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 LensmorOfficial/trade-show-skills --skill post-show-followupgit clone --depth 1 https://github.com/LensmorOfficial/trade-show-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/lensmorofficial/trade-show-skills/post-show-followup)<a href="https://agentmods.dev/skills/lensmorofficial/trade-show-skills/post-show-followup"><img src="https://agentmods.dev/badge/skills/lensmorofficial/trade-show-skills/post-show-followup/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/lensmorofficial/trade-show-skills/post-show-followup"><img src="https://agentmods.dev/badge/skills/lensmorofficial/trade-show-skills/post-show-followup.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 | $0.00105 | $0.02116 |
| Opus 5 | $0.00053 | $0.01058 |
| Sonnet 5 | $0.00021 | $0.00423 |
| Haiku 4.5 | $0.00011 | $0.00212 |
Grade A, and why
post-show-followup 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 13d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Post-Show Follow-up
Generate tiered follow-up email sequences that convert trade show conversations into pipeline — sent within the critical 48-hour window when you're still fresh in their memory.
Why This Matters
Many trade show leads never receive timely, relevant follow-up. Of those that do, many get a generic "Great meeting you!" email that goes nowhere. This skill creates targeted sequences based on how warm the lead actually is.
When this skill triggers:
- Use it in the 24-48 hour window after the show, once leads are tiered or at least roughly segmented
- Use it after
badge-qualifierif you want tier logic grounded in actual booth notes - Do not use it to qualify raw leads from scratch; do that first in
badge-qualifier
Workflow
Step 1: Understand the Context
Extract from the user's request:
Required:
- Show name (just completed or about to end)
- What they were showcasing / selling
Helpful:
- Lead tiers — does the user already have a system? (e.g., hot/warm/cold, or A/B/C)
- Typical deal cycle — quick transactional vs. 6-month enterprise
- CRM they use (affects formatting and merge tags)
- Any specific conversations they want to reference
If the user just says "help me follow up after MEDICA", generate a complete 3-tier sequence with reasonable defaults.
Step 2: Define Lead Tiers
If the user doesn't have tiers, use this framework:
Tier 1 — Hot (had a real conversation, expressed clear interest)
- They asked about pricing, timeline, or next steps
- You have a specific action item from the conversation
- Follow-up within 24 hours
Tier 2 — Warm (good conversation, but exploratory)
- Showed interest but no concrete next step
- Scanned badge, exchanged cards, asked questions
- Follow-up within 48 hours
Tier 3 — Cold (brief contact, badge scan only)
- Quick booth visit, grabbed a brochure
- Badge scanned but no meaningful conversation
- Follow-up within 1 week
If the user qualified leads with badge-qualifier, its Hot / Warm / Cold output maps directly: Hot → Tier 1, Warm → Tier 2, Cold → Tier 3. The lead cards can be pasted in as input.
What ships with it
2 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.
- 13d ago First seen · 190 lines · 105 tokens per session scan A 833c1e6a6bdf
post-show-followup is a skill published in the GitHub repository LensmorOfficial/trade-show-skills (48 stars, last pushed 1mo ago), licensed MIT. It adds 105 tokens to every session and 2,116 once invoked, about $0.0005 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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