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Get Started Free →Run CRM and member retention via LINE Official Account — broadcast cost model, rich menu, auto-response, tagging, 1-to-1 chat, and LINE Pay integration. Use when designing LINE OA strategy for a TW brand, segmenting members for broadcasts, or measuring LINE OA ROI. Do NOT use for generic CRM (use `ecom-rfm-analysis` or `biz-cac-ltv`). STATUS: SKELETON — body pending.
.claude/skills/asgard-ai-platform-tw-ecom-operations-line-oa/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✓→✓ | ＝ Same ✓ | 17% | 0% |
| case-05 | ✓→✓ | ＝ Same ✓ | 33% | 0% |
| case-02 | ✓→✓ | ＝ Same ✓ | 109% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | -19% | 0% |
| case-06 | ✓→✓ | ＝ Same ✓ | 70% | 0% |
> STATUS: SKELETON — body pending.
ecom-rfm-analysisbiz-cac-ltvTODO: LINE OA tier pricing (輕用量 / 中用量 / 高用量), broadcast vs narrowcast cost asymmetry, tagging strategy.
TODO: member behavior → tag → channel.
TODO: onboarding flow, tagging logic, broadcast template, ROI measurement.
TODO: 5-6 pitfalls (tier upgrade mid-month cost, blocked-user bloat, PDPA consent for broadcast, 1-to-1 latency during peak, LINE Notify deprecation impact).
TODO.
TODO.
ecom-rfm-analysistw-ecom-compliance-pdpa_Last verified: 2026-04_
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-04 | pass→pass | 41,896 | 42,541 | +2% | 1 | 1 | 0% | 1,736 | 2,025 | +17% | 0 | 0 | — |
case-05 | pass→pass | 39,602 | 11,243 | -72% | 1 | 1 | 0% | 1,607 | 2,143 | +33% | 0 | 0 | — |
case-01 | fail→fail | 48,174 | 54,472 | +13% | 1 | 1 | 0% | 2,816 | 3,710 | +32% | 0 | 0 | — |
case-02 | pass→pass | 22,539 | 63,962 | +184% | 1 | 1 | 0% | 3,194 | 6,661 | +109% | 0 | 0 | — |
case-03 | pass→pass | 16,073 | 14,341 | -11% | 1 | 1 | 0% | 3,401 | 2,742 | -19% | 0 | 0 | — |
case-06 | pass→pass | 4,697 | 37,180 | +692% | 1 | 1 | 0% | 841 | 1,433 | +70% | 0 | 0 | — |
case-07 | pass→pass | 18,444 | 17,574 | -5% | 1 | 1 | 0% | 2,469 | 2,643 | +7% | 0 | 0 | — |
case-08 | pass→pass | 26,024 | 17,951 | -31% | 1 | 1 | 0% | 1,941 | 2,599 | +34% | 0 | 0 | — |
case-09 | pass→pass | 22,596 | 30,934 | +37% | 1 | 1 | 0% | 2,448 | 4,448 | +82% | 0 | 0 | — |
case-10 | pass→pass | 13,956 | 15,748 | +13% | 1 | 1 | 0% | 2,361 | 2,715 | +15% | 0 | 0 | — |
case-11 | pass→pass | 21,740 | 22,186 | +2% | 1 | 1 | 0% | 3,062 | 3,385 | +11% | 0 | 0 | — |
case-12 | pass→pass | 16,315 | 19,069 | +17% | 1 | 1 | 0% | 2,491 | 2,721 | +9% | 0 | 0 | — |
case-13 | pass→pass | 25,059 | 23,933 | -4% | 1 | 1 | 0% | 3,235 | 3,477 | +7% | 0 | 0 | — |
case-14 | pass→pass | 10,322 | 15,964 | +55% | 1 | 1 | 0% | 1,674 | 2,312 | +38% | 0 | 0 | — |
case-15 | pass→pass | 18,664 | 18,105 | -3% | 1 | 1 | 0% | 2,998 | 2,983 | -1% | 0 | 0 | — |
case-16 | pass→pass | 12,751 | 14,822 | +16% | 1 | 1 | 0% | 2,188 | 2,692 | +23% | 0 | 0 | — |
case-17 | pass→pass | 11,860 | 12,225 | +3% | 1 | 1 | 0% | 1,670 | 2,049 | +23% | 0 | 0 | — |
case-18 | pass→pass | 11,084 | 13,746 | +24% | 1 | 1 | 0% | 2,081 | 2,318 | +11% | 0 | 0 | — |
case-19 | pass→pass | 9,229 | 6,155 | -33% | 1 | 1 | 0% | 1,516 | 1,302 | -14% | 0 | 0 | — |
case-20 | pass→pass | 18,102 | 17,277 | -5% | 1 | 1 | 0% | 2,891 | 2,952 | +2% | 0 | 0 | — |
case-21 | pass→pass | 11,095 | 14,165 | +28% | 1 | 1 | 0% | 1,790 | 2,418 | +35% | 0 | 0 | — |
case-22 | pass→pass | 16,314 | 23,485 | +44% | 1 | 1 | 0% | 2,731 | 3,771 | +38% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of 0 percentage points is the difference between those two pass rates over the 22 comparable cases.
Other measured skills in the registry, with their headline benchmark lift.