Borrowing it
Nothing to install: this file belongs to pass-agent/loomkin. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/pass-agent/loomkin/main/.agents/skills/vault-meeting/SKILL.mdgit clone --depth 1 https://github.com/pass-agent/loomkinWrote 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/pass-agent/loomkin/vault-meeting)<a href="https://agentmods.dev/skills/pass-agent/loomkin/vault-meeting"><img src="https://agentmods.dev/badge/skills/pass-agent/loomkin/vault-meeting/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/pass-agent/loomkin/vault-meeting"><img src="https://agentmods.dev/badge/skills/pass-agent/loomkin/vault-meeting.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 | $0.00023 | $0.01431 |
| Opus 5 | $0.00012 | $0.00715 |
| Sonnet 5 | $0.00005 | $0.00286 |
| Haiku 4.5 | $0.00002 | $0.00143 |
Grade A, and why
vault-meeting 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Process a meeting transcript and extract structured information into the knowledge base.
Team Mode (Large Transcripts)
If the transcript is very long (60+ minutes of conversation, or the user requests team processing), spawn a team to parallelize the work:
team_spawn(
team_name: "meeting-processing",
purpose: "Process a long meeting transcript into structured vault entries",
roles: [
%{name: "meeting-lead", role: "lead"},
%{name: "vault-researcher", role: "researcher"},
%{name: "vault-writer", role: "coder"},
%{name: "vault-reviewer", role: "reviewer"}
]
)
Team roles:
- meeting-lead: Orchestrates extraction, manages redaction judgment, coordinates. Reads the transcript, identifies decisions/action items/topics, delegates creation to the writer.
- vault-researcher: Queries vault for related context — prior decisions on discussed topics, open tasks for mentioned projects, recent checkins from attendees. Provides context to the lead and writer.
- vault-writer: Creates the meeting note, decision records, atomic notes, and kanban items with proper formatting and linking. Works from the lead's extraction.
- vault-reviewer: Validates output quality — checks for temporal language in notes, verifies link targets exist, ensures frontmatter is complete. Runs
vault_auditon created entries.
The researcher and writer can work in parallel on different aspects. For shorter meetings (under 60 minutes), skip team mode and process single-agent.
Step 0: Get the Transcript
Determine where the transcript is:
- Pasted directly: Use the text from the user's message
- Google Drive link or file ID:
fetch_content(source: "google_drive", identifier: "{file_id}") - URL:
fetch_content(source: "url", identifier: "{url}") - Local file reference: Use
vault_readorfile_readas appropriate
If the user says something like "process the meeting from Drive" without a specific file, use ask_user to get the file ID or link.
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 · 151 lines · 23 tokens per session scan A 0199eb901c40
vault-meeting is a skill published in the GitHub repository pass-agent/loomkin (179 stars, last pushed 3mo ago), licensed MIT. It adds 23 tokens to every session and 1,431 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 2026-08-30.
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