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 techwolf-ai/ai-first-toolkit --skill meeting-prepgit clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkitWrote 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/techwolf-ai/ai-first-toolkit/meeting-prep)<a href="https://agentmods.dev/skills/techwolf-ai/ai-first-toolkit/meeting-prep"><img src="https://agentmods.dev/badge/skills/techwolf-ai/ai-first-toolkit/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/techwolf-ai/ai-first-toolkit/meeting-prep"><img src="https://agentmods.dev/badge/skills/techwolf-ai/ai-first-toolkit/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 | $0.00050 | $0.00925 |
| Opus 5.5 | $0.00020 | $0.00370 |
| Sonnet 5.5 | $0.00010 | $0.00185 |
| Haiku 4.5 | $0.00005 | $0.00093 |
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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Prep
Principle: "Narrow scope, high impact." One meeting, one thorough brief. No guessing, only sourced context.
Gathers context from all connected sources for a specific upcoming meeting and produces a structured briefing.
When to Use
- Before any meeting (1:1s have their own skill, use
/prep-one-on-oneinstead) - When the manager says "prep me for [meeting]", "what do I need to know for [meeting]"
- Can be invoked for the next upcoming meeting or a specific one by name/time
Instructions
If any MCP connector is unavailable, follow the connector unavailability protocol in references/operating-principles.md.
1. Identify the Meeting
If not specified, check Google Calendar for the next upcoming meeting.
If specified by name or time, search calendar for the matching event.
Extract from the calendar event:
- Title
- Time and duration
- Attendees (names and emails)
- Location/link
- Description/agenda (if present)
- Attached documents (if any)
If no matching meeting is found:
I couldn't find a meeting matching "[query]" on your calendar.
Could you clarify which meeting you mean? Your upcoming meetings are:
- [list next 5 meetings with times]
2. Load Manager Context
Read from manager-context/ (created by /setup):
manager-profile.mdfor team members and stakeholdersterminology.mdfor decoding any internal termssources.mdfor known data locations
If manager-context doesn't exist, note this:
⚠️ No manager context found. Run /setup first for richer meeting prep.
Proceeding with what I can find from sources directly.
3. Gather Attendee Context
For each attendee, search across sources:
Slack:
- Recent messages from/by this person (last 7 days)
- Threads they've been active in that relate to meeting topics
- Any messages that mention the meeting topic
Gmail:
- Recent email threads with this person (last 14 days)
- Especially any threads that include multiple meeting attendees
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 · 123 lines · 50 tokens per session scan A a5e6270ab2bb
meeting-prep is a skill published in the GitHub repository techwolf-ai/ai-first-toolkit (138 stars, last pushed 29d ago), licensed MIT. It adds 50 tokens to every session and 925 once invoked, about $0.0002 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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