Agent skill

Vault Meeting

by pass-agent in pass-agent/loomkin

Process a meeting transcript — extract decisions, action items, and key discussion points into structured vault entries

MITAuto-check passedProductivity & Automation

Install Vault Meeting

skills CLI
$ npx skills add pass-agent/loomkin --skill vault-meeting -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install pass-agent/loomkin vault-meeting --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/pass-agent/loomkin.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/vault-meeting .claude/skills/vault-meeting && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
vault-meeting
GitHub stars
181
Token cost
~1.5k tokens
SKILL.md length
703 words
Files
1
Skills in repo
14
Repo updated
First seen
Licence
MIT

At a glance

Process a meeting transcript — extract decisions, action items, and key discussion points into structured vault entries

  • Works in 9 steps: Get the Transcript → Check for Prep → Handle Long Transcripts → …
  • Productivity & Automation work in your project
  • SKILL.md covers Team Mode (Large Transcripts), Step 0: Get the Transcript, Step 1: Check for Prep and Step 2: Handle Long Transcripts, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Vault Meeting is an agent skill from pass-agent/loomkin. Process a meeting transcript — extract decisions, action items, and key discussion points into structured vault entries

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Productivity & Automation. The repository describes itself as: What if AI agents could form teams as fluidly as humans? Spawn specialists in milliseconds, share discoveries in real-time, review each other's work, and remember everything… The licence is MIT.

When your agent uses it

  • Productivity & Automation work in your project

Example prompts

  • “/vault-meeting”

Requirements

  • Pre-approved tools (allowed-tools): vault_create_entry, vault_update_entry, vault_search, vault_link, vault_kanban, vault_dashboard, vault_audit, decision_log, fetch_content, context_offload, ask_user, team_spawn

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Get the Transcript
  2. Check for Prep
  3. Handle Long Transcripts
  4. Analyze the Transcript
  5. Redaction Judgment
  6. Create Entries
  7. Update Prep (if exists)
  8. Refresh Dashboard
  9. Report

What it can do on your machine

Read from SKILL.md and the folder at commit f769ae7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • vault_create_entry
    • vault_update_entry
    • vault_search
    • vault_link
    • vault_kanban
    • vault_dashboard
    • vault_audit
    • decision_log
    • fetch_content
    • context_offload

    …and 2 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Vault Meeting loads about 1.5k tokens when it runs. Until then it costs about 33 tokens; SKILL.md has 703 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~33
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from pass-agent/loomkin at commit f769ae7, republished under its MIT licence (© pass-agent). 703 words, ~1,517 tokens.

Download SKILL.mdSave it as .claude/skills/vault-meeting/SKILL.md (or your agent's skills folder).
name
vault-meeting
description
Process a meeting transcript — extract decisions, action items, and key discussion points into structured vault entries
allowed-tools
vault_create_entry, vault_update_entry, vault_search, vault_link, vault_kanban, vault_dashboard, vault_audit, decision_log, fetch_content, context_offload, ask_user, team_spawn

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_audit on 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_read or file_read as 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.

Step 1: Check for Prep

Search for a prep file matching the meeting date: vault_search(query: "prep", entry_type: "meeting", tags: ["prep"])

If prep exists:

  • Read it to understand the planned agenda
  • Track which topics get covered during processing
  • You will mark covered topics and report coverage at the end

Step 2: Handle Long Transcripts

If the transcript is very long (appears to be 20+ minutes of conversation), offload it to a context keeper: context_offload(topic: "meeting-transcript-{date}", content: ...)

This preserves the full transcript at high fidelity without consuming your context window.

Step 3: Analyze the Transcript

Read through and identify:

Attendees — who spoke in the meeting

Decisions — commitments to a course of action. Look for:

  • "Let's go with...", "We'll do...", "We decided..."
  • Choosing between alternatives
  • Agreeing on a direction

For each decision, assess:

  • Who proposed it (who said "I think we should..." or "What if we...")
  • Who decided (who gave final approval — "Sounds good", "Let's do it")
  • Scope: company | product | project
  • Reversibility: one-way (hard to undo — hiring, equity, pivots) | two-way (easy to change — features, tools)

Action items — be thorough. Look for ALL of these patterns:

  • Explicit: "[Person] will...", "Can you...", "Take care of..."
  • Volunteering: "I'll handle that", "Let me do...", "I can take..."
  • Implied: If someone says they'll improve/fix/create something, that is a task
  • Follow-ups: Items needing attention even without explicit assignment

Key discussion points — topics that got meaningful airtime

Summary — 2-3 sentence overview

Show full SKILL.md (251 more words)Show less

Step 4: Redaction Judgment

This is a shared company vault. Apply judgment about what belongs in shared records.

Auto-redact (do it, no confirmation needed):

  • Phone numbers, addresses, SSNs
  • Financial figures (salaries, investment amounts)
  • Passwords, API keys

Flag for user confirmation (use ask_user):

  • Explicit removal requests ("off the record", "don't add that")
  • Personal asides clearly unrelated to work

Omit entirely (don't even flag):

  • HR/personnel matters — note "Personnel discussion - details in private records"
  • Individual criticism of team members

When redacting, think holistically about context. A single-line gap surrounded by reactions is worse than no redaction — remove the full exchange.

Step 5: Create Entries

  1. Meeting note: vault_create_entry(entry_type: "meeting", ...) with full extracted content
  2. Decision records: For each decision:
    • vault_create_entry(entry_type: "decision", ...) — creates DR-YYYY-NNN automatically
    • decision_log(node_type: "decision", ...) — adds to the live decision graph with confidence score
    • vault_link(source_path: meeting, target_path: decision, link_type: "decides")
  3. Action items: vault_kanban(action: "add", ...) for each task, linked to the meeting
  4. Atomic notes: If discussion surfaced a reusable concept or strategy, create it as a note and link to the parent topic

Step 6: Update Prep (if exists)

If a prep file existed:

  • vault_update_entry to check off covered topics (- [ ] to - [x])
  • Count coverage: "Discussed X/Y agenda topics"
  • Add processed: true to frontmatter

Step 7: Refresh Dashboard

vault_dashboard(dashboard_type: "activity") then use the result to update the index entry.

Step 8: Report

Summarize what was created:

  • Meeting note path
  • Decision records created (list with DR numbers)
  • Action items added (count, grouped by assignee)
  • Prep coverage (if applicable)
  • Any flagged redactions that need review

© pass-agent, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/vault-meeting of pass-agent/loomkin.

Open the folder on GitHubat commit f769ae7

Compare with similar skills

Vault Meeting next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Vault Meeting compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Vault Meeting this skillpass-agent/loomkin181—~1.5kAutomated safety check: PassMIT
Agent Browserquran/quran.com-frontend-next1.9k40 repos~3.3kAutomated safety check: PassNone
Dependency Watchtelegramdesktop/tdesktop33k1 repos~2.2kAutomated safety check: PassGPL-3.0
Perform Tasktelegramdesktop/tdesktop33k2 repos~3kAutomated safety check: PassGPL-3.0
Brave Searchbadlogic/pi-skills2.6k5 repos~592Automated safety check: PassMIT
Garden Inboxpaperclipai/paperclip99k—~1.1kAutomated safety check: PassMIT

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Questions about Vault Meeting

What does Vault Meeting do?

Process a meeting transcript — extract decisions, action items, and key discussion points into structured vault entries. Vault Meeting is an agent skill from pass-agent/loomkin.

When should I use Vault Meeting?

Vault Meeting fits situations like: productivity & Automation work in your project.

How do I install Vault Meeting in Claude Code?

Run `npx skills add pass-agent/loomkin --skill vault-meeting -a claude-code`. Or copy the skill folder (.agents/skills/vault-meeting in pass-agent/loomkin) into .claude/skills/vault-meeting in your project. Claude Code loads it when a task matches its description.

How do I install Vault Meeting in Codex?

Run `npx skills add pass-agent/loomkin --skill vault-meeting -a codex`. Or copy the skill folder (.agents/skills/vault-meeting in pass-agent/loomkin) into .agents/skills/vault-meeting in your project. Codex loads it when a task matches its description.

Can I use Vault Meeting in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pass-agent/loomkin --skill vault-meeting -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vault-meeting, .gemini/skills/vault-meeting, .github/skills/vault-meeting and .opencode/skills/vault-meeting in your project.

What does Vault Meeting need to run?

SKILL.md names no scripts, command-line tools or credentials: Vault Meeting is instructions for the agent only. Its frontmatter pre-approves these tools: vault_create_entry, vault_update_entry, vault_search, vault_link, vault_kanban, vault_dashboard, vault_audit, decision_log, fetch_content, context_offload, ask_user, team_spawn.

Does Vault Meeting access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Vault Meeting safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Vault Meeting use?

Vault Meeting is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Vault Meeting use?

About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Vault Meeting?

Skills that share tags, products or a category with Vault Meeting: Agent Browser (quran/quran.com-frontend-next, 1.9k stars), Dependency Watch (telegramdesktop/tdesktop, 33k stars), Perform Task (telegramdesktop/tdesktop, 33k stars) and Brave Search (badlogic/pi-skills, 2.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Vault Meeting?

pass-agent (a GitHub organization) maintains it in pass-agent/loomkin, which has 181 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on May 17, 2026.

Source: pass-agent/loomkin on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.