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 tough-tongue/demo-prep-skills --skill post-demogit clone --depth 1 https://github.com/tough-tongue/demo-prep-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/tough-tongue/demo-prep-skills/post-demo)<a href="https://agentmods.dev/skills/tough-tongue/demo-prep-skills/post-demo"><img src="https://agentmods.dev/badge/skills/tough-tongue/demo-prep-skills/post-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/tough-tongue/demo-prep-skills/post-demo"><img src="https://agentmods.dev/badge/skills/tough-tongue/demo-prep-skills/post-demo.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 | $0.00045 | $0.01757 |
| Opus 5 | $0.00023 | $0.00879 |
| Sonnet 5 | $0.00009 | $0.00351 |
| Haiku 4.5 | $0.00005 | $0.00176 |
Grade A, and why
post-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 — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Post-Demo Follow-Up
Generate structured follow-up materials after a sales call or demo. Produces a follow-up email, internal debrief, and follow-up sequence plan — all based on what actually happened in the conversation.
When to Use
- User says "write a follow-up for my call with [name]"
- User just finished a demo and needs to send a recap
- User wants to create an internal debrief for their team
- User needs to plan the follow-up sequence (nudge, re-engagement)
Required Inputs
Ask the user for:
Who: [Contact name, title, company]
What happened: [Paste meeting notes, transcript, or describe what was discussed]
Outcome: [Positive / Neutral / Negative — what's the next step?]
The more detail they provide, the better the output. A transcript is ideal. Bullet points work. Even "it went well, they want a pilot" is enough to generate useful follow-up.
Process
1. Load Context
Read company-profile.md for the user's product and positioning.
If a prep file exists for this prospect (e.g., prep/acme-sarah-chen-2026-03-06.md), read it for pre-meeting context.
2. Extract Key Information
From the meeting notes or transcript, identify:
| What to Extract | Why It Matters |
|---|---|
| Topics discussed | Structure the follow-up email |
| Pain points mentioned | Reinforce in follow-up |
| Objections raised | Address proactively in email |
| Questions they asked | Answer any that were deferred |
| Buying signals | Note for internal debrief |
| Red flags | Note for internal debrief |
| Agreed next steps | Confirm in email |
| Other stakeholders mentioned | Multi-thread opportunity |
| Timeline | Urgency indicator |
| Budget discussion | Qualification data |
3. Generate Outputs
Produce all three outputs below.
Output Structure
OUTPUT 1: Follow-Up Email
Send within 2-4 hours of the call. Reference specific things discussed — never send a generic follow-up.
Subject: Great chatting, [Name] — here's everything we discussed
Hi [Name],
Thanks for your time today. I really enjoyed learning about [SPECIFIC thing from the conversation — not generic].
Here's a quick recap:
**What we discussed:**
1. [Specific topic 1 — use their words where possible]
2. [Specific topic 2]
3. [Specific topic 3]
**Resources:**
- [Link to the product/demo/resource they asked about]
- [Link to anything you promised to send]
**Next steps:**
- [ ] [Their action item — specific and timeboxed]
- [ ] [Your action item — specific and timeboxed]
- [ ] [Follow-up date]
Let me know if I missed anything or if you'd like to loop in anyone else.
Best,
[User Name]
[Title, Company]
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.
- 12d ago First seen · 216 lines · 45 tokens per session scan A 6385dbecc18b
post-demo is a skill published in the GitHub repository tough-tongue/demo-prep-skills (5 stars, last pushed 6mo ago), licensed MIT. It adds 45 tokens to every session and 1,757 once invoked, about $0.0002 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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