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Build TOPdesk AI/KI adoption ledgers and monitoring summaries from suggestion logs, operator feedback, acceptance/edit/rejection events, override reasons, confidence, cost estimates, prompt/model versions, and value assumptions.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
TOPdesk Action Sequences and automation design. Use for action sequence triggers, webhooks, API calls, payload mapping, idempotency, retries, error handling, safe automation boundaries, audit logging, and automation monitoring.
TOPdesk administration and configuration design. Use for categories, statuses, priorities, impact/urgency, supporting files, branches, persons, operators, operator groups, permissions, SSP forms, service catalog items, change templates, asset templates, knowledge visibility, and configuration governance.
Generate complete governed AI/KI feature packs for TOPdesk. Use for turning an AI use case into feature scope, data contract, prompt design, JSON output schema, evaluation dataset, feedback loop, audit fields, rollout gates, Power BI monitoring measures, RLS/PII controls, and operator-facing acceptance criteria.
Design Power BI governance cockpits for TOPdesk AI/KI features. Use for AI monitoring datasets, semantic models, DAX measures, report pages, prompt/model version tracking, suggestion acceptance, override reasons, confidence drift, cost, token usage, SLA impact, PII/policy findings, feedback loops, evaluation results, RLS, and audit reporting.
Design, implement, and evaluate AI/KI features for TOPdesk workflows. Use for ticket classification, smart routing, summaries, response suggestions, knowledge article generation, semantic search, RAG, chatbot/self-service assistants, duplicate detection, SLA-risk prediction, prompt templates, JSON schemas, operator feedback loops, AI governance, and regression evaluation.
Use when testing live TOPdesk REST/API access, authentication, endpoint availability, paging behavior, response status codes, payload shapes, demo tenants, smoke tests, regression checks, and API readiness before building Power BI, Python, PowerShell, or AI features.
| name | topdesk-ai-adoption-ledger |
| description | Build TOPdesk AI/KI adoption ledgers and monitoring summaries from suggestion logs, operator feedback, acceptance/edit/rejection events, override reasons, confidence, cost estimates, prompt/model versions, and value assumptions. |
Use this skill when an AI pilot needs measurable adoption evidence from suggestion and feedback logs.
scripts/build_ai_adoption_ledger.py to normalize rows and produce adoption metrics.ai-adoption-ledger.csvai-adoption-summary.mdreferences/ai-adoption-ledger.md for metric definitions and interpretation.