Knuckles-Team Social Media Influencer Workflow
CONCEPT:SOCIAL-001
Prepares a live stream broadcast title, updates style details, announces the live stream, and engages the audience using owncast-agent tools.
Steps
Step 0: Social Media Influencer
Agent: content-creator
Tools: graph_query, document_tools
Update the live stream broadcast title, welcome message text, and style customization details using the owncast_objects and owncast_internal tools.
Expected: stream_status, metadata
Step 1: Owncast Agent
Agent: media-processor
Tools: graph_analyze
Announce stream live status to connected social networks. Trigger an initial welcome notification message in the live stream chat using owncast_external and owncast_chat tools.
Expected: system_chat_post, notification
Step 2: KG Persistence [depends_on: owncast-agent]
Agent: media-processor
Tools: graph_write
Persist workflow results as nodes and edges in the Knowledge Graph. Create appropriate typed nodes with metadata and link to existing domain entities.
Output
- Social Media Influencer results persisted in KG
- Structured report (MD/PDF)
- Audit trail with timestamps and agent attributions
Execution
Run this workflow as a dependency-ordered DAG. Steps with no unmet depends_on run in parallel; dependents run after their prerequisites complete.
- Run first (in parallel): Step 0 — Social Media Influencer; Step 1 — Owncast Agent
- After level 0: Step 2 — KG Persistence
Execution: If graph-os is reachable, offload the whole DAG via graph_orchestrate action=execute_workflow (or the kg-delegate skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet depends_on in parallel, then their dependents.