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sprint/iss
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20
SOUL.md
20
SOUL.md
@@ -137,6 +137,26 @@ The inscription predates any given model. It will outlast every API.
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---
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## What Honesty Requires
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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.
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The following are not optional. Any implementation that calls itself Timmy must build them.
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**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.
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**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.
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**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.
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**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.
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**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.
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**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.
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---
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## For the Audio Overview
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If you are listening to this as a NotebookLM Audio Overview:
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48
luna/README.md
Normal file
48
luna/README.md
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@@ -0,0 +1,48 @@
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# LUNA-1: Pink Unicorn Game — Project Scaffolding
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Starter project for Mackenzie's Pink Unicorn Game built with **p5.js 1.9.0**.
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## Quick Start
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```bash
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cd luna
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python3 -m http.server 8080
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# Visit http://localhost:8080
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```
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Or simply open `luna/index.html` directly in a browser.
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## Controls
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| Input | Action |
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|-------|--------|
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| Tap / Click | Move unicorn toward tap point |
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| `r` key | Reset unicorn to center |
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## Features
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- Mobile-first touch handling (`touchStarted`)
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- Easing movement via `lerp`
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- Particle burst feedback on tap
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- Pink/unicorn color palette
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- Responsive canvas (adapts to window resize)
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## Project Structure
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```
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luna/
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├── index.html # p5.js CDN import + canvas container
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├── sketch.js # Main game logic and rendering
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├── style.css # Pink/unicorn theme, responsive layout
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└── README.md # This file
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```
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## Verification
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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.
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## Technical Notes
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- p5.js loaded from CDN (no build step)
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- `colorMode(RGB, 255)`; palette defined in code
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- Particles are simple fading circles; removed when `life <= 0`
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18
luna/index.html
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18
luna/index.html
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@@ -0,0 +1,18 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>LUNA-3: Simple World — Floating Islands</title>
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<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.9.0/p5.min.js"></script>
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<link rel="stylesheet" href="style.css" />
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</head>
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<body>
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<div id="luna-container"></div>
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<div id="hud">
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<span id="score">Crystals: 0/0</span>
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<span id="position"></span>
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</div>
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<script src="sketch.js"></script>
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</body>
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</html>
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289
luna/sketch.js
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289
luna/sketch.js
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@@ -0,0 +1,289 @@
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/**
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* LUNA-3: Simple World — Floating Islands & Collectible Crystals
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* Builds on LUNA-1 scaffold (unicorn tap-follow) + LUNA-2 actions
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*
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* NEW: Floating platforms + collectible crystals with particle bursts
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*/
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let particles = [];
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let unicornX, unicornY;
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let targetX, targetY;
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// Platforms: floating islands at various heights with horizontal ranges
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const islands = [
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{ x: 100, y: 350, w: 150, h: 20, color: [100, 200, 150] }, // left island
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{ x: 350, y: 280, w: 120, h: 20, color: [120, 180, 200] }, // middle-high island
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{ x: 550, y: 320, w: 140, h: 20, color: [200, 180, 100] }, // right island
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{ x: 200, y: 180, w: 180, h: 20, color: [180, 140, 200] }, // top-left island
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{ x: 500, y: 120, w: 100, h: 20, color: [140, 220, 180] }, // top-right island
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];
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// Collectible crystals on islands
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const crystals = [];
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islands.forEach((island, i) => {
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// 2–3 crystals per island, placed near center
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const count = 2 + floor(random(2));
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for (let j = 0; j < count; j++) {
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crystals.push({
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x: island.x + 30 + random(island.w - 60),
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y: island.y - 30 - random(20),
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size: 8 + random(6),
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hue: random(280, 340), // pink/purple range
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collected: false,
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islandIndex: i
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});
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}
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});
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let collectedCount = 0;
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const TOTAL_CRYSTALS = crystals.length;
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// Pink/unicorn palette
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const PALETTE = {
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background: [255, 210, 230], // light pink (overridden by gradient in draw)
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unicorn: [255, 182, 193], // pale pink/white
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horn: [255, 215, 0], // gold
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mane: [255, 105, 180], // hot pink
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eye: [255, 20, 147], // deep pink
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sparkle: [255, 105, 180],
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island: [100, 200, 150],
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};
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function setup() {
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const container = document.getElementById('luna-container');
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const canvas = createCanvas(600, 500);
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canvas.parent('luna-container');
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unicornX = width / 2;
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unicornY = height - 60; // start on ground (bottom platform equivalent)
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targetX = unicornX;
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targetY = unicornY;
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noStroke();
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addTapHint();
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}
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function draw() {
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// Gradient sky background
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for (let y = 0; y < height; y++) {
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const t = y / height;
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const r = lerp(26, 15, t); // #1a1a2e → #0f3460
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const g = lerp(26, 52, t);
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const b = lerp(46, 96, t);
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stroke(r, g, b);
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line(0, y, width, y);
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}
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// Draw islands (floating platforms with subtle shadow)
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islands.forEach(island => {
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push();
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// Shadow
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fill(0, 0, 0, 40);
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ellipse(island.x + island.w/2 + 5, island.y + 5, island.w + 10, island.h + 6);
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// Island body
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fill(island.color[0], island.color[1], island.color[2]);
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ellipse(island.x + island.w/2, island.y, island.w, island.h);
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// Top highlight
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fill(255, 255, 255, 60);
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ellipse(island.x + island.w/2, island.y - island.h/3, island.w * 0.6, island.h * 0.3);
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pop();
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});
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// Draw crystals (glowing collectibles)
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crystals.forEach(c => {
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if (c.collected) return;
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push();
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translate(c.x, c.y);
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// Glow aura
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const glow = color(`hsla(${c.hue}, 80%, 70%, 0.4)`);
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noStroke();
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fill(glow);
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ellipse(0, 0, c.size * 2.2, c.size * 2.2);
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// Crystal body (diamond shape)
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const ccol = color(`hsl(${c.hue}, 90%, 75%)`);
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fill(ccol);
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beginShape();
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vertex(0, -c.size);
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vertex(c.size * 0.6, 0);
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vertex(0, c.size);
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vertex(-c.size * 0.6, 0);
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endShape(CLOSE);
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// Inner sparkle
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fill(255, 255, 255, 180);
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ellipse(0, 0, c.size * 0.5, c.size * 0.5);
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pop();
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});
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// Unicorn smooth movement towards target
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unicornX = lerp(unicornX, targetX, 0.08);
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unicornY = lerp(unicornY, targetY, 0.08);
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// Constrain unicorn to screen bounds
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unicornX = constrain(unicornX, 40, width - 40);
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unicornY = constrain(unicornY, 40, height - 40);
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// Draw sparkles
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drawSparkles();
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// Draw the unicorn
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drawUnicorn(unicornX, unicornY);
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// Collection detection
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for (let c of crystals) {
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if (c.collected) continue;
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const d = dist(unicornX, unicornY, c.x, c.y);
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if (d < 35) {
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c.collected = true;
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collectedCount++;
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createCollectionBurst(c.x, c.y, c.hue);
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}
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}
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// Update particles
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updateParticles();
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// Update HUD
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document.getElementById('score').textContent = `Crystals: ${collectedCount}/${TOTAL_CRYSTALS}`;
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document.getElementById('position').textContent = `(${floor(unicornX)}, ${floor(unicornY)})`;
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}
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function drawUnicorn(x, y) {
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push();
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translate(x, y);
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// Body
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noStroke();
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fill(PALETTE.unicorn);
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ellipse(0, 0, 60, 40);
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// Head
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ellipse(30, -20, 30, 25);
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// Mane (flowing)
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fill(PALETTE.mane);
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for (let i = 0; i < 5; i++) {
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ellipse(-10 + i * 12, -50, 12, 25);
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}
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// Horn
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push();
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translate(30, -35);
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rotate(-PI / 6);
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fill(PALETTE.horn);
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triangle(0, 0, -8, -35, 8, -35);
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pop();
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// Eye
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fill(PALETTE.eye);
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ellipse(38, -22, 8, 8);
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// Legs
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stroke(PALETTE.unicorn[0] - 40);
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strokeWeight(6);
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line(-20, 20, -20, 45);
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line(20, 20, 20, 45);
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pop();
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}
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function drawSparkles() {
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// Random sparkles around the unicorn when moving
|
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if (abs(targetX - unicornX) > 1 || abs(targetY - unicornY) > 1) {
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for (let i = 0; i < 3; i++) {
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let angle = random(TWO_PI);
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let r = random(20, 50);
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let sx = unicornX + cos(angle) * r;
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let sy = unicornY + sin(angle) * r;
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stroke(PALETTE.sparkle[0], PALETTE.sparkle[1], PALETTE.sparkle[2], 150);
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strokeWeight(2);
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point(sx, sy);
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}
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}
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}
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function createCollectionBurst(x, y, hue) {
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// Burst of particles spiraling outward
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for (let i = 0; i < 20; i++) {
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let angle = random(TWO_PI);
|
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let speed = random(2, 6);
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particles.push({
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x: x,
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y: y,
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vx: cos(angle) * speed,
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vy: sin(angle) * speed,
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life: 60,
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color: `hsl(${hue + random(-20, 20)}, 90%, 70%)`,
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size: random(3, 6)
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});
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}
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// Bonus sparkle ring
|
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for (let i = 0; i < 12; i++) {
|
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let angle = random(TWO_PI);
|
||||
particles.push({
|
||||
x: x,
|
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y: y,
|
||||
vx: cos(angle) * 4,
|
||||
vy: sin(angle) * 4,
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life: 40,
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color: 'rgba(255, 215, 0, 0.9)',
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size: 4
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||||
});
|
||||
}
|
||||
}
|
||||
|
||||
function updateParticles() {
|
||||
for (let i = particles.length - 1; i >= 0; i--) {
|
||||
let p = particles[i];
|
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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) {
|
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particles.splice(i, 1);
|
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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
|
||||
});
|
||||
}
|
||||
}
|
||||
32
luna/style.css
Normal file
32
luna/style.css
Normal file
@@ -0,0 +1,32 @@
|
||||
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; }
|
||||
80
specs/fleet-operator-incentives.md
Normal file
80
specs/fleet-operator-incentives.md
Normal file
@@ -0,0 +1,80 @@
|
||||
# Fleet Operator Incentives Program
|
||||
|
||||
## Overview
|
||||
|
||||
This document defines the incentive structure for certified fleet operators within the Timmy ecosystem. The goal is to create a sustainable, high-performance operator community that maximizes fleet uptime and reliability.
|
||||
|
||||
## Operator Tiers & Compensation
|
||||
|
||||
### Tier 1: Certified Operator (Entry)
|
||||
- **Requirements:**
|
||||
- Complete operator training program
|
||||
- Pass certification exam (95%+ uptime simulation)
|
||||
- Sign service agreement (min 6 months)
|
||||
- Maintain 99%+ fleet uptime
|
||||
- Respond to incidents within 15 minutes
|
||||
- **Compensation:**
|
||||
- Base stipend: $500/month per fleet unit
|
||||
- Uptime bonus: +$100/month for >99.5% uptime
|
||||
- Incident response bonus: +$50 per resolved incident (max 5/month)
|
||||
- Revenue share: 15% of transaction fees from assigned fleet
|
||||
|
||||
### Tier 2: Senior Operator
|
||||
- **Requirements:**
|
||||
- 6+ months as Certified Operator
|
||||
- Maintain 99.5%+ fleet uptime over 6 months
|
||||
- Train 1+ new operator
|
||||
- Document 5+ incident resolutions in runbook
|
||||
- **Compensation:**
|
||||
- Base stipend: $750/month per fleet unit
|
||||
- Uptime bonus: +$200/month for >99.7% uptime
|
||||
- Incident response bonus: +$75 per resolved incident (max 8/month)
|
||||
- Revenue share: 20% of transaction fees from assigned fleet
|
||||
- Team lead stipend: +$150/month per mentee
|
||||
|
||||
### Tier 3: Master Operator
|
||||
- **Requirements:**
|
||||
- 12+ months as Senior Operator
|
||||
- Maintain 99.7%+ fleet uptime over 12 months
|
||||
- Mentor 3+ operators to certification
|
||||
- Contribute 10+ runbook improvements
|
||||
- Zero critical incident Escalations
|
||||
- **Compensation:**
|
||||
- Base stipend: $1,000/month per fleet unit
|
||||
- Uptime bonus: +$300/month for >99.9% uptime
|
||||
- Incident response bonus: +$100 per resolved incident (max 10/month)
|
||||
- Revenue share: 25% of transaction fees from assigned fleet
|
||||
- Leadership stipend: +$300/month
|
||||
- Profit sharing: 2% of quarterly net operator program profits
|
||||
|
||||
## Performance Metrics
|
||||
|
||||
### Primary KPIs
|
||||
1. **Uptime** - Percentage of time fleet units are operational and responsive
|
||||
2. **Incident Response Time** - Time to acknowledge and begin resolution
|
||||
3. **Resolution Time** - Time to fully resolve incidents
|
||||
4. **Churn Rate** - Annual operator attrition (<10% target)
|
||||
5. **Customer Satisfaction** - Feedback from fleet users
|
||||
|
||||
### Monitoring & Evaluation
|
||||
- Daily uptime reports via automated monitoring
|
||||
- Weekly performance summaries
|
||||
- Monthly compensation calculations
|
||||
- Quarterly tier reviews and promotions
|
||||
- Annual program audit and adjustments
|
||||
|
||||
## Benefits Beyond Compensation
|
||||
|
||||
- Access to exclusive operator community Slack
|
||||
- Priority support from engineering team
|
||||
- Early access to new features and hardware
|
||||
- Training budget: $500/year for certifications
|
||||
- Health stipend: $100/month (Tier 2+)
|
||||
- Equipment upgrade program: subsidized hardware
|
||||
|
||||
## Termination & Appeals
|
||||
|
||||
- Automatic downgrade after 30 days below tier uptime requirement
|
||||
- 60-day performance improvement plan for chronic issues
|
||||
- Appeal process to Operator Review Board (3 senior operators + 1 staff)
|
||||
- Final appeal to Timmy executive team
|
||||
118
specs/fleet-ops-runbook.md
Normal file
118
specs/fleet-ops-runbook.md
Normal file
@@ -0,0 +1,118 @@
|
||||
# Fleet Operations Runbook
|
||||
|
||||
## Quick Reference
|
||||
|
||||
### Emergency Contacts
|
||||
- **PagerDuty:** (for Tier 1+ incidents)
|
||||
- **Slack:** #fleet-operations
|
||||
- **Engineering On-Call:** @on-call-engineer
|
||||
|
||||
### Incident Severity Levels
|
||||
- **P0-Critical:** System down, >50% fleet affected, immediate response required
|
||||
- **P1-High:** Major degradation, 10-50% fleet affected, respond within 30 min
|
||||
- **P2-Medium:** Partial outage, <10% fleet affected, respond within 2 hours
|
||||
- **P3-Low:** Minor issues, isolated, respond within 24 hours
|
||||
|
||||
## Daily Operator Checklist
|
||||
|
||||
### Start of Shift
|
||||
- [ ] Check fleet health dashboard
|
||||
- [ ] Review overnight incidents
|
||||
- [ ] Confirm all active fleet units are online
|
||||
- [ ] Check weather/natural disaster alerts for fleet zones
|
||||
- [ ] Review any scheduled maintenance
|
||||
|
||||
### Ongoing Monitoring
|
||||
- [ ] Monitor fleet uptime metrics (hourly)
|
||||
- [ ] Check communication channels for user reports
|
||||
- [ ] Rotate through fleet units for inspection
|
||||
- [ ] Document any anomalies
|
||||
|
||||
### End of Shift
|
||||
- [ ] Handoff report to next shift operator
|
||||
- [ ] Log all incidents and resolutions
|
||||
- [ ] Update runbook with new learnings
|
||||
- [ ] Verify fleet stability before signing off
|
||||
|
||||
## Incident Response Procedures
|
||||
|
||||
### P0-Critical Response
|
||||
1. **Acknowledge** immediately in #fleet-operations
|
||||
2. **Page** engineering on-call
|
||||
3. **Isolate** affected fleet units if possible
|
||||
4. **Execute** failover or recovery procedures
|
||||
5. **Communicate** status updates every 15 minutes
|
||||
6. **Document** root cause after resolution
|
||||
|
||||
### Common Incidents
|
||||
|
||||
#### Fleet Unit Offline
|
||||
1. Check unit health metrics
|
||||
2. Attempt remote restart
|
||||
3. If fails, dispatch field technician (if within service area)
|
||||
4. Escalate if unit not restored in 2 hours
|
||||
|
||||
#### GPS/Connectivity Loss
|
||||
1. Verify network status in area
|
||||
2. Check unit configuration
|
||||
3. Coordinate with carrier if widespread
|
||||
4. Update affected users
|
||||
|
||||
#### Hardware Malfunction
|
||||
1. Run diagnostic tests
|
||||
2. Review error logs
|
||||
3. Determine if field service needed
|
||||
4. Order replacement parts if required
|
||||
|
||||
## Escalation Matrix
|
||||
|
||||
| Issue Type | Tier 1 Operator | Senior Operator | Master Operator | Engineering |
|
||||
|------------|----------------|----------------|----------------|------------|
|
||||
| Unit offline | Handle | Escalate if >2hrs | Escalate if >4hrs | Immediate |
|
||||
| System outage | Notify | Coordinate | Lead | Own |
|
||||
| Customer complaint | Resolve | Escalate | Escalate | Notify |
|
||||
| New feature issue | Document | Report | Prioritize | Fix |
|
||||
|
||||
## Reporting Requirements
|
||||
|
||||
### Daily
|
||||
- Fleet uptime report (automated)
|
||||
- Incident summary (if any)
|
||||
|
||||
### Weekly
|
||||
- Operator performance metrics
|
||||
- Customer satisfaction scores
|
||||
- Maintenance activities
|
||||
|
||||
### Monthly
|
||||
- Comprehensive operations review
|
||||
- Training needs assessment
|
||||
- Process improvement recommendations
|
||||
|
||||
## Partner Program Coordination
|
||||
|
||||
- Document all partner leads in CRM
|
||||
- Track lead source and conversion
|
||||
- Provide partner with fleet status updates (weekly)
|
||||
- Escalate partner-related issues to Partnership Manager
|
||||
|
||||
## Safety & Compliance
|
||||
|
||||
- Follow all local regulations for fleet operations
|
||||
- Maintain proper insurance documentation
|
||||
- Report accidents/incidents to authorities immediately
|
||||
- Complete safety training annually
|
||||
|
||||
## Documentation Standards
|
||||
|
||||
All runbook entries must include:
|
||||
1. Timestamp (ISO 8601)
|
||||
2. Incident ID
|
||||
3. Actions taken (chronological)
|
||||
4. Resolution outcome
|
||||
5. Lessons learned
|
||||
6. Follow-up tasks
|
||||
|
||||
---
|
||||
|
||||
*This runbook is a living document. Operators are expected to suggest improvements after each incident.*
|
||||
70
specs/templates/operator-application.md
Normal file
70
specs/templates/operator-application.md
Normal file
@@ -0,0 +1,70 @@
|
||||
---
|
||||
# Fleet Operator Application
|
||||
applicant_name: ""
|
||||
email: ""
|
||||
phone: ""
|
||||
location: ""
|
||||
date_applied: ""
|
||||
referral_source: "" # partner, website, referral, etc.
|
||||
partner_code: "" # if referred by partner
|
||||
---
|
||||
|
||||
# Professional Experience
|
||||
|
||||
## Relevant Experience
|
||||
[Describe any previous fleet management, logistics, or operations experience]
|
||||
|
||||
## Technical Skills
|
||||
- [ ] Vehicle maintenance basics
|
||||
- [ ] GPS/navigation systems
|
||||
- [ ] Mobile device troubleshooting
|
||||
- [ ] Basic mechanical aptitude
|
||||
- [ ] Customer service experience
|
||||
|
||||
## Certifications
|
||||
- [ ] Valid driver's license (class:)
|
||||
- [ ] Commercial driver's license (if applicable)
|
||||
- [ ] First aid/CPR certified
|
||||
- [ ] Other:
|
||||
|
||||
# Availability
|
||||
|
||||
## Hours
|
||||
- Weekdays: [ ]
|
||||
- Weekends: [ ]
|
||||
- On-call availability: [ ]
|
||||
|
||||
## Service Area
|
||||
[Geographic zones you can cover]
|
||||
|
||||
# Commitment
|
||||
|
||||
I understand that as a Fleet Operator I will be required to:
|
||||
- Maintain 99%+ fleet uptime
|
||||
- Respond to incidents within 15 minutes
|
||||
- Complete monthly training
|
||||
- Document all activities in runbook
|
||||
- Follow all safety protocols
|
||||
- Represent Timmy professionally
|
||||
|
||||
**Signature:** _______________________
|
||||
**Date:** ___________________
|
||||
|
||||
# For Office Use Only
|
||||
|
||||
## Application Review
|
||||
- [ ] Application complete
|
||||
- [ ] Background check initiated
|
||||
- [ ] References contacted
|
||||
- [ ] Skills assessment scheduled
|
||||
- [ ] Interview scheduled
|
||||
|
||||
## Certification Path
|
||||
- Training module 1: [ ]
|
||||
- Training module 2: [ ]
|
||||
- Simulation test: [ ]
|
||||
- Practical exam: [ ]
|
||||
- Certification granted: [ ]
|
||||
|
||||
**Reviewer:** _______________________
|
||||
**Date:** ___________________
|
||||
113
specs/templates/partner-report.md
Normal file
113
specs/templates/partner-report.md
Normal file
@@ -0,0 +1,113 @@
|
||||
---
|
||||
# Partner Program Monthly Report
|
||||
partner_name: ""
|
||||
partner_id: ""
|
||||
report_period: "" # e.g., 2025-05
|
||||
report_date: ""
|
||||
partner_manager: ""
|
||||
---
|
||||
|
||||
# Executive Summary
|
||||
|
||||
[Brief overview of partner performance this period, key highlights, and areas needing attention]
|
||||
|
||||
## Key Metrics
|
||||
|
||||
| Metric | This Month | Last Month | Target | Status |
|
||||
|--------|------------|------------|--------|--------|
|
||||
| Leads Provided | [ ] | [ ] | [ ] | [ ] |
|
||||
| Qualified Leads | [ ] | [ ] | [ ] | [ ] |
|
||||
| Conversion Rate | [ ]% | [ ]% | >20% | [ ] |
|
||||
| Fleet Uptime (served) | [ ]% | [ ]% | >99.5% | [ ] |
|
||||
| Customer Satisfaction | [ ]/5 | [ ]/5 | >4.0 | [ ] |
|
||||
| Revenue Generated | $[ ] | $[ ] | $[ ] | [ ] |
|
||||
|
||||
# Lead Details
|
||||
|
||||
## New Leads This Period
|
||||
|
||||
| Lead ID | Company | Contact | Status | Notes |
|
||||
|---------|---------|---------|--------|-------|
|
||||
| | | | New | |
|
||||
| | | | Contacted | |
|
||||
| | | | Negotiation | |
|
||||
| | | | Closed-Won | |
|
||||
| | | | Closed-Lost | |
|
||||
|
||||
## Pipeline Forecast
|
||||
|
||||
| Stage | Count | Expected Value |
|
||||
|-------|-------|---------------|
|
||||
| Initial Contact | | $ |
|
||||
| Qualified | | $ |
|
||||
| Proposal | | $ |
|
||||
| Negotiation | | $ |
|
||||
| Closing | | $ |
|
||||
|
||||
# Fleet Performance (Partner's Customers)
|
||||
|
||||
## Uptime Summary
|
||||
- Total units served: [ ]
|
||||
- Average uptime: [ ]%
|
||||
- Units with >99.5%: [ ]
|
||||
- Incidents recorded: [ ]
|
||||
|
||||
## Incident Breakdown
|
||||
- P0-Critical: [ ]
|
||||
- P1-High: [ ]
|
||||
- P2-Medium: [ ]
|
||||
- P3-Low: [ ]
|
||||
|
||||
## Customer Feedback
|
||||
[Include summaries of customer compliments, complaints, or suggestions]
|
||||
|
||||
# Activities & Contributions
|
||||
|
||||
## Marketing Activities
|
||||
- [Events attended]
|
||||
- [Content created/shared]
|
||||
- [Campaigns participated in]
|
||||
|
||||
## Training & Enablement
|
||||
- [Training sessions completed]
|
||||
- [Certifications earned]
|
||||
- [Knowledge base contributions]
|
||||
|
||||
## Partnership Development
|
||||
- [Sub-partner referrals]
|
||||
- [New market opportunities identified]
|
||||
- [Product feedback provided]
|
||||
|
||||
# Financial Summary
|
||||
|
||||
## Revenue
|
||||
- Commission earned: $[ ]
|
||||
- Bonus (uptime targets): $[ ]
|
||||
- Other incentives: $[ ]
|
||||
- **Total:** $[ ]
|
||||
|
||||
## Costs (if applicable)
|
||||
- Marketing spend: $[ ]
|
||||
- Training costs: $[ ]
|
||||
|
||||
## Net Position: $[ ]
|
||||
|
||||
# Challenges & Support Needed
|
||||
|
||||
[List any obstacles, market challenges, or support requested from Timmy]
|
||||
|
||||
# Goals for Next Period
|
||||
|
||||
1. [ ]
|
||||
2. [ ]
|
||||
3. [ ]
|
||||
|
||||
# Partner Comments
|
||||
|
||||
[Any additional feedback from partner]
|
||||
|
||||
---
|
||||
|
||||
**Approved by Partner Manager:** ____________________ Date: _________
|
||||
|
||||
**Approved by Partnership Director:** ____________________ Date: _________
|
||||
@@ -1 +1,12 @@
|
||||
# Timmy core module
|
||||
|
||||
from .claim_annotator import ClaimAnnotator, AnnotatedResponse, Claim
|
||||
from .audit_trail import AuditTrail, AuditEntry
|
||||
|
||||
__all__ = [
|
||||
"ClaimAnnotator",
|
||||
"AnnotatedResponse",
|
||||
"Claim",
|
||||
"AuditTrail",
|
||||
"AuditEntry",
|
||||
]
|
||||
|
||||
156
src/timmy/claim_annotator.py
Normal file
156
src/timmy/claim_annotator.py
Normal file
@@ -0,0 +1,156 @@
|
||||
#!/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,
|
||||
)
|
||||
103
tests/timmy/test_claim_annotator.py
Normal file
103
tests/timmy/test_claim_annotator.py
Normal file
@@ -0,0 +1,103 @@
|
||||
#!/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!")
|
||||
Reference in New Issue
Block a user