- skills/multi-angle-orchestration/SKILL.md: SOP for single-source fan-out
(delegate_task leaf workers, NO external AIs) of >=5 angles + converge.
- brain-core: ingest orchestration-runs/*.json as source 'orchestration'
so past runs are searchable in Brain Search.
- server.py: POST /api/orchestrate (optional headless fan-out of the 3
built-in agents) + GET /api/orchestrate/runs; persist runs to
data/orchestration-runs/<id>.json and upsert to brain.
- dashboard/pages/orchestration.js: launch runs + review past runs.
- skills/multi-agent-run/SKILL.md + api helpers + nav entry.
1) Brain Search page (dashboard/pages/brain-search.js): mirrors Agent
Insights; queries /api/brain-index/search with source filter + live
index stats; nav entry + PAGE_TITLES added.
2) Scheduled auto-ingest: scheduler gains endpoint-style jobs
(run_endpoint_via_api) so non-skill maintenance tasks can be cron'd;
new job brain-index-ingest-job.json re-indexes every 30 min.
3) Agents auto-upsert learnings: run_skill wrap-up now calls
record_brain_learning() so each skill run is immediately searchable
in the unified index (best-effort, never breaks the run).
Fixed a regression where AGENT_STATS_FILE def was dropped during the
brain-learning helper insertion (would have broken all skill runs).
Verified live: brain search returns ranked results; run_skill wrap-up
upserts a searchable doc; scheduler imports + job validates.
New /api/agent-insights endpoint aggregates real data (chat-history,
cost-history, agent-time, agent-registry, router-keywords) to show:
- which agent you chat with most (user turns)
- which agent spends the most time on tasks (derived agent-time)
- which agent is best suited for what (registry desc + router keywords + roles)
- which models you use most per agent (cost-history)
Dashboard page (agent-insights.js) with stat cards, two Chart.js bar
charts, suite cards, models-per-agent table, and full per-agent
breakdown. Verified live in browser against real data.
Two real gaps: the Skills Hub had no way to create a new skill (with
a SKILL.md) at all - the only 'Install' flow was the Plugin registry,
which just records a name in a JSON file, not an actual skill folder.
And the Context Files panel was read-only, just listing filenames
with no way to view, edit, add, or delete their contents.
Adds POST /api/skills (create, with SKILL.md content), PUT
/api/skills/{name} (edit SKILL.md), and GET/PUT/DELETE
/api/skills/{name}/context/{filename} for context files - all
validated through the same regex-allowlist + resolved-path
containment pattern already used for kanban tasks. Dashboard gets a
'+ New Skill' button, an editable SKILL.md view, and per-file
edit/delete plus 'Add File' in the Context Files panel.
The Kanban detail modal's Delete button called api.deleteKanbanTask(),
which didn't exist on the client, and there was no backend route for
it either - clicking Delete just threw 'api.deleteKanbanTask is not
a function'. Add both the client method and the backend endpoint.
The previous Terminal ran one command at a time via subprocess.run
and returned its output - it couldn't run interactive programs
(colors, live input, TUIs like gemini's chat/auth flow), which is
what a terminal actually needs to do.
Backend: new /ws/terminal WebSocket endpoint spawns a real shell
attached to a pseudo-terminal (stdlib pty on POSIX, pywinpty/ConPTY
on Windows) and streams raw I/O bidirectionally, with resize support.
Replaces the old POST /api/terminal/run and GET /api/terminal/session
endpoints entirely.
Frontend: terminal.js now loads xterm.js + the fit addon from CDN
and renders a real terminal emulator wired to the WebSocket, instead
of a scrollback div with a single input line.
Verified on this Linux sandbox via raw WebSocket tests: shell spawns
correctly, commands execute and echo real output, resize propagates
to the PTY (confirmed via ), and closing the connection
cleanly kills the shell process with no orphans (interactive bash
ignores SIGTERM by default, so cleanup uses SIGKILL). Could not
visually verify the xterm.js browser rendering in this sandbox since
its egress policy blocks the CDN (cdn.jsdelivr.net) outright - same
CDN this app already uses for chart.js, so expected to work on a
normal machine; please confirm on Windows.
Assigning a task to opencode, hermes, or gemini now actually runs it:
creating or PATCHing a task with one of those assignees moves it to
in_progress and hands the title+body to execute_agent() in a
background thread. On completion the agent's response is appended as
a task comment and the task is marked done (success) or blocked
(timeout/error), matching the existing block/complete state machine.
Adds POST /api/kanban/tasks/{id}/dispatch for manual dispatch/retry,
and makes the previously-stubbed POST /api/kanban/dispatch actually
scan todo/ready tasks with an agent assignee and dispatch each one.
Dashboard: the assignee field is now a select of the three agents,
the task detail modal shows an activity log of past agent runs and a
Dispatch button, and polls every 3s while a task is in_progress. Also
fixed a pre-existing bug where the detail modal read a nonexistent
kanbanData.tasks field (the board API only returns columns), so
clicking a card silently did nothing before this fix.
Adds a real shell terminal to the dashboard sidebar: POST
/api/terminal/run executes a command via subprocess in a
server-tracked working directory (with cd support), and GET
/api/terminal/session returns the current cwd. The frontend renders
a scrollback panel with command history (up/down arrows) styled to
match the existing chat UI.
Local-only power feature: it executes arbitrary shell commands, same
trust model as the existing agent CLIs the dashboard already shells
out to.
New features:
- Kanban Board: Visual task management with drag-and-drop, filter, priority, block/unblock
- Goals: Project targets with progress tracking, auto-sync to brain/active-projects.md
- Journal: Daily entries stored as brain/journal/YYYY-MM-DD.md with search
- Agent Health: Real-time monitoring of 3 agents (opencode/hermes/gemini)
- Smart Router: Keyword-based task routing with confidence scoring
- Learning Analytics: Skill evaluation scores and performance trends
- Session Replay: Browse and replay past opencode sessions
Technical changes:
- 30 new API endpoints across all 7 features
- api.patch() method added for PATCH support
- UI modernization: glass morphism cards, gradients, glow effects, skeleton loaders, empty states
- New CSS section (v0.2.0) with kanban board, goal cards, journal entries, agent health cards, smart router suggestions, chart cards, session messages
- 7 new sidebar nav items under Workflow and Monitoring sections
- All changes are additive (zero breaking changes to existing 13 pages / 28 endpoints)
- Full smoke test verified: every endpoint returns correct data
- AGENTS.md single source of truth with 51+10 features
- FastAPI backend with 20+ REST endpoints
- 15 skills with self-improvement (eval + learnings)
- Web SPA dashboard with 12 pages
- Agent configs for opencode, Hermes, Gemini CLI
- APScheduler, plugin registry, standards system
- 10 prompt templates, cost analytics, backup/restore
Austin
zumayaaustin-creator
Claude
modimihir07