Aggregate AI tool sessions and correlate them with GitHub activity and backup diffs.
npx skills add https://github.com/b08x/syncopated-context --skill recall-b08x
Please help me install this Agent Skill. Skill: recall Source: https://github.com/b08x/syncopated-context/tree/main/plugins/notebook/skills/recall Command: npx skills add https://github.com/b08x/syncopated-context --skill recall-b08x
Fragmented recall across multiple AI tools makes it hard to track work, compare activity, and decide where to act next. This Skill aggregates sessions from Claude Code, Hermes, Gemini CLI, and OpenCode, aligns them with GitHub commits and backup diffs, and surfaces a clear next action.
Ask the recall skill to aggregate your sessions across all platforms for a given date range or topic and present a single, high-leverage action.
High-intent search queries and answers about installing and using this skill.
To aggregate AI coding sessions across multiple platforms, this Skill extracts and correlates user sessions from Claude Code, Hermes, Gemini CLI, and OpenCode into a unified recall view. It aligns these sessions with GitHub commits and backup diffs to provide a single high-leverage next action.
Recall correlates GitHub activity with AI tool sessions by mapping GitHub commits and PR activity against sessions from Claude Code, Hermes, Gemini CLI, and OpenCode. This integration aligns code changes with your conversational work to track progress and compare activity across platforms.
Yes, you can filter aggregated sessions by date ranges or specific topics using temporal and topic-based queries. The Skill processes these filters across your multi-platform sessions and backup diffs to synthesize a single highest-leverage action for your specified timeframe.
Restic backups are supported for mapping file changes to work across platforms through backup diff analysis. The Skill uses these backup diffs alongside GitHub activity to correlate file changes with your multi-platform sessions, providing a comprehensive recall view.
The best way to scale recall across large session histories is by using the optional ck-search indexing module. This modular RAG implementation indexes large recall histories from Claude Code, Hermes, Gemini CLI, and OpenCode, enabling efficient temporal and topic-based queries without performance degradation.
The recall skill decides on a single next action by synthesizing correlated data from multi-platform sessions, GitHub commits, PR activity, and backup diffs. It analyzes this aggregated context to surface one highest-leverage action you should take next, reducing decision fatigue from fragmented tool usage.
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