Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/zime-ai/zime-gtm-skillsnpx agentmods add skills/zime-ai/zime-gtm-skills/onboarding-journeyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zime-ai/zime-gtm-skills/onboarding-journey)<a href="https://agentmods.dev/skills/zime-ai/zime-gtm-skills/onboarding-journey"><img src="https://agentmods.dev/badge/skills/zime-ai/zime-gtm-skills/onboarding-journey/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zime-ai/zime-gtm-skills/onboarding-journey"><img src="https://agentmods.dev/badge/skills/zime-ai/zime-gtm-skills/onboarding-journey.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.00788 |
| Opus 5 | $0.00033 | $0.00394 |
| Sonnet 5 | $0.00013 | $0.00158 |
| Haiku 4.5 | $0.00007 | $0.00079 |
Grade A, and why
onboarding-journey scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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. Run the reads-well-too check 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.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 94 lines · 66 tokens per session scan A c3b98d263ba4
onboarding-journey is a skill published in the GitHub repository zime-ai/zime-gtm-skills (14 stars, last pushed 17d ago), licensed MIT. It adds 66 tokens to every session and 788 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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