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 mikonos/zettelkasten-agent-skills --skill meeting-notegit clone --depth 1 https://github.com/mikonos/zettelkasten-agent-skillsWrote 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/mikonos/zettelkasten-agent-skills/meeting-note)<a href="https://agentmods.dev/skills/mikonos/zettelkasten-agent-skills/meeting-note"><img src="https://agentmods.dev/badge/skills/mikonos/zettelkasten-agent-skills/meeting-note/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/mikonos/zettelkasten-agent-skills/meeting-note"><img src="https://agentmods.dev/badge/skills/mikonos/zettelkasten-agent-skills/meeting-note.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 | $0.00051 | $0.00874 |
| Opus 5.5 | $0.00020 | $0.00350 |
| Sonnet 5.5 | $0.00010 | $0.00175 |
| Haiku 4.5 | $0.00005 | $0.00087 |
Grade A, and why
meeting-note 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 2mo 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting Notes (high-output)
Core idea
The value is not “what was said”, but:
- why it was said
- what was not said (assumptions, power dynamics)
- what it means (risks, decisions, next actions) …and then linking it into your knowledge network.
Hard constraints
- Unknowns →
TBD(time, attendees, owners, deadlines, data sources, etc.) - Structure by topics and decision status (✅ / ⏳ / ❓)
- Must deliver:
- decisions / alignment / disagreements (with speakers + reasons)
- decision trail (proposal → debate → converge / postpone)
- assumptions (“elephants in the room”) with evidence
- risks & opportunities + mitigation/leverage
- action items (measurable + owner + deadline + success criteria)
- ≥2 Zettelkasten links (
[[Note]])
Workflow
Step 0: Plan first
Draft a short TODO list, then execute, then report completion + QA.
Step 1: Basics & importance
- Basics: time, place, topic, attendees (name + role)
- Meeting type: decision / discussion / report / brainstorm / alignment
- Importance:
- L3 strategic/high-risk → add “expert roundtable”
- L2 project/stage decision → emphasize decision trail + actions
- L1 daily sync → stay concise but keep actions
Step 2: Multi-pass processing
- Map topics (name each topic with one sentence)
- Speaker deep-dive (if there is a main presenter)
- Key decision-maker deep-dive (if applicable)
- Power dynamics & hidden layer (with evidence)
Step 3: Topic-by-topic structure
For each key topic include:
- conclusion (✅/⏳/❓) and what blocks it
- alignment points
- disagreement points (speaker + reason)
- decision trail
- hidden layer (assumptions; must include evidence)
- risks/opportunities
- open questions + needed inputs
Step 4: Atomize reusable units
Extract “atoms”:
- decision atoms
- insight atoms
- assumption/risk atoms
Step 5: Action items
Each action item must have:
- verb-first task
- measurable success criteria
- owner + deadline (TBD if unknown)
Output template
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.
- 2mo ago First seen · 120 lines · 51 tokens per session scan A 5012625074e5
meeting-note is a skill published in the GitHub repository mikonos/zettelkasten-agent-skills (3 stars, last pushed 9mo ago), licensed MIT. It adds 51 tokens to every session and 874 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 2026-08-31.
meeting-note compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| meeting-notemikonos/zettelkasten-agent-skills | Skill | 3 | 9mo ago | MIT | A | 51 | Claude Code, Codex |
| knowledge-ingestopenclaw/openclaw | Skill | 394k | today | MIT | A | 80 | Claude Code, Codex |
| mem0-oss-to-platformmem0ai/mem0 | Skill | 69k | yesterday | Apache-2.0 | A | 217 | Claude Code, Codex |
| forgetasgeirtj/system_prompts_leaks | Skill | 71k | yesterday | CC0-1.0 | A | 0 | Claude Code, Codex |
| Cortexdanielmiessler/LifeOS | Skill | 20k | 2d ago | MIT | A | 184 | Claude Code |
| memoryopensquilla/opensquilla | Skill | 7.1k | yesterday | Apache-2.0 | A | 44 | Claude Code, Codex |
| ha-data-storesshiwenwen/hope-agent | Skill | 1.9k | yesterday | MIT | A | 115 | Claude Code, Codex |