reference for enterprise patterns even when point solutions are more innovative.

Step 2: Write the research questions

Before searching, list 3–6 concrete questions the design will need answered. Prefer data-model and workflow questions over UI questions:

• What entities and status lifecycles does the competitor use?
• What edge cases do they handle that we might miss?
• Is there an industry-standard term we should adopt instead of inventing one?

Step 3: Search

For each competitor, run searches shaped like:

• <Competitor> <feature> documentation
• <Competitor> <feature> how it works
• <Competitor> <feature> best practices

Rules:

• Be specific: SAP S/4HANA inventory valuation methods, not SAP inventory.
• Fan searches out to subagents (one competitor or one question per subagent) to keep the main context clean. Each subagent returns findings + source URLs only.
• Focus on data models, workflows, and terminology — not screenshots or UI copy.

Step 4: Write the findings file

Save to .ai/research/{feature-slug}.md (kebab-case slug). Use exactly this structure:

# {Feature} Research: Best Practices Survey

## Summary
One paragraph: what was researched, key findings.

## Competitors Surveyed
- **SAP S/4HANA** — {why relevant}
- **{Competitor}** — {why relevant}

## Key Consensus Patterns
### 1. {Pattern name}
- **SAP**: {how SAP does it}
- **{Competitor}**: {how they do it}
- **Rationale**: {why this is the standard}

## Answers to Research Questions
1. {Question} — {answer, citing which competitor}

## Competitor-Specific Details
### {Competitor}
{notable configuration options, terminology, unique approaches}

## Recommended Approach for Carbon
1. {Recommendation with rationale, naming the competitor pattern it follows}

## Sources
- {URL}

Done when

• Every matching domain row was researched, SAP included
• Every research question from Step 2 has an answer (or is explicitly marked unanswered — carry it into the spec's Open Questions)
• The findings file exists at .ai/research/{slug}.md with all sections filled
• Every claim has a source URL in the Sources section

Next step

Hand the findings file to /spec-writing (design + spec) or cite it from an existing spec. Do not start implementation from research alone.