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npx skills add https://github.com/deusXmachina-dev/memorylane --skill last-30-minutesThe command stays on one line. Scroll horizontally to inspect it before copying.
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(new) Find a person's repeated tasks from their screen activity, and what each one is worth automating, with the time and money saved. Outputs the numbers and data a report is built from, not the visual. Use to analyze processes, mine workflows, or see what is automatable and what it saves. Every figure is labelled and grounded, never made up.
(new) Turn a process analysis into a polished, client-ready report, first an HTML deck you review, then a matching PDF. Use to package an analysis into an exec report or PDF. Shows the deck for approval before making the PDF, and never makes up numbers.
Deploy the MemoryLane Claude Code plugin by verifying only plugin/marketplace files changed, bumping the plugin version, then committing and pushing.
Based on SOC occupation classification
| name | last-30-minutes |
| allowed-tools | mcp__memorylane__browse_timeline, mcp__memorylane__search_context, mcp__memorylane__get_activity_details |
| description | Summarize what you've been doing in the last 30 minutes. |
Summarize the user's recent screen activity.
Call browse_timeline(startTime="30 minutes ago", endTime="now", limit=50, sampling="recent_first").
browse_timeline(startTime="2 hours ago", endTime="now", limit=50, sampling="recent_first").From the returned entries:
Only call get_activity_details(ids) when a summary is ambiguous and the exact on-screen text would genuinely help clarify what the user was doing. Do not fetch OCR speculatively.
Format as a brief narrative followed by bullet points:
**Last 30 minutes** (N activities recorded)
You were primarily working on [main task].
- **[App Name]** (~X min) — [what you were doing]
- **[App Name]** (~X min) — [what you were doing]
If the results came from the wider 2-hour window, adjust the heading accordingly.
get_activity_details for ambiguous cases.search_context(query) if the user asks follow-up questions like "what was I doing in Chrome?" or "find that thing I was reading about X".recent_first sampling is used instead of uniform because the user cares most about what just happened, and the window is short enough that uniform sampling would not add value.