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 note1-ai/note1-mcp --skill note1-meetingsgit clone --depth 1 https://github.com/note1-ai/note1-mcpWrote 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/note1-ai/note1-mcp/note1-meetings)<a href="https://agentmods.dev/skills/note1-ai/note1-mcp/note1-meetings"><img src="https://agentmods.dev/badge/skills/note1-ai/note1-mcp/note1-meetings/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/note1-ai/note1-mcp/note1-meetings"><img src="https://agentmods.dev/badge/skills/note1-ai/note1-mcp/note1-meetings.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 | $0.00087 | $0.01046 |
| Opus 5.5 | $0.00035 | $0.00418 |
| Sonnet 5.5 | $0.00017 | $0.00209 |
| Haiku 4.5 | $0.00009 | $0.00105 |
Grade A, and why
note1-meetings 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 10d 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 — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
note1 meetings
note1.ai records meetings, transcribes them and writes summaries and action items. You reach a user's meetings through the note1 MCP tools. Every tool acts with the signed-in user's own permissions.
Pick the right tool
- A question about content ("what did we decide about pricing?"):
note1_search_meetingswithmode: "analysis". It returns ananswerplus thematchesit is based on. - Finding where something was said:
note1_search_meetingswith the defaultmode: "search". It returns ranked snippets. Narrow withkind(title,summary,transcript,action_item,topic,question) when the user names one. - Browsing ("meetings last week", "failed recordings"):
note1_list_meetingswithcallAtAfter,callAtBefore(ISO dates, the latter exclusive) andstatus(comma list such asscheduled,ready,failed). Usemine: truefor meetings the user took part in andsameSeriesAswith a meeting id for other occurrences of a recurring meeting. Results are paged: pass the returnednextPageaspageto continue, and keep going until the user has what they asked for. - One meeting:
note1_get_meetingreturns the summary, sections, participants, status, the recurring series (previous and next occurrence) and the link. Prefer it for "summarize the meeting". - Full content or a document to save:
note1_export_meetingwithcontent(summary,transcriptorboth) andformat(markdownorjson). Use it for verbatim quotes or paste-ready text. Do not export a transcript to answer a question search can answer. - Who spoke, what was asked, topics, tracker hits, highlights:
note1_get_meeting_insightswithkind(speakers,questions,topics,trackers,highlights,all). Never read the transcript for "who spoke the most" or "which questions went unanswered".
Always cite sources
Search matches carry meetingId, title, date, timestamp and a snippet. When you state a fact from a meeting, name the meeting title, its date and the timestamp, and link it: https://note1.ai/dashboard/meeting/<meetingId> (note1_get_meeting also returns the exact url). Quote the snippet, do not paraphrase it into something stronger. If the matches do not support an answer, say so instead of guessing, and offer to search with other words or another kind.
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.
- 10d ago First seen · 42 lines · 87 tokens per session scan A 7880590872f4
note1-meetings is a skill published in the GitHub repository note1-ai/note1-mcp (1 stars, last pushed 2d ago), licensed MIT. It adds 87 tokens to every session and 1,046 once invoked, about $0.0003 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 2026-11-05.
note1-meetings compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| note1-meetingsnote1-ai/note1-mcp | Skill | 1 | 2d ago | MIT | A | 87 | Claude Code |
| opik-diagnosecomet-ml/opik-mcp | Skill | 226 | today | Apache-2.0 | A | 187 | Claude Code |
| cortex-explore-memorycdeust/Cortex | Skill | 77 | today | MIT | A | 91 | Claude Code |
| qmclaw-workbenchxi-zhao/OpenQuantum | Skill | 72 | 4d ago | MIT | A | 124 | Codex |
| quantum-groverxi-zhao/OpenQuantum | Skill | 72 | 4d ago | MIT | A | 62 | Claude Code, Codex |
| guppy-programsxi-zhao/OpenQuantum | Skill | 72 | 4d ago | MIT | A | 48 | Claude Code, Codex |
| quantum-algorithmsxi-zhao/OpenQuantum | Skill | 72 | 4d ago | MIT | A | 34 | Claude Code, Codex |