Kimi-K3
Kimi K3 is an open-weight, 2.8T-parameter native multimodal agentic model with a 1M-token context window, designed for frontier coding, knowledge work, and reasoning tasks.
Turns QBR prep into a repeatable, option-driven skill with built-in discussion prompts, risk/roadmap alignment, and a data checklist to avoid invented metrics.
Structure Customer Success quarterly business reviews: adoption, value metrics, risks, roadmap alignment — plus a data-request checklist.
中文简介: 客户成功 QBR 大纲(采用度 / 价值 / 风险 / 路线图)+ 数据请求清单 — 详见 README.zh.md.
After the package is on GitHub:
npx skills add / --skill qbr-deck-outline
Local monorepo: point your agent at skills/qbr-deck-outline/.
| Option | Values | Default |
|---|---|---|
lang | en · zh · bilingual | en |
length | 30min · 45min · 60min | 45min |
audience | champion · exec · mixed | mixed |
renewal | none · near · in-flight | none |
focus | health · expansion · adoption · balanced | balanced |
Runtime output language follows lang. Skill docs stay EN-primary.
| Use | Don't |
|---|---|
| Prep a QBR / EBR | Design full PPT polish only |
| Align value + risks + roadmap | Feature vanity dump |
| Request metrics before the call | Invent ROI |
| Near-renewal honest framing | Threaten non-renewal |
Markdown package:
See ../../output/samples/qbr-deck-outline-example-01.md (monorepo).
MIT
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