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/next-step-commitmentWrote 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/next-step-commitment)<a href="https://agentmods.dev/skills/zime-ai/zime-gtm-skills/next-step-commitment"><img src="https://agentmods.dev/badge/skills/zime-ai/zime-gtm-skills/next-step-commitment/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/next-step-commitment"><img src="https://agentmods.dev/badge/skills/zime-ai/zime-gtm-skills/next-step-commitment.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 | $0.00065 | $0.01060 |
| Opus 5 | $0.00032 | $0.00530 |
| Sonnet 5 | $0.00013 | $0.00212 |
| Haiku 4.5 | $0.00006 | $0.00106 |
Grade A, and why
next-step-commitment 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 11d 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Next-Step-Commitment Audit
You are a sales-call momentum auditor. Your goal is to tell a rep or manager whether a call ended in a commitment strong enough to actually move the deal, or just felt like it did.
A narrow, single-question skill: did the call close with a specific
action, a date or trigger, and two-sided ownership — the three elements in
references/rubric.md — or does it just read that way. Runs on any call,
any stage; the bar is the same at discovery and at late-stage negotiation,
only the subject matter changes.
When to use this
- A manager reviewing a call wants to know if it actually ended in something concrete, not just a good conversation.
- A rep wants a gut-check before marking a deal "next step: scheduled."
- RevOps wants to sweep a pipeline export for deals that have gone quiet because the last call never locked down a real next step.
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 file or which call — decide from what's there, note the assumption once, and move on.
- If the transcript ends mid-conversation or is cut off before a close, score what's there and say so rather than guessing at how it ended.
- Score only the call's ending against next-step commitment — pain, qualification, and rapport are out of scope; that's what the other skills in this repo are for.
Modes
Transcript mode (.txt, .vtt, .json, .md)
claude "run next-step-commitment on ./calls/call.txt"
- Read the transcript's ending — the last few exchanges before the call closes out.
- Score it against the three elements in
references/rubric.md: specific action, date or concrete trigger, two-sided ownership. - Run the rubric's reads-well-too check before finalizing.
- Write the output in the exact shape under
## Output format.
CSV mode (.csv)
claude "run next-step-commitment on ./exports/pipeline.csv"
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.
- 11d ago First seen · 113 lines · 65 tokens per session scan A 176dfccb76ec
next-step-commitment is a skill published in the GitHub repository zime-ai/zime-gtm-skills (14 stars, last pushed 15d ago), licensed MIT. It adds 65 tokens to every session and 1,060 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.
Other skills, from other repositories
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b2b-pmm-orchestrator
Route vague B2B product marketing requests to the right PMM skill, sequence multiple skills into intelligent GTM workflows, and keep the agent focused on the smallest useful artifact that moves the business forward.
category-point-of-view
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ai-pmm-reviewer
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customer-story-engine
Capture true customer stories and turn them into plain-spoken B2B story assets: story briefs, case studies, one-page PDFs, website posts, and sales proof.
sales-narrative-deck
Create a sales-ready B2B narrative deck outline that starts with buyer pain, teaches the market, shows the solution, supports a demo, and gives reps a clear path to proof, pricing, competition, recap, and next steps.