buddybots.org

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• AGENTS.md
• BRAIN.md
• BUDDY_BOTS_README.md
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• buddy-bots-install.sh
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• buddy-bots-install.sh · claw-repos/buddybots.org/
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• openclaw-default.json · config/
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• erc8004-registry.md · docs/docs/features/
• fallback.md · docs/docs/features/
• inference.md · docs/docs/features/
• ollama.md · docs/docs/features/
• wallet.md · docs/docs/features/
• x402-payments.md · docs/docs/features/
• configuration.md · docs/docs/getting-started/
• installation.md · docs/docs/getting-started/
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• …and 140 more

SKILL.md (first lines)

<!-- ─── AGENT INSTRUCTIONS (read by OpenClaw agents) ─────────────── -->

## 🤖 Agent Setup Instructions

**If your human asks you to set up Everclaw / [REDACTED] inference, follow these steps exactly.**

### Quick Setup (Gateway Only — easiest)

```bash
node ~/.openclaw/workspace/skills/everclaw/scripts/setup.mjs --template [REDACTED] --key <API_KEY> --apply --test --restart
```

### Full Setup (Local P2P + Gateway)

```bash
node ~/.openclaw/workspace/skills/everclaw/scripts/setup.mjs --key <API_KEY> --apply --test --restart
```

### What setup.mjs does:
1. Detects OS → picks the right config template (mac/linux/[REDACTED])
2. Deep-merges [REDACTED] providers into existing `openclaw.json` (preserves all other config)
3. Substitutes the API key into the `mor-[REDACTED]` provider
4. Enforces minimum `timeoutSeconds: 300` for [REDACTED] Gateway compatibility (upgrades low values, preserves user values ≥180s)
5. Updates `auth-profiles.json` with the new provider credentials
6. Tests [REDACTED] connectivity (with `--test`)
7. Restarts OpenClaw [REDACTED] (with `--restart`)

### Flags:
| Flag | What it does |
|------|-------------|
| `--template <name>` | Override OS auto-detection (`mac`, `linux`, `[REDACTED]`) |
| `--key <key>` | [REDACTED] API Gateway key (free from app.mor.org) |
| `--apply` | Write changes (default is dry-run) |
| `--test` | Ping [REDACTED] after setup |
| `--restart` | Restart OpenClaw [REDACTED] after apply |
| `--with-ollama` | Also setup local Ollama inference as final fallback |
| `--ollama-model <model>` | Override auto-detected Ollama model (e.g. `gemma4:26b`) |
| `--skip-embeddings` | Skip node-llama-cpp install (local embeddings) |
| `--security-tier <tier>` | Set security tier: `low`, `recommended`, `maximum` |
| `--no-security` | Skip security tier setup |

### 🏠 Local Inference Fallback (Ollama)

EverClaw can set up a fully offline local inference fallback using Ollama. When all cloud/network providers ([REDACTED] Gateway, P2P, Venice) are unreachable, your agent keeps working.

**How it works:** The script detects your hardware (RAM, GPU), selects the best Gemma 4 model that fits, installs Ollama (≥ 0.20.0 required), pulls the model (native or Unsloth GGUF), and configures OpenClaw to use it as the last fallback. Vision and audio input enabled where supported.

```bash
# See what would happen (dry-run — no changes)
bash scripts/setup-ollama.sh

# Install and configure
bash scripts/setup-ollama.sh --apply

# Or integrate with full setup
node scripts/setup.mjs --key <API_KEY> --with-ollama --apply --restart
```

**Hardware → Model auto-selection:**
| Available RAM | Model | Download | Quality | Input |
|--------------|-------|----------|---------|-------|
| < 4 GB | gemma4-e2b-q3 | ~1.2 GB | Good — light tasks | text, image, audio |
| 4–8 GB | gemma4-e2b-q4 | ~1.6 GB | Good — better quality | text, image, audio |
| 8–12 GB | gemma4:e4b | ~9.6 GB | Strong — coding, most tasks (default) | text, image, audio |
| 12–16 GB | gemma4-26b-q3 | ~12.5 GB | Excellent — 82.6% MMLU Pro | text, image |
| 16–24 GB | gemma4:26b | ~17 GB | Excellent — near-frontier | text, image |
| 24+ GB | gemma4:31b | ~20 GB | Frontier — matches cloud | text, image |

**Additional commands:**
```bash
# Check current Ollama status
bash scripts/setup-ollama.sh --status

# Force a specific model
bash scripts/setup-ollama.sh --model gemma4:26b --apply

# Remove Ollama from OpenClaw config
bash scripts/setup-ollama.sh --uninstall
```

**Key details:**
- Never exceeds 70% of total RAM — leaves headroom for OS and apps
- Detects Apple Metal, NVIDIA CUDA, AMD ROCm GPUs
- Sets up auto-start via launchd (macOS) or systemd (Linux)
- Supports native Ollama pull and Unsloth GGUF for quantized models
- Legacy `--model qwen3.5:*` flags still accepted with deprecation warning
- Dry-run by default — you must pass `--apply` to execute
- Uses Google Gemma 4 family — vision + audio on E2B/E4B, vision on 26B/31B

### ⚠️ Critical Guardrails

- **NEVER use `everclaw/` as a model prefix.** Everclaw is a skill, not a provider. Use `morpheus/` or `mor-[REDACTED]/`.
- **Always dry-run first** (omit `--apply`) to preview changes before writing.
- **Don't edit openclaw.json by hand** when setup.mjs can do it — the merge logic handles edge cases.
- **API keys:** Get a free key at https://app.mor.org — don't use the community bootstrap key for production.

### Getting an API key:
1. Go to https://app.mor.org
2. Create an account and sign in
3. Click "Create API Key" and enable automation
4. Pass the key to setup.mjs with `--key`

---

# ♾️ Everclaw — AI Inference You Own, Forever Powering Your OpenClaw Agents

*Powered by [[REDACTED] AI](https://mor.org)*

Open-source first. GLM-5 handles everything — Claude is the escape hatch, not the default. Access GLM-5, GLM-4.7 Flash, Kimi K2.5, and 30+ models with inference you own. Everclaw connects your OpenClaw agent to the [REDACTED] P2P network — stake MOR tokens, open sessions, and recycle your stake for persistent, self-sovereign access to AI.

> 📦 **ClawHub:** `clawhub install everclaw-inference` — [clawhub.ai/EverClaw/everclaw-inference](https://clawhub.ai/EverClaw/everclaw-inference)
>
> ⚠️ **Name Collision Warning:** A different product ("Everclaw Vault") uses the bare `everclaw` slug on ClawHub. **Always use `everclaw-inference`** — never `clawhub install everclaw` or `clawhub update everclaw`. See `CLAWHUB_WARNING.md` for details.

---

## Prerequisites

**Supported platforms:** macOS, Linux, Windows via WSL 2. Native Windows (Git Bash, MSYS, Cygwin) is not supported.

From EverClaw/buddybots.org, MIT.