agentic-os

Commit Graph

Author	SHA1	Message	Date
Austin	e723908916	feat: continuous-learning loop for the central brain - brain/graph/learn-loop.sh: rebuild+cluster -> (LLM-tier) deep-extract corpus -> merge -> measure & heuristically optimize (orphan rate, community balance, size) -> record metrics.json + learnings.md -> sync to Windows - brain/corpus/{diagrams,designs,notes}/: drop sources for the brain to learn - cron agentic-os-brain-rebuild now runs the learn-loop (compounding) - README documents the learning tiers (offline structural vs LLM semantic) Verified: 614 nodes, 1024 links, 0.2% orphans after optimization; no node loss.	2026-07-26 15:07:40 -07:00
Austin	96d8281b9b	Wire up dynamic agent registry, integrations, agent-time tracking, UI modernization - server.py: dynamic agent execution engine (cli/http/mcp), live agent registry (/api/agents register/unregister), integrations API, agent stats & skill scoring, kanban task delete, plugin uninstall, agent-time tracking + /test page - dashboard: modernized agent-health, plugins marketplace, smart-router, styles; added agent-time monitor page + terminal page - scheduler.py rewrite; start.sh / start-agentic-os.sh improvements - skills: added firebase-*, notion-knowledge-capture, xcode-project-setup, audit/test plugins; updated learnings across skills - brain/ docs + data registry files (agent-registry, integrations, router-keywords) - .gitignore: exclude runtime artifacts (pid, graphify-out, logs) Verified live on :8081 - all new endpoints return 200 and register/unregister persists to data/agent-registry.json.	2026-07-25 12:27:26 -07:00

Author

SHA1

Message

Date

Austin

e723908916

feat: continuous-learning loop for the central brain

- brain/graph/learn-loop.sh: rebuild+cluster -> (LLM-tier) deep-extract corpus
  -> merge -> measure & heuristically optimize (orphan rate, community balance,
  size) -> record metrics.json + learnings.md -> sync to Windows
- brain/corpus/{diagrams,designs,notes}/: drop sources for the brain to learn
- cron agentic-os-brain-rebuild now runs the learn-loop (compounding)
- README documents the learning tiers (offline structural vs LLM semantic)

Verified: 614 nodes, 1024 links, 0.2% orphans after optimization; no node loss.

2026-07-26 15:07:40 -07:00

Austin

96d8281b9b

Wire up dynamic agent registry, integrations, agent-time tracking, UI modernization

- server.py: dynamic agent execution engine (cli/http/mcp), live agent
  registry (/api/agents register/unregister), integrations API, agent stats
  & skill scoring, kanban task delete, plugin uninstall, agent-time tracking
  + /test page
- dashboard: modernized agent-health, plugins marketplace, smart-router,
  styles; added agent-time monitor page + terminal page
- scheduler.py rewrite; start.sh / start-agentic-os.sh improvements
- skills: added firebase-*, notion-knowledge-capture, xcode-project-setup,
  audit/test plugins; updated learnings across skills
- brain/ docs + data registry files (agent-registry, integrations, router-keywords)
- .gitignore: exclude runtime artifacts (pid, graphify-out, logs)

Verified live on :8081 - all new endpoints return 200 and register/unregister
persists to data/agent-registry.json.

2026-07-25 12:27:26 -07:00

2 Commits