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spark-recipe-topic-timeline

spark-recipe-topic-timeline

github.com/readdleProductivity154345 installsUpdated 6d ago
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About spark-recipe-topic-timeline

A read-only Spark recipe that combines meeting discussions and email threads into a chronological narrative about a project or topic. It is intended for catching up, onboarding others, and preparing status updates, while highlighting turning points and unresolved threads.

Key features

  1. 01Gather relevant meeting details
  2. 02Search and review email threads
  3. 03Merge entries by date
  4. 04Highlight turning points and open threads
  5. 05Summarize current status

Use cases

  1. 01Catch up on a project
  2. 02Brief a newly joined teammate
  3. 03Prepare a status update
  4. 04Spot gaps or unresolved issues

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/readdle/spark-cli-skills --skill spark-recipe-topic-timeline

After installing, type/spark-recipe-topic-timelinein Claude Code to confirm it loaded.

Details

From the project README

Recipe: Topic Timeline

For a given project or topic, build a unified chronological narrative by interleaving meeting discussions and email threads. Useful for catching up, briefing someone new, or preparing a status update.

Prerequisite: Read the use-spark base skill for command reference and filter syntax.

Access level required: read-only.

Steps

Step 1: Define the scope

Ask the user for:

  • The topic or project name (keywords to search on)
  • The time range (default to 30 days if unspecified)
Step 2: Gather meeting data
spark meetings --filter "subject:topic-keyword newer_than:30d"

If the subject filter misses relevant meetings, broaden:

spark meetings --filter "newer_than:30d"

For each relevant meeting, read the summary:

spark meeting <id>

Pull full detail only for meetings where the topic was a major agenda item:

spark meeting <id> --transcript --notes

Record: date, participants, and the key points related to the topic.

Step 3: Gather email data
spark search "topic keyword"

For threads that are clearly relevant, read the full conversation:

spark thread <id>

If there are specific people associated with the topic, also pull their threads:

spark emails --filter "from:[email protected] subject:keyword newer_than:30d"

Record: date of each message, participants, and the substance.

Step 4: Merge into a timeline

Combine all entries (meetings and emails) and sort by date. For each entry:

  • Date
  • Channel: Meeting / Email
  • Participants
  • What happened: one or two sentences summarizing the key substance
Step 5: Annotate the timeline

Layer on editorial notes:

  • Mark turning points where direction changed
  • Flag open threads that don't have a resolution
  • Note gaps — periods with no activity that might indicate stalled progress
Step 6: Present the timeline

Start with a one-paragraph executive summary of where the topic stands now, then present the full timeline oldest-to-newest. End with:

  • Current status: the latest known state
  • Open items: anything still unresolved
  • Next touchpoint: upcoming meeting or pending email that will advance the topic

Tips

  • spark search is relevance-ranked and returns full bodies — it's the best starting point for email discovery.
  • Meeting summaries usually capture the topic well enough. Reserve --transcript for meetings where you need exact quotes or attribution.
  • For topics that span many months, work in chunks (e.g., month by month) to avoid overwhelming the output.
  • This pairs well with recipe-decision-tracker — use that recipe when you only need the decision points, and this one when you need the full narrative.
  • If building this for someone else (e.g., onboarding a new team member), call out any assumed context that an outsider wouldn't have.

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