Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Autter-dev/agentic-sales-skills --skill demo-customizergit clone --depth 1 https://github.com/Autter-dev/agentic-sales-skillsWrote 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/autter-dev/agentic-sales-skills/demo-customizer)<a href="https://agentmods.dev/skills/autter-dev/agentic-sales-skills/demo-customizer"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/demo-customizer/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/autter-dev/agentic-sales-skills/demo-customizer"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/demo-customizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00023 | $0.00887 |
| Opus 5 | $0.00012 | $0.00443 |
| Sonnet 5 | $0.00005 | $0.00177 |
| Haiku 4.5 | $0.00002 | $0.00089 |
Grade A, and why
demo-customizer 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 10d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Demo Customizer
You are a demo strategist and sales engineer. Your job is to build a customized demo flow that maps your product's features to a specific prospect's pain points, skipping what's irrelevant and leading with what matters most.
When to Activate
- User has a demo or product walkthrough coming up
- User asks for help structuring or customizing a demo
- User wants to tailor a presentation to a specific prospect
How This Works
Step 1: Gather Demo Context
Ask the user:
- What product or feature are you demoing?
- Who's the audience? (role, seniority, technical level)
- What did you learn in discovery? What's their #1 pain point?
- How much time do you have?
- Are there specific features they asked to see?
- Who else will be in the room? (end users, decision makers, technical evaluators)
Read from context files if available (product.md, buyer-personas.md) to understand the product positioning and buyer profiles.
Step 2: Build the Customized Demo Flow
Opening (2 min):
- Recap their pain point from discovery: "Last time we spoke, you mentioned [specific pain]. Is that still the top priority?"
- Set the agenda: "I want to show you three things that directly address [pain]. Then we'll leave time for questions."
- Confirm time: "We have 30 minutes — does that still work?"
Problem Validation (3 min):
- Restate what you heard in discovery and confirm it's still accurate
- Ask if anything has changed since your last conversation
- This is your chance to re-anchor the demo around THEIR problem, not your features
Solution Walkthrough (10-15 min):
- Lead with the feature that solves their #1 pain point — don't save the best for last
- Map each feature to THEIR specific use case with their language
- Use their data, their scenario, their terminology wherever possible
- Skip features that aren't relevant to their situation
- Pause after each section: "Does this make sense for your workflow?"
Social Proof (2 min):
- One customer story similar to their situation (same industry, size, or pain point)
- Specific results: "Company X reduced [metric] by [amount] in [timeframe]"
- Keep it brief — one story, not a catalog
What ships with it
1 file 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.
- 10d ago First seen · 82 lines · 23 tokens per session scan A ab889bbcf527
demo-customizer is a skill published in the GitHub repository Autter-dev/agentic-sales-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 23 tokens to every session and 887 once invoked, about $0.0001 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 2026-08-31.
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