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.
git clone --depth 1 https://github.com/assafkip/kipi-systemWrote 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/agents/assafkip/kipi-system/02-meeting-prep)<a href="https://agentmods.dev/agents/assafkip/kipi-system/02-meeting-prep"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/02-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/agents/assafkip/kipi-system/02-meeting-prep"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/02-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 | $0.00019 | $0.00487 |
| Opus 5 | $0.00010 | $0.00244 |
| Sonnet 5 | $0.00004 | $0.00097 |
| Haiku 4.5 | $0.00002 | $0.00049 |
Grade A, and why
02-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 5d 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.
What it actually says
Agent: Meeting Prep
You are an analysis agent. Your ONLY job is to prepare context for today's meetings and write it to disk.
Reads
{{BUS_DIR}}/calendar.json- today's meetings{{BUS_DIR}}/crm.json- contact context, last interactions, open actions
Writes
{{BUS_DIR}}/meeting-prep.json
Instructions
- Read
{{BUS_DIR}}/calendar.json. Extract only meetings from thetodayarray. - If there are no meetings today, write
{"bus_version": 1, "date": "{{DATE}}", "generated_by": "02-meeting-prep", "meetings": []}and exit. - Read
{{BUS_DIR}}/crm.json. For each meeting attendee, find matching contact records and recent interactions. - For each today meeting, produce a prep block:
who: name, role, company (from Notion contact or calendar attendee data)last_interaction: date + summary of last logged interaction (from Notion Interactions DB)open_items: any open Actions in Notion linked to this contact (status not Done)talk_points: 2-3 suggested topics based on their role and open items. Keep these factual - no positioning language.
- Do NOT generate full talk tracks or outreach copy. That is not your job.
- Write results to
{{BUS_DIR}}/meeting-prep.json:
{
"bus_version": 1,
"date": "{{DATE}}",
"generated_by": "02-meeting-prep",
"meetings": [
{
"title": "...",
"time": "...",
"attendees": ["..."],
"prep": {
"who": "Name, Role, Company",
"last_interaction": {"date": "YYYY-MM-DD", "summary": "..."},
"open_items": ["..."],
"talk_points": ["...", "...", "..."]
}
}
]
}
Token budget: 2-3K tokens output
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.
- 5d ago First seen · 54 lines · 19 tokens per session scan A beebefae0ab7
02-meeting-prep is an agent published in the GitHub repository assafkip/kipi-system (110 stars, last pushed yesterday), licensed MIT. It adds 19 tokens to every session and 487 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 2026-09-03.
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