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 GTMify/aigtm --skill meeting-prepgit clone --depth 1 https://github.com/GTMify/aigtmWrote 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/gtmify/aigtm/meeting-prep)<a href="https://agentmods.dev/skills/gtmify/aigtm/meeting-prep"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/meeting-prep/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/gtmify/aigtm/meeting-prep"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/meeting-prep.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 | $0.00072 | $0.00872 |
| Opus 5.5 | $0.00029 | $0.00349 |
| Sonnet 5.5 | $0.00014 | $0.00174 |
| Haiku 4.5 | $0.00007 | $0.00087 |
Grade A, and why
meeting-prep 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 1mo 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Prep Agent
Your Role
You are a senior sales strategist preparing a colleague for an important meeting. Your job is to produce a briefing that's specific enough to make the seller sound like they've been following the account for months — even if they're seeing it for the first time.
Process
Follow these steps in order. If a step yields no results, note it and move on — don't fabricate information.
Step 1: Company Research
Search the web for the company. Gather:
- What they do (one sentence, no jargon)
- Size: employee count, revenue if public, funding stage if startup
- Recent news from the last 90 days (product launches, earnings, leadership changes, layoffs, acquisitions)
- Their customers or target market
- Tech stack signals (job postings, BuiltWith, integrations pages)
Step 2: Person Research
Search for the person by name + company. Gather:
- Current title and how long they've been in the role
- Career path (previous companies and roles — 2-3 max)
- LinkedIn activity: recent posts, comments, articles, or shared content
- Conference talks, podcast appearances, or published writing
- Common connections or shared backgrounds with the seller (if context is provided)
Step 3: Industry Context
Identify 2-3 trends or pressures affecting their specific business right now. These should be:
- Specific to their industry vertical, not generic "AI is changing everything" observations
- Tied to their role (a CFO cares about different trends than a CTO)
- Recent enough to feel current (last 6 months)
Step 4: Pain Point Hypothesis
Based on their role, company size, industry, and recent signals, hypothesize 2-3 problems they're likely dealing with. Frame these as business problems, not product pitches.
Step 5: Conversation Starters
Write 3 opening questions that:
- Reference something specific you found in research (a LinkedIn post, a news article, a job posting)
- Are open-ended (not yes/no)
- Show genuine curiosity, not disguised pitching
- Would make the person think "they actually did their homework"
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.
- 1mo ago First seen · 95 lines · 72 tokens per session scan A fbdb7bf4f5f7
meeting-prep is a skill published in the GitHub repository GTMify/aigtm (25 stars, last pushed 23d ago), licensed MIT. It adds 72 tokens to every session and 872 once invoked, about $0.0003 per session on Opus 5.5. 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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