Convert live session digests and execution traces into narrative and memory JSON.
npx skills add https://github.com/mandubian/autonoetic --skill autonoetic-digest
Please help me install this Agent Skill. Skill: autonoetic.digest Source: https://github.com/mandubian/autonoetic/tree/main/agents/digest Command: npx skills add https://github.com/mandubian/autonoetic --skill autonoetic-digest
This skill consolidates post-session activity into a succinct digest, transforming raw session data into durable memories and a readable narrative, reducing manual post-mortem work.
Digest the latest session transcript to generate a concise narrative and memory entries.
High-intent search queries and answers about installing and using this skill.
You can turn post-session data into durable memories by processing live session digests and execution traces to produce concise narratives and structured memory entries. This condenses raw session activity into readable takeaways for future reference.
The best way to generate a narrative from an execution trace is to process the raw session data through a digesting workflow that outputs a structured JSON object containing a readable narrative string and an array of durable memory entries.
Yes, you can capture error analysis takeaways from a live session digest by consolidating execution traces and error data into structured memory entries with types, tags, and confidence fields for ongoing reliability improvements.
No, generating a post-session digest requires no external dependencies, allowing you to directly process live session transcripts and execution traces into narratives and structured memory arrays within your existing environment.
Post-session memory stabilization outputs a structured JSON object containing a narrative string and a memories array, where each memory entry includes specific fields for type, content, tags, and an optional confidence level.
You need to process session digests for gateway-internal context during post-session reviews and internal gateway diagnostics, transforming raw maintenance workflow data into durable memories to reduce manual post-mortem work.
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