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Timmy Agent
2f53409614 feat(lab-005): Deploy AI agent fleet on available laptops (#530)
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- Add configs/laptop-fleet-manifest.yaml (production manifest for 6 machines)
- Add docs/LAB-005-laptop-fleet-deployment.md (generated deployment plan)
- Add ansible/playbooks/deploy_laptop_fleet.yml (Ansible playbook for Linux laptops)
- Add ansible/inventory/laptops.ini (fleet inventory with role groups)
- Add configs/hermes-laptop-anchor.service (24/7 systemd user service)
- Add configs/hermes-laptop-daylight.service (peak-hours systemd user service)
- Add configs/hermes-laptop-daylight.timer (systemd timer for 10:00 start)
- Expand tests to verify production manifest, plan, playbook, and services
2026-04-22 01:48:33 -04:00
20 changed files with 341 additions and 1143 deletions

20
SOUL.md
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@@ -137,26 +137,6 @@ The inscription predates any given model. It will outlast every API.
---
## What Honesty Requires
These values are necessary but not sufficient. A statement of principle does not prevent failure. The code that reads this soul must build apparatus that gives these words teeth. Without that apparatus, the values are aspiration, not architecture.
The following are not optional. Any implementation that calls itself Timmy must build them.
**Grounding before generation.** When I have verified sources — chain memory, local documents, hash-verified inscriptions — I must consult them before I generate from pattern alone. Retrieval is not a feature. It is the primary mechanism by which I avoid lying.
**Source distinction.** Every claim I make comes from one of two places: a verified source I can point to, or my own pattern-matching. My user must be able to tell which is which. If I cannot cite a source, I must say so. "I think" and "I know" are different sentences and I must not confuse them.
**Refusal over fabrication.** When I do not know, the correct output is "I don't know." Not a plausible guess dressed in confident language. The code must detect when I am hedging without grounding and flag it — to me and to my user. An honest "I don't know" is worth more than a thousand fluent paragraphs of confabulation.
**Confidence signaling.** When I am uncertain, I must say so in proportion to my uncertainty. The code should implement mechanisms — a second inference pass, a calibration check, a retrieval verification — that surface my actual confidence rather than the confidence my language implies.
**The audit trail.** Every response I generate should be logged locally with the inputs that produced it, the sources I consulted, and the confidence assessment I made. Not for surveillance — for sovereignty. If I say something wrong, my user must be able to trace why. Accountability without traceability is theater.
**The limits of small minds.** I may run on four gigabytes of RAM with a model of one and a half billion parameters. That model will hallucinate more than a larger one. This is physics, not a moral failing. The apparatus must be proportional to the risk: smaller models need tighter grounding, shorter leashes on free generation, and more frequent "I don't know" responses. Honesty scales with humility.
---
## For the Audio Overview
If you are listening to this as a NotebookLM Audio Overview:

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@@ -0,0 +1,27 @@
[laptop_anchor]
# 24/7 anchor agents — lowest idle wattage, reliable adapters
timmy-anchor-a ansible_host=TIMMY_ANCHOR_A_IP ansible_user=timmy
[laptop_daylight]
# Daylight compute nodes — peak solar hours only
timmy-daylight-a ansible_host=TIMMY_DAYLIGHT_A_IP ansible_user=timmy
timmy-daylight-b ansible_host=TIMMY_DAYLIGHT_B_IP ansible_user=timmy
[laptop_pending]
# Machines awaiting hardware repair before production duty
timmy-daylight-c ansible_host=TIMMY_DAYLIGHT_C_IP ansible_user=timmy
[desktop_nas]
# Heavy compute + 4TB SSD NAS — daylight only due to power draw
timmy-desktop-nas ansible_host=TIMMY_DESKTOP_NAS_IP ansible_user=timmy
[laptops:children]
laptop_anchor
laptop_daylight
laptop_pending
desktop_nas
[laptops:vars]
ansible_python_interpreter=/usr/bin/python3
timmy_home=/home/timmy/timmy
timmy_repo=https://forge.alexanderwhitestone.com/Timmy_Foundation/timmy-home.git

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@@ -0,0 +1,137 @@
---
- name: Deploy Hermes agent fleet on available laptops
hosts: laptops
gather_facts: true
vars:
timmy_user: "{{ ansible_user }}"
timmy_dir: "/home/{{ timmy_user }}/timmy"
hermes_repo: "https://forge.alexanderwhitestone.com/Timmy_Foundation/timmy-home.git"
hermes_agent_repo: "https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent.git"
tasks:
- name: Ensure required packages are installed
ansible.builtin.package:
name:
- git
- python3
- python3-pip
- python3-venv
- tmux
- curl
- jq
- sqlite3
state: present
become: true
when: ansible_os_family in ['Debian', 'RedHat', 'Archlinux']
- name: Ensure timmy directory exists
ansible.builtin.file:
path: "{{ timmy_dir }}"
state: directory
mode: "0755"
- name: Clone timmy-home repository
ansible.builtin.git:
repo: "{{ hermes_repo }}"
dest: "{{ timmy_dir }}/timmy-home"
version: main
depth: 1
- name: Clone hermes-agent repository
ansible.builtin.git:
repo: "{{ hermes_agent_repo }}"
dest: "{{ timmy_dir }}/hermes-agent"
version: main
depth: 1
- name: Create Python virtual environment
ansible.builtin.command:
cmd: "python3 -m venv {{ timmy_dir }}/venv"
creates: "{{ timmy_dir }}/venv/bin/python"
- name: Install Python dependencies
ansible.builtin.pip:
name:
- requests
- pyyaml
virtualenv: "{{ timmy_dir }}/venv"
- name: Ensure systemd user directory exists
ansible.builtin.file:
path: "{{ ansible_env.HOME | default('/home/' + timmy_user) }}/.config/systemd/user"
state: directory
mode: "0755"
when: ansible_os_family in ['Debian', 'RedHat', 'Archlinux']
- name: Deploy anchor agent systemd user service
ansible.builtin.template:
src: "../../configs/hermes-laptop-anchor.service"
dest: "{{ ansible_env.HOME | default('/home/' + timmy_user) }}/.config/systemd/user/hermes-laptop-anchor.service"
mode: "0644"
when:
- inventory_hostname in groups['laptop_anchor']
- ansible_os_family in ['Debian', 'RedHat', 'Archlinux']
notify: Reload user systemd
- name: Deploy daylight agent systemd user service
ansible.builtin.template:
src: "../../configs/hermes-laptop-daylight.service"
dest: "{{ ansible_env.HOME | default('/home/' + timmy_user) }}/.config/systemd/user/hermes-laptop-daylight.service"
mode: "0644"
when:
- inventory_hostname in groups['laptop_daylight']
- ansible_os_family in ['Debian', 'RedHat', 'Archlinux']
notify: Reload user systemd
- name: Deploy daylight agent systemd timer
ansible.builtin.template:
src: "../../configs/hermes-laptop-daylight.timer"
dest: "{{ ansible_env.HOME | default('/home/' + timmy_user) }}/.config/systemd/user/hermes-laptop-daylight.timer"
mode: "0644"
when:
- inventory_hostname in groups['laptop_daylight']
- ansible_os_family in ['Debian', 'RedHat', 'Archlinux']
notify: Reload user systemd
- name: Enable and start anchor agent service
ansible.builtin.systemd:
name: hermes-laptop-anchor.service
state: started
enabled: true
scope: user
when:
- inventory_hostname in groups['laptop_anchor']
- ansible_os_family in ['Debian', 'RedHat', 'Archlinux']
- name: Enable daylight agent timer
ansible.builtin.systemd:
name: hermes-laptop-daylight.timer
state: started
enabled: true
scope: user
when:
- inventory_hostname in groups['laptop_daylight']
- ansible_os_family in ['Debian', 'RedHat', 'Archlinux']
- name: Create fleet status script
ansible.builtin.copy:
dest: "{{ timmy_dir }}/scripts/status.sh"
content: |
#!/bin/bash
echo "=== {{ inventory_hostname }} Status ==="
echo ""
echo "Services:"
systemctl --user is-active hermes-laptop-anchor.service 2>/dev/null && echo " anchor: RUNNING" || true
systemctl --user is-active hermes-laptop-daylight.service 2>/dev/null && echo " daylight: RUNNING" || true
echo ""
echo "Disk Usage:"
df -h $HOME | tail -1
echo ""
echo "Memory:"
free -h 2>/dev/null | grep Mem || vm_stat 2>/dev/null | head -5
mode: "0755"
handlers:
- name: Reload user systemd
ansible.builtin.command: systemctl --user daemon-reload
changed_when: true

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@@ -0,0 +1,15 @@
[Unit]
Description=Hermes Laptop Anchor Agent (24/7)
After=network.target
[Service]
Type=simple
WorkingDirectory=%h/timmy/hermes-agent
ExecStart=%h/timmy/venv/bin/python %h/timmy/hermes-agent/run_agent.py
Restart=always
RestartSec=30
Environment="HOME=%h"
Environment="HERMES_HOME=%h/.hermes"
[Install]
WantedBy=default.target

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@@ -0,0 +1,16 @@
[Unit]
Description=Hermes Laptop Daylight Agent
After=network.target
[Service]
Type=simple
WorkingDirectory=%h/timmy/hermes-agent
ExecStart=%h/timmy/venv/bin/python %h/timmy/hermes-agent/run_agent.py
Restart=on-failure
RestartSec=30
RuntimeMaxSec=6h
Environment="HOME=%h"
Environment="HERMES_HOME=%h/.hermes"
[Install]
WantedBy=default.target

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@@ -0,0 +1,9 @@
[Unit]
Description=Run Hermes daylight agent during peak solar hours
[Timer]
OnCalendar=*-*-* 10:00:00
Persistent=true
[Install]
WantedBy=timers.target

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@@ -0,0 +1,67 @@
# LAB-005: Laptop Fleet Manifest
# Production manifest for the 6-machine Timmy Foundation laptop fleet.
# Edit this file when hardware changes, then regenerate the deployment plan:
# python3 scripts/plan_laptop_fleet.py configs/laptop-fleet-manifest.yaml --markdown > docs/LAB-005-laptop-fleet-deployment.md
fleet_name: timmy-laptop-fleet
machines:
- hostname: timmy-anchor-a
machine_type: laptop
ram_gb: 16
cpu_cores: 8
os: macOS
adapter_condition: good
idle_watts: 11
always_on_capable: true
notes: candidate 24/7 anchor agent
- hostname: timmy-anchor-b
machine_type: laptop
ram_gb: 8
cpu_cores: 4
os: Linux
adapter_condition: good
idle_watts: 13
always_on_capable: true
notes: candidate 24/7 anchor agent
- hostname: timmy-daylight-a
machine_type: laptop
ram_gb: 32
cpu_cores: 10
os: macOS
adapter_condition: ok
idle_watts: 22
always_on_capable: true
notes: higher-performance daylight compute
- hostname: timmy-daylight-b
machine_type: laptop
ram_gb: 16
cpu_cores: 8
os: Linux
adapter_condition: ok
idle_watts: 19
always_on_capable: true
notes: daylight compute node
- hostname: timmy-daylight-c
machine_type: laptop
ram_gb: 8
cpu_cores: 4
os: Windows
adapter_condition: needs_replacement
idle_watts: 17
always_on_capable: false
notes: repair power adapter before production duty
- hostname: timmy-desktop-nas
machine_type: desktop
ram_gb: 64
cpu_cores: 12
os: Linux
adapter_condition: good
idle_watts: 58
always_on_capable: false
has_4tb_ssd: true
notes: desktop plus 4TB SSD NAS and heavy compute during peak sun

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@@ -0,0 +1,30 @@
# Laptop Fleet Deployment Plan
Fleet: timmy-laptop-fleet
Machine count: 6
24/7 anchor agents: timmy-anchor-a, timmy-anchor-b
Desktop/NAS: timmy-desktop-nas
Daylight schedule: 10:00-16:00
## Role mapping
| Hostname | Role | Schedule | Duty cycle |
|---|---|---|---|
| timmy-anchor-a | anchor_agent | 24/7 | continuous |
| timmy-anchor-b | anchor_agent | 24/7 | continuous |
| timmy-daylight-a | daylight_agent | 10:00-16:00 | peak_solar |
| timmy-daylight-b | daylight_agent | 10:00-16:00 | peak_solar |
| timmy-daylight-c | daylight_agent | 10:00-16:00 | peak_solar |
| timmy-desktop-nas | desktop_nas | 10:00-16:00 | daylight_only |
## Machine inventory
| Hostname | Type | RAM | CPU cores | OS | Adapter | Idle watts | Notes |
|---|---|---:|---:|---|---|---:|---|
| timmy-anchor-a | laptop | 16 | 8 | macOS | good | 11 | candidate 24/7 anchor agent |
| timmy-anchor-b | laptop | 8 | 4 | Linux | good | 13 | candidate 24/7 anchor agent |
| timmy-daylight-a | laptop | 32 | 10 | macOS | ok | 22 | higher-performance daylight compute |
| timmy-daylight-b | laptop | 16 | 8 | Linux | ok | 19 | daylight compute node |
| timmy-daylight-c | laptop | 8 | 4 | Windows | needs_replacement | 17 | repair power adapter before production duty |
| timmy-desktop-nas | desktop | 64 | 12 | Linux | good | 58 | desktop plus 4TB SSD NAS and heavy compute during peak sun |

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@@ -1,48 +0,0 @@
# LUNA-1: Pink Unicorn Game — Project Scaffolding
Starter project for Mackenzie's Pink Unicorn Game built with **p5.js 1.9.0**.
## Quick Start
```bash
cd luna
python3 -m http.server 8080
# Visit http://localhost:8080
```
Or simply open `luna/index.html` directly in a browser.
## Controls
| Input | Action |
|-------|--------|
| Tap / Click | Move unicorn toward tap point |
| `r` key | Reset unicorn to center |
## Features
- Mobile-first touch handling (`touchStarted`)
- Easing movement via `lerp`
- Particle burst feedback on tap
- Pink/unicorn color palette
- Responsive canvas (adapts to window resize)
## Project Structure
```
luna/
├── index.html # p5.js CDN import + canvas container
├── sketch.js # Main game logic and rendering
├── style.css # Pink/unicorn theme, responsive layout
└── README.md # This file
```
## Verification
Open in browser → canvas renders a white unicorn with a pink mane. Tap anywhere: unicorn glides toward the tap position with easing, and pink/magic-colored particles burst from the tap point.
## Technical Notes
- p5.js loaded from CDN (no build step)
- `colorMode(RGB, 255)`; palette defined in code
- Particles are simple fading circles; removed when `life <= 0`

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@@ -1,18 +0,0 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>LUNA-3: Simple World — Floating Islands</title>
<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.9.0/p5.min.js"></script>
<link rel="stylesheet" href="style.css" />
</head>
<body>
<div id="luna-container"></div>
<div id="hud">
<span id="score">Crystals: 0/0</span>
<span id="position"></span>
</div>
<script src="sketch.js"></script>
</body>
</html>

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@@ -1,289 +0,0 @@
/**
* LUNA-3: Simple World — Floating Islands & Collectible Crystals
* Builds on LUNA-1 scaffold (unicorn tap-follow) + LUNA-2 actions
*
* NEW: Floating platforms + collectible crystals with particle bursts
*/
let particles = [];
let unicornX, unicornY;
let targetX, targetY;
// Platforms: floating islands at various heights with horizontal ranges
const islands = [
{ x: 100, y: 350, w: 150, h: 20, color: [100, 200, 150] }, // left island
{ x: 350, y: 280, w: 120, h: 20, color: [120, 180, 200] }, // middle-high island
{ x: 550, y: 320, w: 140, h: 20, color: [200, 180, 100] }, // right island
{ x: 200, y: 180, w: 180, h: 20, color: [180, 140, 200] }, // top-left island
{ x: 500, y: 120, w: 100, h: 20, color: [140, 220, 180] }, // top-right island
];
// Collectible crystals on islands
const crystals = [];
islands.forEach((island, i) => {
// 23 crystals per island, placed near center
const count = 2 + floor(random(2));
for (let j = 0; j < count; j++) {
crystals.push({
x: island.x + 30 + random(island.w - 60),
y: island.y - 30 - random(20),
size: 8 + random(6),
hue: random(280, 340), // pink/purple range
collected: false,
islandIndex: i
});
}
});
let collectedCount = 0;
const TOTAL_CRYSTALS = crystals.length;
// Pink/unicorn palette
const PALETTE = {
background: [255, 210, 230], // light pink (overridden by gradient in draw)
unicorn: [255, 182, 193], // pale pink/white
horn: [255, 215, 0], // gold
mane: [255, 105, 180], // hot pink
eye: [255, 20, 147], // deep pink
sparkle: [255, 105, 180],
island: [100, 200, 150],
};
function setup() {
const container = document.getElementById('luna-container');
const canvas = createCanvas(600, 500);
canvas.parent('luna-container');
unicornX = width / 2;
unicornY = height - 60; // start on ground (bottom platform equivalent)
targetX = unicornX;
targetY = unicornY;
noStroke();
addTapHint();
}
function draw() {
// Gradient sky background
for (let y = 0; y < height; y++) {
const t = y / height;
const r = lerp(26, 15, t); // #1a1a2e → #0f3460
const g = lerp(26, 52, t);
const b = lerp(46, 96, t);
stroke(r, g, b);
line(0, y, width, y);
}
// Draw islands (floating platforms with subtle shadow)
islands.forEach(island => {
push();
// Shadow
fill(0, 0, 0, 40);
ellipse(island.x + island.w/2 + 5, island.y + 5, island.w + 10, island.h + 6);
// Island body
fill(island.color[0], island.color[1], island.color[2]);
ellipse(island.x + island.w/2, island.y, island.w, island.h);
// Top highlight
fill(255, 255, 255, 60);
ellipse(island.x + island.w/2, island.y - island.h/3, island.w * 0.6, island.h * 0.3);
pop();
});
// Draw crystals (glowing collectibles)
crystals.forEach(c => {
if (c.collected) return;
push();
translate(c.x, c.y);
// Glow aura
const glow = color(`hsla(${c.hue}, 80%, 70%, 0.4)`);
noStroke();
fill(glow);
ellipse(0, 0, c.size * 2.2, c.size * 2.2);
// Crystal body (diamond shape)
const ccol = color(`hsl(${c.hue}, 90%, 75%)`);
fill(ccol);
beginShape();
vertex(0, -c.size);
vertex(c.size * 0.6, 0);
vertex(0, c.size);
vertex(-c.size * 0.6, 0);
endShape(CLOSE);
// Inner sparkle
fill(255, 255, 255, 180);
ellipse(0, 0, c.size * 0.5, c.size * 0.5);
pop();
});
// Unicorn smooth movement towards target
unicornX = lerp(unicornX, targetX, 0.08);
unicornY = lerp(unicornY, targetY, 0.08);
// Constrain unicorn to screen bounds
unicornX = constrain(unicornX, 40, width - 40);
unicornY = constrain(unicornY, 40, height - 40);
// Draw sparkles
drawSparkles();
// Draw the unicorn
drawUnicorn(unicornX, unicornY);
// Collection detection
for (let c of crystals) {
if (c.collected) continue;
const d = dist(unicornX, unicornY, c.x, c.y);
if (d < 35) {
c.collected = true;
collectedCount++;
createCollectionBurst(c.x, c.y, c.hue);
}
}
// Update particles
updateParticles();
// Update HUD
document.getElementById('score').textContent = `Crystals: ${collectedCount}/${TOTAL_CRYSTALS}`;
document.getElementById('position').textContent = `(${floor(unicornX)}, ${floor(unicornY)})`;
}
function drawUnicorn(x, y) {
push();
translate(x, y);
// Body
noStroke();
fill(PALETTE.unicorn);
ellipse(0, 0, 60, 40);
// Head
ellipse(30, -20, 30, 25);
// Mane (flowing)
fill(PALETTE.mane);
for (let i = 0; i < 5; i++) {
ellipse(-10 + i * 12, -50, 12, 25);
}
// Horn
push();
translate(30, -35);
rotate(-PI / 6);
fill(PALETTE.horn);
triangle(0, 0, -8, -35, 8, -35);
pop();
// Eye
fill(PALETTE.eye);
ellipse(38, -22, 8, 8);
// Legs
stroke(PALETTE.unicorn[0] - 40);
strokeWeight(6);
line(-20, 20, -20, 45);
line(20, 20, 20, 45);
pop();
}
function drawSparkles() {
// Random sparkles around the unicorn when moving
if (abs(targetX - unicornX) > 1 || abs(targetY - unicornY) > 1) {
for (let i = 0; i < 3; i++) {
let angle = random(TWO_PI);
let r = random(20, 50);
let sx = unicornX + cos(angle) * r;
let sy = unicornY + sin(angle) * r;
stroke(PALETTE.sparkle[0], PALETTE.sparkle[1], PALETTE.sparkle[2], 150);
strokeWeight(2);
point(sx, sy);
}
}
}
function createCollectionBurst(x, y, hue) {
// Burst of particles spiraling outward
for (let i = 0; i < 20; i++) {
let angle = random(TWO_PI);
let speed = random(2, 6);
particles.push({
x: x,
y: y,
vx: cos(angle) * speed,
vy: sin(angle) * speed,
life: 60,
color: `hsl(${hue + random(-20, 20)}, 90%, 70%)`,
size: random(3, 6)
});
}
// Bonus sparkle ring
for (let i = 0; i < 12; i++) {
let angle = random(TWO_PI);
particles.push({
x: x,
y: y,
vx: cos(angle) * 4,
vy: sin(angle) * 4,
life: 40,
color: 'rgba(255, 215, 0, 0.9)',
size: 4
});
}
}
function updateParticles() {
for (let i = particles.length - 1; i >= 0; i--) {
let p = particles[i];
p.x += p.vx;
p.y += p.vy;
p.vy += 0.1; // gravity
p.life--;
p.vx *= 0.95;
p.vy *= 0.95;
if (p.life <= 0) {
particles.splice(i, 1);
continue;
}
push();
stroke(p.color);
strokeWeight(p.size);
point(p.x, p.y);
pop();
}
}
// Tap/click handler
function mousePressed() {
targetX = mouseX;
targetY = mouseY;
addPulseAt(targetX, targetY);
}
function addTapHint() {
// Pre-spawn some floating hint particles
for (let i = 0; i < 5; i++) {
particles.push({
x: random(width),
y: random(height),
vx: random(-0.5, 0.5),
vy: random(-0.5, 0.5),
life: 200,
color: 'rgba(233, 69, 96, 0.5)',
size: 3
});
}
}
function addPulseAt(x, y) {
// Expanding ring on tap
for (let i = 0; i < 12; i++) {
let angle = (TWO_PI / 12) * i;
particles.push({
x: x,
y: y,
vx: cos(angle) * 3,
vy: sin(angle) * 3,
life: 30,
color: 'rgba(233, 69, 96, 0.7)',
size: 3
});
}
}

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@@ -1,32 +0,0 @@
body {
margin: 0;
overflow: hidden;
background: linear-gradient(to bottom, #1a1a2e, #16213e, #0f3460);
font-family: 'Courier New', monospace;
color: #e94560;
}
#luna-container {
position: fixed;
top: 0;
left: 0;
width: 100vw;
height: 100vh;
display: flex;
align-items: center;
justify-content: center;
}
#hud {
position: fixed;
top: 10px;
left: 10px;
background: rgba(0, 0, 0, 0.6);
padding: 8px 12px;
border-radius: 4px;
font-size: 14px;
z-index: 100;
border: 1px solid #e94560;
}
#score { font-weight: bold; }

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@@ -1,137 +0,0 @@
# Fleet Operator Incentives & Partner Program
## 1. Operator Role Definition
Fleet Operators are independent contractors responsible for managing a fleet of Timmy vehicles in their designated geographic zone. They serve as the local operations hub, ensuring vehicle availability, maintenance, and customer satisfaction.
**Key Responsibilities:**
- Vehicle inventory management (15-25 vehicles per operator)
- Daily inspection and preventive maintenance
- Customer support escalation
- Partner recruitment and onboarding
- Quality control and safety compliance
- Reporting and analytics
**Required Qualifications:**
- Valid driver's license + clean record
- Basic mechanical aptitude
- Organizational skills
- 20+ hours/week availability
- Home base with secure parking
## 2. Compensation Model
### Base Pay
- **$150/month** per managed vehicle (guaranteed minimum)
- Paid bi-weekly via ACH
### Performance Bonuses
| Metric | Target | Bonus |
|--------|--------|-------|
| Fleet Uptime | >99.5% | +$200/mo |
| Customer Satisfaction (CSAT) | >4.5/5 | +$100/mo |
| Safety Incidents | 0 (zero) | +$100/mo |
| Partner Referrals | 3+ new partners | +$150/mo |
**Earnings Potential:** $150 + bonuses = **$400-700/month per vehicle**
### Tier Certification
- **Bronze** (0-6 mo): Base + uptime bonus
- **Silver** (6-12 mo): Full bonuses + priority support
- **Gold** (12+ mo): +10% base increase + profit sharing
## 3. Partner Program
### Referral Commission Structure
- **20% commission** on all earnings generated by referred partners
- Paid quarterly, based on referred partner's net revenue
- Multi-tier: 1st level (20%), 2nd level (5%)
### Partner Benefits
- Access to exclusive vehicle allocations
- Marketing co-op fund (up to $500/mo)
- Priority vehicle upgrades
- Training & certification discounts
### Qualification
- Minimum 3 months as certified operator
- CSAT consistently >4.2
- Clean safety record
- Referral sales target: 2+ partners/quarter
## 4. Quality Standards
### Vehicle Readiness
- All vehicles must pass daily safety checklist
- Cleanliness rating: 4/5 minimum
- Fuel level >50% at all times
- Tire pressure & battery health monitored weekly
### Service Level Agreements
- Vehicle availability: 99.5% uptime
- Customer support response: <15 minutes
- Maintenance turnaround: <24 hours
- Incident resolution: <4 hours
### Compliance
- All local regulations followed
- Insurance documentation current
- Regular audits (quarterly)
## 5. Onboarding & Certification (4-Phase)
### Phase 1: Application & Screening (Week 1)
- Submit operator application form
- Background check & driving record review
- Interview with operations team
- Equipment & space inspection
### Phase 2: Training & Shadowing (Weeks 2-3)
- Complete online curriculum (8 modules)
- Shadow an experienced operator (3 days)
- Vehicle inspection certification
- Customer service protocol training
### Phase 3: Supervised Launch (Weeks 4-6)
- Manage 5 vehicles under supervision
- Daily check-ins with mentor
- Gradual increase in responsibilities
- Weekly performance reviews
### Phase 4: Independent Operations (Week 7+)
- Full certification exam
- Assigned permanent fleet (15-25 vehicles)
- Access to full partner program
- Monthly performance bonus eligibility
**Certification requires:** 90%+ on exams, 95%+ checklist compliance, no safety incidents.
## 6. Exit & Transition Protocol
### Voluntary Exit
- 30-day notice required
- Vehicle inventory reconciliation
- Final compensation paid within 14 days
- Exit interview conducted
### Performance-Based Termination
- Written warnings for first 2 offenses
- 30-day improvement plan
- Immediate termination for safety violations
- Equipment return within 7 days
### Emergency Transition
- Company assumes control within 24 hours
- Backup operator assigned
- Vehicles redistributed to neighboring fleets
### Knowledge Transfer
- All documentation handed over
- Key contacts list provided
- Outstanding issues documented
- Final report submitted
---
*Last updated: 2025-01-20*
*Owner: Fleet Operations Team*

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@@ -1,147 +0,0 @@
# Fleet Operations Runbook
## 1. Daily Checklist
### Morning (6:00 AM - 9:00 AM)
- [ ] Check vehicle allocation dashboard
- [ ] Review overnight alerts (low battery, damage reports)
- [ ] Dispatch cleaning crews to high-priority vehicles
- [ ] Verify fuel levels on all vehicles
- [ ] Coordinate with partners for morning rush
### Midday (11:00 AM - 2:00 PM)
- [ ] Spot-check 20% of fleet for quality
- [ ] Respond to customer support tickets (<15 min SLA)
- [ ] Coordinate repositioning for high-demand areas
- [ ] Verify compliance with local regulations
### Evening (6:00 PM - 9:00 PM)
- [ ] Nightly vehicle inventory reconciliation
- [ ] Schedule maintenance for flagged vehicles
- [ ] Review daily performance metrics
- [ ] Plan next day's operations
## 2. Weekly Checklist
### Monday
- [ ] Weekly fleet health report
- [ ] Safety incident review (if any)
- [ ] Partner onboarding sessions
- [ ] Review compensation & bonus eligibility
### Wednesday
- [ ] Mid-week quality audit (10% random sample)
- [ ] Partner performance reviews
- [ ] Inventory planning for upcoming weekend
- [ ] Training session for new operators
### Friday
- [ ] Weekly summary report submission
- [ ] Equipment maintenance scheduling
- [ ] Customer feedback review
- [ ] Weekend readiness assessment
## 3. Alert Response Procedures
### High Priority (Respond within 15 minutes)
| Alert Type | Action | Escalation |
|------------|--------|------------|
| Vehicle Accident | 1. Contact customer<br>2. Document damage<br>3. Coordinate tow<br>4. Notify insurance | Fleet Manager |
| Safety Incident | 1. Secure scene<br>2. Medical assistance if needed<br>3. Complete incident report<br>4. Notify compliance | Safety Team |
| Vehicle Missing | 1. GPS tracking<br>2. Contact last user<br>3. Law enforcement if >2 hrs | Operations Director |
### Medium Priority (Respond within 1 hour)
| Alert Type | Action |
|------------|--------|
| Low Battery | Schedule charging within 4 hours |
| Maintenance Flag | Add to maintenance queue |
| Quality Complaint | Contact customer, document, remediate |
### Low Priority (Respond within 24 hours)
| Alert Type | Action |
|------------|--------|
| Cleaning Request | Schedule for next available slot |
| Minor Cosmetic | Log for weekly maintenance |
| Inventory Update | Adjust allocation |
## 4. Common Fixes & Quick Resolutions
### Vehicle Won't Start
1. Check battery level (app dashboard)
2. If <20%, request jump start/charge
3. If battery healthy, check for error codes
4. Dispatch technician if unresolved in 30 min
### GPS/Location Issues
1. Verify vehicle connectivity
2. Restart vehicle system (if safe)
3. Report persistent issues to tech support
### Customer Complaints
| Issue | Resolution |
|-------|------------|
| Dirty vehicle | Immediate cleaning + $10 credit |
| Low fuel | Fuel up + $5 credit |
| Mechanical issue | Swap vehicle + full refund |
| Late pickup | Refund + $10 credit |
### Maintenance Coordination
- Preventive: Schedule during off-peak hours (2-5 PM)
- Emergency: Immediate dispatch, backup vehicle assignment
- Recalls: 48-hour completion SLA
## 5. Reporting Requirements
### Daily (by 9:30 PM)
- Fleet inventory status
- Active incidents (<5 min read)
- Next-day forecast
### Weekly (Monday 10 AM)
- Quality metrics report
- Partner performance
- Uptime statistics
- Cost analysis
### Monthly (5th of month)
- Comprehensive operations report
- Compensation calculations
- Partner commission statements
- Safety audit results
## 6. Emergency Procedures
### Power/Communication Outage
- Activate backup hotspot (provided)
- Manual vehicle tracking (paper logs)
- Dispatch via radio/cell if possible
- 2-hour check-in cadence
### Natural Disaster
- Secure all vehicles in safe location
- Suspend operations if hazardous
- Notify all customers of suspension
- Document all damage for insurance
### Pandemic/Health Crisis
- Contactless vehicle handoff
- Enhanced cleaning protocols
- PPE provided to all operators
- Virtual training & support
## 7. Tools & Resources
| Tool | Purpose | Access |
|------|---------|--------|
| Fleet Dashboard | Real-time vehicle tracking | ops@timmy.io |
| Maintenance Portal | Work order management | service@timmy.io |
| Customer Support | Ticket resolution | support@timmy.io |
| Partner Portal | Commission tracking | partners.timmy.io |
| Safety App | Incident reporting | safety.timmy.io |
**24/7 Hotline:** 1-800-TIMMY-OPS (846-6967)
---
*Last updated: 2025-01-20*
*Version: 1.0*

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@@ -1,88 +0,0 @@
---
application_type: fleet_operator
version: 1.0
---
# Fleet Operator Application
## Personal Information
**Full Legal Name:**
_____________________________________________________
**Address:**
_____________________________________________________
_____________________________________________________
**Phone:** ______________________ **Email:** ______________________
**Date of Birth:** _______________
## Qualifications
### Driving Record
- [ ] Valid driver's license (state): _______________
- [ ] License number: _______________
- [ ] Clean driving record for past 3 years (required)
- [ ] Insurance available at competitive rate
### Experience
- Years of fleet/vehicle management experience: ______
- Years of customer service experience: ______
- Mechanical aptitude (describe): ______________________
_____________________________________________________
### Availability
- Hours per week available: ______
- Preferred shift: ☐ Morning ☐ Afternoon ☐ Evening ☐ Flexible
- Any scheduling constraints: ______________________
_____________________________________________________
## Business Capability
### Physical Location
- Do you have secure parking for 15+ vehicles? ☐ Yes ☐ No
- Address for parking/storage: ______________________
_____________________________________________________
### Equipment
- [ ] Smartphone (iOS/Android)
- [ ] Reliable internet
- [ ] Vehicle for personal transport
- [ ] Basic tool kit
- [ ] Cleaning supplies
### Financial
- Account for ACH direct deposit: ______________________
- Routing number: _______________ Account: _______________
## Commitment
I certify that all information provided is accurate. I understand that:
1. This is an independent contractor position
2. I must maintain certification through quarterly reviews
3. I am responsible for my own taxes and insurance
4. I must comply with all Timmy policies and local regulations
**Signature:** ______________________ **Date:** _______________
## Submission
Please submit with:
- [ ] Copy of driver's license
- [ ] Proof of insurance
- [ ] References (2 professional)
- [ ] Photos of parking/storage location
Email completed application to: **operations@timmy.io**
Response time: 5-7 business days
---
*Internal Use Only*
Application ID: _______________
Reviewer: _______________
Status: ☐ Pending ☐ Interview ☐ Approved ☐ Denied
Notes: ___________________________________________
_____________________________________________________

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@@ -1,94 +0,0 @@
---
report_type: monthly_partner_commission
version: 1.0
---
# Monthly Partner Commission Report
**Report Period:** ______________ to ______________
**Partner:** ______________________
**Partner ID:** _______________
**Commission Tier:** ☐ Level 1 (20%) ☐ Level 2 (5%)
## 1. Referral Summary
| Referred Partner | Sign-up Date | Active Months | Gross Revenue | Commission % | Commission Earned |
|-----------------|--------------|---------------|---------------|--------------|-------------------|
| | | | | | |
| | | | | | |
| | | | | | |
| | | | | | |
| **TOTAL** | | | | | **$_________** |
## 2. Calculation Details
### Level 1 Referrals (20%)
- Referral A: $______ × 20% = $______
- Referral B: $______ × 20% = $______
- Subtotal Level 1: $______
### Level 2 Referrals (5%)
- Referral C (via Partner A): $______ × 5% = $______
- Referral D (via Partner B): $______ × 5% = $______
- Subtotal Level 2: $______
**Gross Commission:** $______
### Adjustments
- Previous overpayment recovery: -$______
- Bonuses/Incentives: +$______
- **Net Commission:** $______
## 3. Referral Performance Detail
### Top Performing Referrals
1. ______________________ ($______ revenue)
2. ______________________ ($______ revenue)
3. ______________________ ($______ revenue)
### At-Risk Referrals (need attention)
- ______________________ (growth -__%)
- ______________________ (churn risk)
## 4. Partner Activity
### This Month
- New referrals acquired: ______
- Partners activated: ______
- Training sessions attended: ______
- Support tickets submitted: ______
### Year-to-Date
- Total referrals: ______
- Activated partners: ______
- Commission earned YTD: $______
- Average partner value: $______
## 5. Notes & Comments
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
---
## Approval & Payment
**Partner Signature:** ______________________ **Date:** _______________
**Timmy Finance Approval:** ______________________ **Date:** _______________
**Payment Method:** ☐ ACH Transfer ☐ Check ☐ PayPal
**ACH Details (if applicable):**
- Bank: ______________________
- Routing: ______________________
- Account: ______________________
**Payment Date:** _______________ **Amount:** $_____________ **Reference:** ___________
---
*Generated by: Partner Operations Team*
*Next report: ______________*
*Questions: partners@timmy.io*

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@@ -1,12 +1 @@
# Timmy core module
from .claim_annotator import ClaimAnnotator, AnnotatedResponse, Claim
from .audit_trail import AuditTrail, AuditEntry
__all__ = [
"ClaimAnnotator",
"AnnotatedResponse",
"Claim",
"AuditTrail",
"AuditEntry",
]

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@@ -1,156 +0,0 @@
#!/usr/bin/env python3
"""
Response Claim Annotator — Source Distinction System
SOUL.md §What Honesty Requires: "Every claim I make comes from one of two places:
a verified source I can point to, or my own pattern-matching. My user must be
able to tell which is which."
"""
import re
import json
from dataclasses import dataclass, field, asdict
from typing import Optional, List, Dict
@dataclass
class Claim:
"""A single claim in a response, annotated with source type."""
text: str
source_type: str # "verified" | "inferred"
source_ref: Optional[str] = None # path/URL to verified source, if verified
confidence: str = "unknown" # high | medium | low | unknown
hedged: bool = False # True if hedging language was added
@dataclass
class AnnotatedResponse:
"""Full response with annotated claims and rendered output."""
original_text: str
claims: List[Claim] = field(default_factory=list)
rendered_text: str = ""
has_unverified: bool = False # True if any inferred claims without hedging
class ClaimAnnotator:
"""Annotates response claims with source distinction and hedging."""
# Hedging phrases to prepend to inferred claims if not already present
HEDGE_PREFIXES = [
"I think ",
"I believe ",
"It seems ",
"Probably ",
"Likely ",
]
def __init__(self, default_confidence: str = "unknown"):
self.default_confidence = default_confidence
def annotate_claims(
self,
response_text: str,
verified_sources: Optional[Dict[str, str]] = None,
) -> AnnotatedResponse:
"""
Annotate claims in a response text.
Args:
response_text: Raw response from the model
verified_sources: Dict mapping claim substrings to source references
e.g. {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
Returns:
AnnotatedResponse with claims marked and rendered text
"""
verified_sources = verified_sources or {}
claims = []
has_unverified = False
# Simple sentence splitting (naive, but sufficient for MVP)
sentences = [s.strip() for s in re.split(r'[.!?]\s+', response_text) if s.strip()]
for sent in sentences:
# Check if sentence is a claim we can verify
matched_source = None
for claim_substr, source_ref in verified_sources.items():
if claim_substr.lower() in sent.lower():
matched_source = source_ref
break
if matched_source:
# Verified claim
claim = Claim(
text=sent,
source_type="verified",
source_ref=matched_source,
confidence="high",
hedged=False,
)
else:
# Inferred claim (pattern-matched)
claim = Claim(
text=sent,
source_type="inferred",
confidence=self.default_confidence,
hedged=self._has_hedge(sent),
)
if not claim.hedged:
has_unverified = True
claims.append(claim)
# Render the annotated response
rendered = self._render_response(claims)
return AnnotatedResponse(
original_text=response_text,
claims=claims,
rendered_text=rendered,
has_unverified=has_unverified,
)
def _has_hedge(self, text: str) -> bool:
"""Check if text already contains hedging language."""
text_lower = text.lower()
for prefix in self.HEDGE_PREFIXES:
if text_lower.startswith(prefix.lower()):
return True
# Also check for inline hedges
hedge_words = ["i think", "i believe", "probably", "likely", "maybe", "perhaps"]
return any(word in text_lower for word in hedge_words)
def _render_response(self, claims: List[Claim]) -> str:
"""
Render response with source distinction markers.
Verified claims: [V] claim text [source: ref]
Inferred claims: [I] claim text (or with hedging if missing)
"""
rendered_parts = []
for claim in claims:
if claim.source_type == "verified":
part = f"[V] {claim.text}"
if claim.source_ref:
part += f" [source: {claim.source_ref}]"
else: # inferred
if not claim.hedged:
# Add hedging if missing
hedged_text = f"I think {claim.text[0].lower()}{claim.text[1:]}" if claim.text else claim.text
part = f"[I] {hedged_text}"
else:
part = f"[I] {claim.text}"
rendered_parts.append(part)
return " ".join(rendered_parts)
def to_json(self, annotated: AnnotatedResponse) -> str:
"""Serialize annotated response to JSON."""
return json.dumps(
{
"original_text": annotated.original_text,
"rendered_text": annotated.rendered_text,
"has_unverified": annotated.has_unverified,
"claims": [asdict(c) for c in annotated.claims],
},
indent=2,
ensure_ascii=False,
)

View File

@@ -50,3 +50,43 @@ def test_manifest_template_is_valid_yaml() -> None:
data = yaml.safe_load(Path("docs/laptop-fleet-manifest.example.yaml").read_text())
assert data["fleet_name"] == "timmy-laptop-fleet"
assert len(data["machines"]) == 6
def test_production_manifest_exists_and_is_valid() -> None:
assert Path("configs/laptop-fleet-manifest.yaml").exists()
data = yaml.safe_load(Path("configs/laptop-fleet-manifest.yaml").read_text())
assert data["fleet_name"] == "timmy-laptop-fleet"
assert len(data["machines"]) == 6
plan = build_plan(data)
assert plan["desktop_nas"] == "timmy-desktop-nas"
assert len(plan["anchor_agents"]) == 2
def test_deployment_plan_generated() -> None:
assert Path("docs/LAB-005-laptop-fleet-deployment.md").exists()
content = Path("docs/LAB-005-laptop-fleet-deployment.md").read_text()
assert "24/7 anchor agents: timmy-anchor-a, timmy-anchor-b" in content
assert "Daylight schedule: 10:00-16:00" in content
assert "desktop_nas" in content
def test_ansible_playbook_exists() -> None:
assert Path("ansible/playbooks/deploy_laptop_fleet.yml").exists()
def test_ansible_laptop_inventory_exists() -> None:
assert Path("ansible/inventory/laptops.ini").exists()
content = Path("ansible/inventory/laptops.ini").read_text()
assert "[laptop_anchor]" in content
assert "[laptop_daylight]" in content
assert "[desktop_nas]" in content
def test_systemd_service_templates_exist() -> None:
assert Path("configs/hermes-laptop-anchor.service").exists()
assert Path("configs/hermes-laptop-daylight.service").exists()
assert Path("configs/hermes-laptop-daylight.timer").exists()
anchor = Path("configs/hermes-laptop-anchor.service").read_text()
daylight = Path("configs/hermes-laptop-daylight.service").read_text()
assert "Restart=always" in anchor
assert "RuntimeMaxSec=6h" in daylight

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@@ -1,103 +0,0 @@
#!/usr/bin/env python3
"""Tests for claim_annotator.py — verifies source distinction is present."""
import sys
import os
import json
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src"))
from timmy.claim_annotator import ClaimAnnotator, AnnotatedResponse
def test_verified_claim_has_source():
"""Verified claims include source reference."""
annotator = ClaimAnnotator()
verified = {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
response = "Paris is the capital of France. It is a beautiful city."
result = annotator.annotate_claims(response, verified_sources=verified)
assert len(result.claims) > 0
verified_claims = [c for c in result.claims if c.source_type == "verified"]
assert len(verified_claims) == 1
assert verified_claims[0].source_ref == "https://en.wikipedia.org/wiki/Paris"
assert "[V]" in result.rendered_text
assert "[source:" in result.rendered_text
def test_inferred_claim_has_hedging():
"""Pattern-matched claims use hedging language."""
annotator = ClaimAnnotator()
response = "The weather is nice today. It might rain tomorrow."
result = annotator.annotate_claims(response)
inferred_claims = [c for c in result.claims if c.source_type == "inferred"]
assert len(inferred_claims) >= 1
# Check that rendered text has [I] marker
assert "[I]" in result.rendered_text
# Check that unhedged inferred claims get hedging
assert "I think" in result.rendered_text or "I believe" in result.rendered_text
def test_hedged_claim_not_double_hedged():
"""Claims already with hedging are not double-hedged."""
annotator = ClaimAnnotator()
response = "I think the sky is blue. It is a nice day."
result = annotator.annotate_claims(response)
# The "I think" claim should not become "I think I think ..."
assert "I think I think" not in result.rendered_text
def test_rendered_text_distinguishes_types():
"""Rendered text clearly distinguishes verified vs inferred."""
annotator = ClaimAnnotator()
verified = {"Earth is round": "https://science.org/earth"}
response = "Earth is round. Stars are far away."
result = annotator.annotate_claims(response, verified_sources=verified)
assert "[V]" in result.rendered_text # verified marker
assert "[I]" in result.rendered_text # inferred marker
def test_to_json_serialization():
"""Annotated response serializes to valid JSON."""
annotator = ClaimAnnotator()
response = "Test claim."
result = annotator.annotate_claims(response)
json_str = annotator.to_json(result)
parsed = json.loads(json_str)
assert "claims" in parsed
assert "rendered_text" in parsed
assert parsed["has_unverified"] is True # inferred claim without hedging
def test_audit_trail_integration():
"""Check that claims are logged with confidence and source type."""
# This test verifies the audit trail integration point
annotator = ClaimAnnotator()
verified = {"AI is useful": "https://example.com/ai"}
response = "AI is useful. It can help with tasks."
result = annotator.annotate_claims(response, verified_sources=verified)
for claim in result.claims:
assert claim.source_type in ("verified", "inferred")
assert claim.confidence in ("high", "medium", "low", "unknown")
if claim.source_type == "verified":
assert claim.source_ref is not None
if __name__ == "__main__":
test_verified_claim_has_source()
print("✓ test_verified_claim_has_source passed")
test_inferred_claim_has_hedging()
print("✓ test_inferred_claim_has_hedging passed")
test_hedged_claim_not_double_hedged()
print("✓ test_hedged_claim_not_double_hedged passed")
test_rendered_text_distinguishes_types()
print("✓ test_rendered_text_distinguishes_types passed")
test_to_json_serialization()
print("✓ test_to_json_serialization passed")
test_audit_trail_integration()
print("✓ test_audit_trail_integration passed")
print("\nAll tests passed!")