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SkillsMP a collecté 8 skills depuis adobe/adobe-retail-partnerships-ai-kit. Ouvrez un skill pour examiner sa source et ses détails.
Affichage de 8 skills collectés sur 8.
Analyze the partner's existing codebase across all detected surfaces and write service cards into service-cards/ — one per-surface card set (backend/, plus a UI set in mobile/, web/, ios/, or android/), always the shared context in shared/, and a…
Langue du texte source : anglais
Produce a fully branded, runnable partner app from partner-supplied mocks by reproducing the partner's UI on top of a reference app that already contains all the Adobe integration capabilities (claim, find-subscription, cancel, notify). Every partner's UI is…
Langue du texte source : anglais
Generate production-ready Adobe backend clients in the partner's existing backend stack: Phase 0 — a reviewable design approved before any code is written; Phase 1 — the IMS OAuth token service; Phase 2 — the typed Adobe Integration API client (Workflow, Get…
Langue du texte source : anglais
Generate a complete .env.example with all required Adobe integration variables, add .env to .gitignore, and add startup config validation to the backend.
Langue du texte source : anglais
Scan the entire codebase and produce a definitive integration checklist — what's done, what's partial, and what's missing. Share this with Adobe partner engineering when requesting stage access review.
Langue du texte source : anglais
Generate reviewable backend and UI Low-Level Designs (LLDs) for one feature, before any code is written — Phase A (backend LLD, the DG-3 gate) then Phase B (UI LLD, the DG-4 gate). See ../../manual/methodology/card-model.md#lld-section-contract and…
Langue du texte source : anglais
Generate comprehensive unit and integration tests for all Adobe integration code, using the partner's existing test framework and patterns.
Langue du texte source : anglais
Implement one Adobe integration feature end-to-end across all detected surfaces (backend route, mobile/native screen(s), web component(s)), from the feature's approved LLD, following the target repo's own conventions.
Langue du texte source : anglais