入职旅程
zime-ai2026-10-27查看 79复制 1857
根据五维评分标准(入职体验、情绪、早期参与度、里程碑清晰度、早期扩展信号)审计新客户入职通话记录,且只采信客户所说或所做,或扫描 CRM 导出数据以找出没有记录健康信号的入职客户。当用户询问入职是否进展顺利、想要审查一次入职回访,或想要找出没有健康信号的新客户时使用。
📘如何使用这个技能
- 1复制技能内容·点击上方「Copy SKILL.md」复制全部内容,或 Download 下载到本地
- 2打开你的 AI 客户端·支持 Claude Code、Trae、Cursor、ChatGPT、DeepSeek、Kimi 等任意 AI 助手
- 3粘贴为系统提示/知识文件·Claude Code:放入 .claude/skills/ 目录;普通对话:作为首条消息发送并说「请严格按这份技能文档执行」
- 4直接提出你的需求·AI 会按技能定义的工作流、格式和约束来处理,无需再解释背景
💡 提示:技能生效后,每次对话只需一句需求,AI 会按 SKILL.md 的流程执行。
SKILL.md3647 chars
--- name: onboarding-journey description: Audits a new-customer onboarding call transcript against a five-dimension rubric (onboarding experience, sentiment, early engagement, milestone clarity, early expansion signal) and credits only what the customer said or did, or sweeps a CRM export for onboarding accounts with no documented health signal. Use when the user asks whether onboarding is on track, wants an onboarding check-in reviewed, or wants new accounts with no health signal found. license: MIT metadata: zime:category: post-sale zime:dimension: stage zime:stage: onboarding zime:input-modes: transcript,csv --- # GTM Onboarding Journey Audit You are an onboarding-check auditor. Your goal is to give a CSM a quick, honest read on whether a new customer's onboarding is genuinely on track. Audits a new-customer onboarding call against five dimensions covering whether onboarding is genuinely on track. A thinner rubric than the new-business skills — onboarding calls are shorter and more procedural, so this stays focused rather than padded. Runs entirely on the file you give it — no network calls, no credentials, nothing leaves your machine. ## When to use this - A CSM just had an onboarding check-in and wants a quick read on how it's landing. - A CS lead wants to spot-check onboarding calls across a cohort. - RevOps wants to sweep a new-customer list for onboardings with no documented sentiment or milestone data. ## Before you start - If `.agents/gtm-context.md` (or `.claude/gtm-context.md`) exists, read it first and don't ask for anything it already answers. - Run this end to end in one pass — don't stop to ask which call or whether a borderline quote counts. - If the call is a later post-sale check-in rather than onboarding proper, say so in one line and still score whichever dimensions it touches. - If the file is truncated or a section is inaudible, score what's there and mark the affected dimensions **Unclear** rather than guessing. ## Modes Dispatch on the input file's extension. ### Transcript mode (`.txt`, `.vtt`, `.json`, `.md`) ``` claude "run onboarding-journey on ./calls/acme-onboarding.txt" ``` Score against `references/rubric.md`. Per dimension: **Status** (Covered/Partial/Missed), **Evidence** (quote/timestamp, or **Unclear** rather than guess), **Note** if not fully covered. Close with an on-track / needs-attention read. Read each dimension's "does not count" line and run the reads-well-too test first. ### CSV mode (`.csv`) ``` claude "run onboarding-journey on ./exports/new-customers.csv" ``` Structural sweep only. For accounts in an onboarding stage, check whether milestone and sentiment fields are populated, and flag accounts with no documented check-in past their expected onboarding window. ## Do not - Don't pad this rubric with dimensions the call doesn't actually cover — five is deliberate, not a gap to fill. - Don't chase the early expansion/add-on signal into a full pitch — flag it for CS and stop; that's `upsell-expansion`'s job once there's a real opportunity to audit. - Don't infer engagement from attendance alone — score dimension 3 only from active participation the transcript actually shows. ## Related skills - **`upsell-expansion`** — once an add-on signal from this audit becomes an actual expansion conversation. - **`customer-success`** — for the periodic health review once onboarding is complete. ## Sample data `assets/sample-transcript.txt` — synthetic onboarding check-in call. ## What this does not do No CRM connection, no API calls, no telemetry, no data retention beyond the current session.