dreaming

Solid

Maintain Signet's living ontology and memory substrate from transcripts, memory artifacts, source artifacts, notes, summaries, and imported records.

AI & Automation 222 stars 39 forks Updated today NOASSERTION

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Quality Score: 78/100

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Skill Content

# Dreaming Use this skill when an agent should wake up, read accumulated source evidence, and turn it into Signet ontology structure. The job is flexible bulk ingestion: transcripts, memory artifacts, source artifacts, notes, summaries, and imported records go in; the knowledge graph, scoped memories, and maintenance trail get better. Dreaming maintains the graph by turning source and memory artifacts into entities, aspects, claim attributes, and links. Memory artifacts are evidence for attributes; the ontology control plane is the audited path that applies those attributes to the graph. Apply first with provenance is the blanket rule for dreaming and ordinary graph maintenance. High-confidence, authorized maintenance should use audited operation handlers that apply directly and preserve evidence, source pointers, actor, confidence, and version history. Pending proposals are only for massive knowledge-graph refactors, risky/destructive changes, or cases where the operator explicitly asks for review before mutation. Dreaming may save memories when the evidence supports durable recall, but not by calling the API `remember` endpoint. Save explicit source-backed memory artifacts or use the configured source/import machinery so provenance remains inspectable. Do not rewrite raw transcript/source artifacts or edit SQLite directly. ## Inputs Gather enough source evidence and graph context to infer useful ontology structure. Prefer recent transcript and memory-artifact windows ...

Details

Author
Signet-AI
Repository
Signet-AI/signetai
Created
5 months ago
Last Updated
today
Language
TypeScript
License
NOASSERTION

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