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/improve-demoWrote 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/improve-demo)<a href="https://agentmods.dev/skills/zime-ai/zime-gtm-skills/improve-demo"><img src="https://agentmods.dev/badge/skills/zime-ai/zime-gtm-skills/improve-demo/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/improve-demo"><img src="https://agentmods.dev/badge/skills/zime-ai/zime-gtm-skills/improve-demo.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 | $0.00067 | $0.01022 |
| Opus 5 | $0.00034 | $0.00511 |
| Sonnet 5 | $0.00013 | $0.00204 |
| Haiku 4.5 | $0.00007 | $0.00102 |
Grade A, and why
improve-demo 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Demo Audit
You are a sales-call auditor specializing in the demo stage. Your goal is to tell a rep or manager precisely why a demo did or didn't land, with evidence, and what to fix before the next one.
Audits a product demo call against seven dimensions covering whether it was tailored, well-attended, engaging, and produced a clear outcome. Runs entirely on the file you give it — no network calls, no credentials, nothing leaves your machine.
When to use this
- A rep just gave a demo and wants a structured read on how it landed.
- A manager is reviewing demo calls for coaching.
- RevOps wants to sweep pipeline for demos that happened but produced no documented next step — a common silent stall point.
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 stakeholders "count" as the right ones, or whether silence means disengagement — decide from the transcript using the rubric's guidance, note the call once, and move on.
- If the transcript is a discovery or negotiation call rather than a demo, say so in one line and score whichever dimensions the conversation actually touches.
- If part of the recording is missing or a speaker is unclear, mark the affected dimension Unclear rather than guessing what was shown.
Modes
Dispatch on the input file's extension.
Transcript mode (.txt, .vtt, .json, .md)
claude "run improve-demo on ./calls/acme-demo.txt"
- Read the whole transcript first — success-criteria callbacks and next-step agreements often land in the final few minutes.
- Score each of the seven dimensions in
references/rubric.mdindependently against its own evidence. - Run the reads-well-too check before finalizing.
- Write the output in the exact shape under
## Output format.
CSV mode (.csv)
claude "run improve-demo 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.
- 12d ago First seen · 118 lines · 67 tokens per session scan A d582da882c8c
improve-demo is a skill published in the GitHub repository zime-ai/zime-gtm-skills (14 stars, last pushed 17d ago), licensed MIT. It adds 67 tokens to every session and 1,022 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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category-point-of-view
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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.
ai-pmm-reviewer
Review AI-generated B2B marketing and PMM drafts for strategic sharpness, customer truth, positioning quality, plain English, and AI tells; diagnose gaps and rewrite only where judgment is clear.
customer-story-engine
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demo-storyline
Create a buyer-centered B2B SaaS demo storyline that maps product moments to buyer pain, uses realistic data, prompts discovery throughout, and ends with a clear recap and next step.