Borrowing it
Nothing to install: this file belongs to Othmane-Khadri/gtm-engineer-playbook. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Othmane-Khadri/gtm-engineer-playbook/main/.claude/skills/gtm-playbook/meeting-prep-brief/SKILL.mdgit clone --depth 1 https://github.com/Othmane-Khadri/gtm-engineer-playbookWrote 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/othmane-khadri/gtm-engineer-playbook/meeting-prep-brief)<a href="https://agentmods.dev/skills/othmane-khadri/gtm-engineer-playbook/meeting-prep-brief"><img src="https://agentmods.dev/badge/skills/othmane-khadri/gtm-engineer-playbook/meeting-prep-brief/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/othmane-khadri/gtm-engineer-playbook/meeting-prep-brief"><img src="https://agentmods.dev/badge/skills/othmane-khadri/gtm-engineer-playbook/meeting-prep-brief.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 | $0.00070 | $0.03197 |
| Opus 5 | $0.00035 | $0.01598 |
| Sonnet 5 | $0.00014 | $0.00639 |
| Haiku 4.5 | $0.00007 | $0.00320 |
Grade A, and why
meeting-prep-brief 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 — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Prep Brief
Generate a concise pre-call intelligence brief in 2-3 minutes. Everything you need before walking into a meeting: company context, stakeholder profile, competitive landmines, talking points, and a proposed agenda. Uses WebSearch for real-time intelligence and builds on existing account research when available.
Steps
1. Collect Input
Ask the user for the following:
- Company name (required)
- Contact name and title (required) — who you are meeting with
- Meeting type (required) — one of: discovery call, demo, follow-up, QBR, negotiation
- Your product/service (optional) — if provided, talking points and agenda will be tailored to the user's offering
- Deal context (optional) — past conversations, where they are in the funnel, previous meetings, known objections
- Specific questions (optional) — anything the user wants answered or addressed during the meeting
Do NOT proceed until you have the company name, contact name/title, and meeting type.
2. Check Existing Intelligence
Use Glob to check for existing files that can accelerate the brief:
docs/accounts/{company}.md— account research brief (from the Account Research Brief skill)docs/signals/{company}.md— signal data (from the Signal Scanner skill)docs/pipeline/scored-leads.md— qualification scoredocs/icp.md— ICP match assessment
If any of these exist: Read them. Summarize what you loaded. Skip redundant research in subsequent steps and build on the existing intelligence instead.
If none exist: Proceed with full research from Step 3 onward.
3. Company Context
Skip this step if a recent account brief already exists at docs/accounts/{company}.md.
Run 2-3 WebSearch queries (e.g., "{company} what does it do", "{company} news 2026", "{company} funding" ).
Gather:
- What they do (one paragraph, plain language)
- Recent news from the last 30 days (1-3 headlines with source URLs)
- Key metrics: funding stage, total raised, headcount, revenue range (if public)
- Current challenges or priorities — inferred from press releases, job postings, executive interviews, or earnings calls
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 · 289 lines · 70 tokens per session scan A 17bc433f5449
meeting-prep-brief is a skill published in the GitHub repository Othmane-Khadri/gtm-engineer-playbook (56 stars, last pushed 5mo ago), licensed MIT. It adds 70 tokens to every session and 3,197 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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