dtoro 532310bb4b feat(tasks): phase 3 — close the knowledge loop (complete_task + retrieval)
Adds the compounding knowledge loop the task model is built around:

- complete_task(outcome, summary): a nomos-LOCAL, session-scoped tool (the
  shared MCP server has no session id). Introduces the local-tool mechanism —
  buildTools appends task tools, the agent loop routes them to handleTaskTool
  instead of the MCP client. Sets the task's terminal status/outcome/summary,
  mirrors it onto the task entity, and emits task.status.
- Knowledge → task linkage: after a successful upsert_knowledge in a task,
  nomos links the note to the task entity (documents) and emits
  knowledge.recorded, so the task's outcome view shows what it learned. The
  note's about-link to the involved entity (written by upsert_knowledge) is the
  retrieval path future tasks use.
- SOUL: every chat is a task loop — retrieve prior knowledge FIRST
  (get_entity_knowledge on the target), plan, execute, record learnings, then
  complete_task. Scales down for trivial read-only tasks.
- deleteSession now cleans up the task entity, its relationships, and its
  task-scoped events (was orphaning them); the knowledge doc itself and its
  about-links survive, as knowledge should outlive the task.

Verified end-to-end: a task recorded a note and completed; task.status +
knowledge.recorded hit the SSE stream; status=done/outcome=success persisted;
the note linked to both lxc:caddy (retrieval) and the task; a future
get_entity_knowledge(lxc:caddy) surfaces it; delete cleaned edges+events (0/0/0)
while the knowledge survived.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-11 12:43:29 +02:00

Oikos

Agentic homelab operating system written in Go. Single binary (cmd/oikos), Docker-deployed on mac-mini, with a standalone Nomos MCP agent gateway (cmd/nomos). Manages the hubris Proxmox homelab autonomously — observes state, classifies actions against policy, executes approved procedures over SSH, learns from outcomes, and escalates when uncertain.

For agents running on enrolled clients: start with AGENTS.md. For client machines: see CLIENTS.md. For developers: see CONTRIBUTING.md.

Quick start

# Dev stack (postgres + api + scheduler + notifier)
docker compose --profile dev up -d

# Full stack (adds Nomos agent gateway)
docker compose --profile full up -d

# Build standalone binary
go build -o bin/oikos -tags timetzdata ./cmd/oikos

# Run all roles in one process (dev mode)
OIKOS_DATABASE_URL="postgres://oikos:oikos_dev@localhost:5432/oikos?sslmode=disable" \
  go run ./cmd/oikos all

Architecture

                  ┌──────────────────────────────────┐
                  │         mac-mini (Docker)         │
                  │                                   │
  Workstation ─── │  nomos (8092) ──MCP── api (8090) │
  (mesh)          │    MCP gateway      REST + MCP    │
                  │                                   │
                  │  scheduler ── notifier ── postgres │
                  │  (observe)    (Matrix)   (Timescale)│
                  └──────────────────────────────────┘
Component Port Role
oikos api 8090 REST API + MCP server (15 tools)
oikos scheduler Probe runner, signal lifecycle, metrics
oikos notifier Approval tokens, Matrix alerts
nomos serve 8092 MCP client gateway, query routing

Phases

Phase Status Description
1 — Ontology + DB TimescaleDB, migrations, seeds, blast_radius
2 — API OpenAPI-first REST + MCP, auth, SSE, audit
3 — Control loop Scheduler, actuator, learning, classifier, notifier
4 — Nomos agent Standalone MCP client gateway, agent activity
5 — Secrets Infisical backend + SOPS fallback, rotation runbooks
6 — Deploy CI pipeline, cutover checklist, watchdog, rollback

Full plan: plans/2026-07-06-consolidate-oikos-control-plane-onto-mac-mini.md.

Operations

API endpoints

curl http://localhost:8090/api/v1/entities?type=service  # fleet
curl http://localhost:8090/api/v1/health                  # fleet health
curl http://localhost:8090/api/v1/agent-activity          # agent log

Nomos queries

# Structured tool call
curl -X POST localhost:8092/query -H "Content-Type: application/json" \
  -d '{"tool":"get_blast_radius","args":{"entity_id":"service:authentik"}}'

# Natural language
curl -X POST localhost:8092/query -H "Content-Type: application/json" \
  -d '{"query":"what depends on authentik?"}'

CLI

oikos migrate     # apply DB migrations
oikos seed        # ingest ontology/inventory/policy seeds
oikos export      # export DB state to YAML
oikos api         # serve REST + MCP
oikos scheduler   # run observe loop
oikos notifier    # run notification loop
oikos all         # all roles in one process
oikos secret list # enumerate SOPS secrets
oikos secret migrate  # SOPS → Infisical

Repo layout

cmd/oikos/          Go entry point — single binary
cmd/nomos/          Nomos MCP client gateway
internal/           Go packages (httpapi, mcp, scheduler, actuator, learning,
                    notifier, policy, secrets, db, config, ontology, domain,
                    knowledge)
api/openapi.yaml    API contract (OpenAPI 3.1)
migrations/         Forward-only SQL migrations (TimescaleDB)
seeds/              Bootstrap YAML (ontology, inventory, policy, knowledge)
compose/            Dockerfiles + Caddy config
scripts/            Deploy, watchdog, verification, rollback
nomos/              Nomos config, persona, skills
.agents/            Agent instruction files, shared conventions, skills
archive/            Historical reference (legacy wiki, plans, SOPS backups)
plans/              Design documents (active + done)
docs/adr/           Architecture decision records

For agents

See AGENTS.md for the full orientation. Quick reference:

  • Source of truth: DB (runtime) then seeds (bootstrap). Old wiki is archived at archive/knowledge/ — use MCP search_knowledge instead.
  • Mutations: classify against policy, request approval for destructive/config_mutation
  • Secrets: Infisical (primary) or SOPS (fallback) — never hardcode
Description
Agentic OS for running a Homelab
Readme 37 MiB
Languages
Go 53.1%
Svelte 25.7%
TypeScript 14%
Shell 3.8%
Python 1.7%
Other 1.5%