ai-core/README.md

@@ -1,106 +1,7 @@
-# AI Core — SnS Network Solutions
+# AI Core
 
-The holding company's internal AI team. A **strict hierarchy**: one leader agent
-(**Chief**) is the single point of contact and routes work to a lean set of
-specialists. Nothing runs unless it's necessary to the business.
+## Project Overview
+This project is the core of our AI system, managing various agents and their functionalities.
 
-> **Goal:** all services eventually run on AWS (EC2 + Bedrock). **For now** it runs on
-> the home server `ws` in a VM. The stack is containerized so it moves between the two
-> **unchanged** — the VM is disposable; this git folder is the source of truth.
-
-## Chain of command
-
-```
-        SAM  (owner / CEO — final authority, approval gates)
-         │   you talk to ONE agent
-        CHIEF  (team leader — routes, decides, aggregates, enforces gates)
-         │   specialists report UP only, never to each other
-   ┌─────┼─────┐
- SCOUT  SCRIBE  (LEDGER — add when billing starts)
-research  docs
-```
-
-- You only ever message **Chief**. Specialists have no direct channel to you.
-- Specialists only talk to **Chief** — no lateral messaging (enforced by config).
-- Chief cannot send external comms, move money, or make legal promises — those
-  escalate back to you. Chief runs the team; you stay CEO.
-
-## Roster (lean — only what the business needs now)
-
-| Agent | Role | Status |
-|-------|------|--------|
-| **Chief** | Team leader / orchestrator. Single point of contact, routing, aggregation, approval gates. | Active |
-| **Scout** | Research & competitive intel. Read-only, informational. | Active |
-| **Scribe** | Documents — proposals, SOWs, NDAs, SOPs — from templates, held for review. | Active |
-| Ledger | Bookkeeping/billing prep. Generates, never sends or pays. | Add when invoicing starts |
-
-Add specialists *under* Chief as the business creates work for them. The command
-structure never changes — that's the point.
-
-## Layout
-
-```
-ai-core/
-├── docker-compose.yml     OpenClaw gateway (image ghcr.io/openclaw/openclaw, :18789)
-├── .env.example           config template — copy to .env, fill in, never commit .env
-├── .gitignore
-├── agents/                canonical agent definitions (version-controlled)
-│   ├── chief/             team leader
-│   ├── scout/             research specialist
-│   └── scribe/            document & visual specialist
-│       each agent folder holds its OpenClaw workspace:
-│         SOUL · IDENTITY · USER · AGENTS · TOOLS · HEARTBEAT · MEMORY
-│         + skills/   knowledge/   projects/
-├── knowledge/             shared knowledge base — sns.md (brand foundation) + research/reference docs
-└── state/                 runtime state + sessions (gitignored, created on first run)
-```
-
-## Run it (on the `ws` VM)
-
-Prereqs: a Linux VM with Docker + Docker Compose, and ≥4GB RAM (OpenClaw OOMs under 2GB).
-
-```bash
-cp .env.example .env        # then fill in your OpenAI API key + model refs
-docker compose up -d
-docker compose logs -f gateway
-```
-
-The gateway binds to `127.0.0.1:18789` only — it is **not** exposed to the internet.
-Reach the web UI over Tailscale or an SSH tunnel:
-
-```bash
-ssh -L 18789:127.0.0.1:18789 <user>@ws   # then open http://localhost:18789
-```
-
-**Register the agents** (first run) — the canonical SOUL.md files live in `agents/`;
-register each with the gateway so it picks them up:
-
-```bash
-docker compose exec gateway openclaw agents add chief
-docker compose exec gateway openclaw agents add scout
-docker compose exec gateway openclaw agents add scribe
-docker compose exec gateway openclaw agents list --bindings
-```
-
-> ponytail: exact `agents add` workflow + workspace path (`~/.openclaw/agents/<id>/workspace/SOUL.md`)
-> should be confirmed against https://docs.openclaw.ai on first run — ceiling: this is a
-> one-time manual registration step, not yet automated. Upgrade path: a bootstrap script
-> that syncs `agents/*/SOUL.md` into the state volume on `up`.
-
-## LLM backend — OpenAI / ChatGPT (current)
-
-OpenClaw talks to OpenAI via an **API key**.
-
-- **On `ws` now:** put your `OPENAI_API_KEY` in `.env` (see `.env.example`) and set the
-  model refs. Route routine work to a small/fast model and reasoning to a strong one to
-  control cost.
-- The key is the only credential needed — no cloud account required to run on `ws`.
-
-## Move to AWS + Bedrock (future goal)
-
-The end goal is to run this same stack on AWS with Amazon Bedrock. When we migrate, run the
-*same* `docker compose up` on an EC2 instance (t3.large, 8GB): drop the `OPENAI_*` keys,
-attach an **IAM instance role** so OpenClaw uses Bedrock via the AWS credential chain, put a
-Bedrock VPC endpoint in front, and reach the gateway over Tailscale/SSM. **The agents,
-skills, and compose file are identical** — only the provider config changes. That backend
-portability is the whole point of this design.
+### Scripts
+- `project_manager.py`: A command-line interface to manage tasks for different projects.

ai-core/scripts/project_manager.py

@@ -0,0 +1,20 @@
+import argparse
+
+# Initialize the argument parser
+parser = argparse.ArgumentParser(description='Project Manager CLI')
+
+# Add subcommands for add, list, and complete
+subparsers = parser.add_subparsers(dest='command', help='Sub-commands help')
+add_parser = subparsers.add_parser('add', help='Add a new task')
+list_parser = subparsers.add_parser('list', help='List all tasks')
+complete_parser = subparsers.add_parser('complete', help='Mark a task as complete')
+
+# Parse the arguments
+args = parser.parse_args()
+
+if args.command == 'add':
+    print(f'Adding new task...')
+elif args.command == 'list':
+    print(f'Listing all tasks...')
+elif args.command == 'complete':
+    print(f'Marking a task as complete...')