arthai-marketplace

/opportunity-map

Map AI opportunities by ROI and effort, recommend target orgs.

Synopsis

/opportunity-map <client-name>

When to use it

After discovery, to turn pain points and readiness data into a prioritized list of AI initiatives
Building the priority matrix and phased roadmap that anchors the proposal
Not for: dollar-level financial modeling of an initiative — that’s /roi-calculator; or gathering the underlying client data — that’s /client-discovery

Quickstart

/opportunity-map acme-corp

What you’ll see: 8-15 candidate AI initiatives generated from the client’s pain points, each scored and ranked, a 2x2 impact/effort matrix, a three-wave roadmap, and department-level recommendations written to the client’s assessment directory.

Examples

/opportunity-map acme-corp     # the single invocation form — reads discovery, writes assessment

What it does

Loads discovery data — reads clients/<client-name>/discovery/ and profile.md; extracts pain points, goals, tech stack, readiness scores, maturity level, budget, and timeline. If discovery/intake.md, current-state.md, or maturity-assessment.md are missing, it stops and tells you to run /client-discovery first.
Generates AI initiatives — 8-15 candidates using Jobs-to-Be-Done framing: at least 2 per pain point, a mix of Automation / Insight / Generation / Prediction types, at least 2 quick wins and 1 moonshot, calibrated to the client’s maturity level.
Scores every initiative — weighted formula across 6 factors: Revenue Impact (25%), Cost Savings (20%), Feasibility (20%), Time to Value (15%), Strategic Alignment (10%), Risk inverse (10%). Scores classify as Must-Do / Should-Do / Could-Do / Defer, each with a written justification.
Priority matrix — an ASCII 2x2 impact/effort matrix (Quick Wins, Strategic Bets, Fill-Ins, Money Pits) plus a ranked priority table.
Three-wave roadmap — Wave 1 Quick Wins (Month 1-2), Wave 2 Foundation Building (Month 3-4), Wave 3 Strategic Bets (Month 5-6), with deliverables, dependencies, resources, and success metrics per wave.
Capability mapping — maps the toolkit’s actual agent ecosystem to each client department: which agents and skills deploy where, a concrete in-practice scenario, and a week-one quick win per department, plus cross-department synergies.

Output & artifacts

Written to clients/<client-name>/:

assessment/opportunity-matrix.md — initiative catalog, factor-by-factor scoring, ASCII priority matrix, ranked table, justifications
assessment/roadmap.md — three-wave roadmap, timeline visualization, dependencies, budget summary, KPIs, risk register per wave
assessment/department-recommendations.md — per-department agent/skill briefs, synergies, change-management and governance recommendations

Troubleshooting

Problem	Fix
`Discovery data not found for <client-name>`	Run `/client-discovery <client-name>` first — this skill requires intake, current-state, and maturity files
Initiatives feel too ambitious for the client	Expected guardrail: maturity below 10 biases toward simpler initiatives; budget under $50K restricts to quick wins on existing tools
An initiative needs data the client doesn’t have	The skill flags these — they need a data acquisition plan before they’re roadmap-ready
Scores look arbitrary	Every score must trace to discovery evidence — if one doesn’t, challenge it and regenerate

/consulting — the engagement orchestrator; runs this as the assess phase
/client-discovery — produces the discovery data this skill requires
/roi-calculator — next step: financial models for the top-scored initiatives
/pitch-generator — folds the matrix and roadmap into the proposal