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 markmhendrickson/neotoma --skill remember-meetingsgit clone --depth 1 https://github.com/markmhendrickson/neotomaWrote 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/markmhendrickson/neotoma/remember-meetings)<a href="https://agentmods.dev/skills/markmhendrickson/neotoma/remember-meetings"><img src="https://agentmods.dev/badge/skills/markmhendrickson/neotoma/remember-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/markmhendrickson/neotoma/remember-meetings"><img src="https://agentmods.dev/badge/skills/markmhendrickson/neotoma/remember-meetings.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 | $0.00023 | $0.00688 |
| Opus 5 | $0.00012 | $0.00344 |
| Sonnet 5 | $0.00005 | $0.00138 |
| Haiku 4.5 | $0.00002 | $0.00069 |
Grade A, and why
remember-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 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.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Remember Meetings
Ingest meeting transcripts and extract structured entities — decisions, action items, attendees, and commitments — into Neotoma memory with full provenance.
When to use
When the user has meeting transcripts (from Zoom, Otter, Google Meet, or manual notes) and wants to capture the decisions, action items, and participants in durable memory.
Prerequisites
Run the ensure-neotoma skill first if Neotoma is not yet installed or configured in your current harness.
Supported formats
| Format | Extension | Source |
|---|---|---|
| WebVTT | .vtt |
Zoom, Google Meet |
| SubRip | .srt |
Zoom, various |
| Plain text | .txt |
Otter, manual |
| Markdown | .md |
Manual, meeting notes apps |
| JSON | .json |
Structured exports |
Workflow
Phase 0: Verify Neotoma
Confirm Neotoma MCP is connected (call get_session_identity).
Phase 1: Identify transcripts
- Ask the user for the transcript file(s) or directory.
- Detect the format from the file extension.
- If a calendar MCP is available, optionally cross-reference with calendar events to enrich metadata (meeting title, attendees, time).
Phase 2: Parse and preview
- Read each transcript file.
- Parse speaker turns, timestamps, and content.
- Present a preview: meeting date, duration, participants detected, key topics.
- Ask the user to confirm before processing.
Phase 3: Extract entities
For each meeting:
- Event: create a meeting event entity with title, date, duration, attendees.
- Contacts: extract attendees as contacts (name, role if mentioned).
- Decisions: identify conclusions, agreements, choices made during the meeting.
- Tasks: extract action items with assignee, description, and deadline if stated.
- Notes: capture key discussion points that don't fit other entity types.
Set source_file to the transcript filename. Include source_quote on each extracted entity with the verbatim transcript snippet that supports it.
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 · 87 lines · 23 tokens per session scan A 6d5b0bf7276d
remember-meetings is a skill published in the GitHub repository markmhendrickson/neotoma (32 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 688 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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