Percept Summarize
by @jarvis563
Generates AI summaries of conversations after silence, extracting entities, action items, and relationships for searchable meeting notes and context retrieval.
clawhub install percept-summarizeπ About This Skill
percept-summarize
Automatic conversation summaries with entity extraction and relationship mapping.
What it does
When a conversation ends (60 seconds of silence), Percept generates an AI-powered summary with extracted entities (people, companies, topics), action items, and relationship connections. Summaries are stored locally and searchable.
When to use
Requirements
How it works
1. Conversation ends (60s silence timeout) 2. Percept builds a speaker-tagged transcript 3. Sends transcript to OpenClaw for AI summarization 4. Extracts entities (people, orgs, topics) and relationships 5. Stores summary + entities in SQLite 6. Entities linked via relationship graph (works_on, client_of, mentioned_with)
Entity resolution
5-tier cascade for identifying entities: 1. Exact match (confidence 1.0) 2. Fuzzy match (0.8) β handles typos, nicknames 3. Contextual/graph (0.7) β uses relationship connections 4. Recency (0.6) β recently mentioned entities ranked higher 5. Semantic search (0.5) β vector similarity via LanceDB
Querying summaries
Summaries are searchable via the Percept dashboard (port 8960) or SQLite directly:
SELECT * FROM conversations WHERE summary LIKE '%action items%' ORDER BY end_time DESC;
Full-text search via FTS5:
SELECT * FROM utterances_fts WHERE utterances_fts MATCH 'project deadline';