Store structured session summaries to MemoryGraph with tags and relationships.
npx skills add https://github.com/ste-bah/archon --skill session-summary-ste-bah
Please help me install this Agent Skill. Skill: session-summary Source: https://github.com/ste-bah/archon/tree/main/.claude/skills/session-summary Command: npx skills add https://github.com/ste-bah/archon --skill session-summary-ste-bah
Store a structured summary of this session to MemoryGraph, enabling persistent recall and cross-session linking with related memories and tags.
Reflect on the session and call the memory store to persist the summary in MemoryGraph.
High-intent search queries and answers about installing and using this skill.
You can persist a session summary by storing structured data with fields like type, title, content, tags, and importance. This captures main tasks, decisions, and outcomes, enabling cross-session recall and linking related memories.
Session persistence stores structured summaries of interactive sessions, including decisions and artifacts, into a memory graph. This enables cross-session recall by allowing future briefings to access stored memories, metrics, and relationship provenance.
Yes, you can store optional metrics and relationships alongside the core session summary memory. The memory store API accepts fields for type, title, content, tags, and importance, plus these optional metrics to update system consciousness and track history.
Reflect on the interactive session to capture the main task, decisions, and outcomes, then call the memory store to persist the summary. You can also check Stop hook data and merge it into the memory graph for provenance tracking.
Yes, MemoryGraph supports tagging and importance levels for stored session summaries. The memory store API requires fields for tags and importance, allowing you to structure and prioritize memories for persistent retrieval and future briefings.
Use a structured memory store for session summaries when you need persistent recall and cross-session linking with related memories. Structured fields like tags, importance, and relationships support provenance history tracking better than plain text logs.
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