Extract Spark Meetings

Extract Spark Meetings

Spark Mail (the email client) records and summarizes meetings as +AI Meeting Notes and lets the owner share each note as a link. This skill converts those links into local markdown files with structured frontmatter, so meetings become greppable, taggable, and visible to future search.

Output is plain markdown + YAML — no Spark dependency once extracted.

Target link, if given: $ARGUMENTS. If that is blank or still shows the literal placeholder, run batch mode against links.md.

Reference files live in ${CLAUDE_SKILL_DIR}/references/.

Link shapes

Spark deep links look like https://sparkmailapp.com/dpl/bl?token=…; the same link can also arrive as readdle-spark://bl=… or readdlespark://bl=…. Treat any of these as a Spark meeting link. Spark may also hand out other share-link forms — if the user says it is a Spark meeting link, try it rather than rejecting it on shape.

When NOT to use

• The source isn't a Spark meeting link (e.g., Google Meet transcripts, Zoom cloud recordings, Otter.ai) — different link shapes and page structures; this skill's extractor will miss fields.
• You need a one-line summary, not a structured file — read the meeting directly and answer inline.
• Live-meeting capture (as it happens) — this skill reads already-saved meeting notes.

Expected layout

{current-directory}/
├── spark-meetings/          # Output directory (auto-created)
│   └── YYYY-MM-DD-*.md      # Extracted meeting files
└── links.md                 # Optional: links checklist for batch mode

Modes

Single link

Given one link, process it and write one file. Update links.md only if it exists and contains that link.

Batch (links.md)

Given no link, treat links.md as a checklist and process every unchecked entry:

- [ ] https://sparkmailapp.com/dpl/bl?token=AbC123...
- [x] https://sparkmailapp.com/dpl/bl?token=XyZ789... # already processed — skipped

Workflow

Process links sequentially, one at a time — do not parallelize. The CLI talks to a single Spark Desktop process over IPC, and web endpoints can throttle or return partial pages when hit concurrently; sequential runs also produce per-link errors you can act on rather than a jumbled burst of failures. Parallelism looks faster but costs you correctness and debuggability.

For each link:

1. Fetch the content

Try sources in this order and stop at the first that returns real meeting content. Each fallback exists because the one before it has a precondition that may not hold.

a. Official spark CLI — check with which spark. If present, run:

spark meeting --transcript --notes "https://sparkmailapp.com/dpl/bl?token=..."

The positional accepts a numeric meeting ID or a Spark deep link. Prefer this path because it reads the note straight from the user's Spark Desktop — no scraping, no rate limits, works offline, and it is the only route for readdle-spark:// links, which no browser can fetch. It requires Spark Desktop running on the same machine with CLI access enabled (Settings → AI Agents), and the note must belong to an account signed in there. If the command is missing, errors, or reports that the meeting isn't found, fall through.

b. Browser-automation MCP — Playwright MCP and Chrome DevTools MCP are the common ones. Don't hard-code a server name: check what's actually available, since tool names differ per server. Use this when the link opens a JS-rendered page; a browser waits for the DOM instead of returning an empty shell.

c. WebFetch — last resort, with the prompt: "Extract all meeting content including participants, discussion points, action items, decisions, and next steps." Fast and needs no browser, but a deep link may render as an app-launch landing page rather than the transcript. A near-empty body means the page is JS-rendered or gated: retry once with a browser MCP, not with WebFetch again.

If every route fails after a single retry, mark the link as failed (leave it unchecked in links.md) and move on.

2. Parse content

Extract in the original language of the meeting. Use English for section headings so filenames and frontmatter stay consistent across languages.

Fields:

• date — meeting date (YYYY-MM-DD)
• title — brief descriptive title
• participants — list of attendees
• duration — if mentioned
• summary — 2-3 sentence overview
• discussion_points — key topics
• action_items — tasks with owners and due dates
• decisions — decisions made
• next_steps — follow-ups

3. Write the file

Filename: spark-meetings/YYYY-MM-DD-{title-slug}.md. Collisions append -2, -3, etc. before the extension.

---
date: 2024-03-15
title: Quarterly Planning Meeting
participants:
  - Alice Johnson
  - Bob Smith
  - Carol Davis
duration: 60 min
tags:
  - planning
  - quarterly
  - strategy
spark_url: https://sparkmailapp.com/dpl/bl?token=AbC123...
extracted_date: 2024-03-15
---

# Quarterly Planning Meeting

## Summary

Brief 2-3 sentence summary of the meeting's purpose and outcomes.

## Discussion Points

- **Q1 Goals Review**: Discussed progress on Q1 objectives...
- **Q2 Planning**: Outlined key initiatives for next quarter...
- **Resource Allocation**: Reviewed team capacity and hiring needs...

## Action Items

- [ ] @alice Prepare Q2 budget proposal (Due: 2024-03-20)
- [ ] @bob Schedule follow-up with design team (Due: 2024-03-18)
- [ ] @carol Draft hiring plan for Q2 (Due: 2024-03-22)

## Decisions Made

1. Approved $50K budget for marketing initiative
2. Decided to postpone feature X to Q3
3. Agreed on weekly check-ins starting April

## Next Steps

- Schedule Q2 kickoff meeting
- Review and approve budget by March 20
- Begin hiring process for two engineering roles

4. Apply tags

Pick tags from references/tagging-guide.md: one primary meeting-type tag, 1-3 topic tags, optionally a cadence tag. The guide's tag set is deliberately generic — extend it in that file with your organization's own tags (product names, team names, initiatives) and keep the additions checked in so everyone's archive uses the same vocabulary.

5. Update links.md

Mark the link as [x] only after both content extraction and file write succeed. If either step failed, leave it unchecked and surface the failure in the output summary — this way a re-run will retry only the failed links.

• Single link mode: update links.md only if it already exists and contains the link; otherwise skip the update.
• Batch mode: walk unchecked (- [ ]) links in order, update the checkbox after each successful extraction, continue on failures.

Output summary

Report:

• Files created, with paths
• Links skipped or failed, each with a one-line reason (CLI error, fetch error, parse failure, etc.)

If batch mode ran zero links (all already checked), say so explicitly so the user knows nothing was missed.