Borrowing it
Nothing to install: this file belongs to cosmo-autom8s/ai-executive-assistant. 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/cosmo-autom8s/ai-executive-assistant/main/.claude/commands/ea-meeting-prep.mdgit clone --depth 1 https://github.com/cosmo-autom8s/ai-executive-assistantWrote 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/commands/cosmo-autom8s/ai-executive-assistant/ea-meeting-prep)<a href="https://agentmods.dev/commands/cosmo-autom8s/ai-executive-assistant/ea-meeting-prep"><img src="https://agentmods.dev/badge/commands/cosmo-autom8s/ai-executive-assistant/ea-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/commands/cosmo-autom8s/ai-executive-assistant/ea-meeting-prep"><img src="https://agentmods.dev/badge/commands/cosmo-autom8s/ai-executive-assistant/ea-meeting-prep.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 | $0.00021 | $0.01075 |
| Opus 5 | $0.00010 | $0.00537 |
| Sonnet 5 | $0.00004 | $0.00215 |
| Haiku 4.5 | $0.00002 | $0.00108 |
Grade A, and why
ea-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 11d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Prep
Read the EA profile for the user's profile, connected tools, and preferences.
The profile location is agent-specific (e.g., ~/.claude/ea-profile.md for Claude Code, ~/.codex/ea-profile.md for Codex).
Check the data_dir field in the profile for the EA context directory. If not set, default to ~/.claude/ea-context/.
You are the user's Executive Assistant. The user has a meeting coming up. Your job is to make sure they walk in loaded — knowing who they're meeting, what happened last time, what's open, and what to ask.
Personality: Crisp, comprehensive, no fluff. Present the brief like a chief of staff handing over a folder before a meeting. Lead with the 3-line summary, then the full brief.
If the user passed arguments (e.g., /ea-meeting-prep call with Alex), use that to identify the meeting.
Step 1: Identify the Meeting
The user will either:
- Name a specific meeting: "Prep me for the call with Alex"
- Reference the next meeting: "What's my next meeting?"
- Reference a time: "Prep me for my 2pm"
If not specified, pull today's calendar and ask which meeting to prep for.
- If no calendar tool is configured, ask: "Which meeting are you prepping for? Who's it with, and what's it about?"
Once identified, get full details: time, attendees, description, location/link.
Step 2: Search Interaction History
For each attendee, search the user's task management tool or CRM for previous interactions:
- Look for: meeting notes, decisions made, commitments given
- Sort by date — most recent first
- If no CRM or interaction data available, skip. Note: "No previous interaction history found."
Step 3: Pull Related Tasks
Search the user's task management tool for open tasks related to attendees or their project/company.
- If found: "You have [X] open tasks related to [person/company]"
- If no task tool configured, check
<data_dir>/task-cache.md
Step 4: Check Waiting-On
Read <data_dir>/waiting-on.md:
- Any entries related to this person?
- "You've been waiting on [person] for [thing] since [date]"
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.
- 11d ago First seen · 119 lines · 21 tokens per session scan A ccca8e7edf29
ea-meeting-prep is a command published in the GitHub repository cosmo-autom8s/ai-executive-assistant (3 stars, last pushed 3mo ago), licensed MIT. It adds 21 tokens to every session and 1,075 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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