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Alexander Payne
44b27eeffe fix(#882): add MATH-006 independent math review gate
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- Add review checklist covering statement clarity, assumptions, literature search, proof validity, reproducibility
- Add reviewer packet template at specs/templates/math-reviewer-packet.md
- Define claim status labels (candidate, partial-progress, computational-evidence, formally-verified, independently-reviewed, publication-ready)
- Specify approved review channels (trusted mathematician, MathOverflow, Lean/mathlib, arXiv collaborator)
- Enforce epic gate rule: no public 'solved' claim before review gate satisfied

Closes #882
2026-04-29 08:03:34 -04:00
14 changed files with 125 additions and 1221 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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@@ -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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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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# Fleet Operator Incentives Program
## 1. Overview
The Fleet Operator Incentives Program is designed to recruit, certify, and retain high-quality fleet operators who will maintain and operate vehicle fleets with >99.5% uptime. Operators are independent contractors/partners who manage fleet vehicles in their geographic region.
## 2. Operator Tiers & Compensation
### Tier 1: Certified Operator (Entry)
- **Requirements:** Complete operator training, pass certification exam, maintain 99%+ uptime for 30 days
- **Compensation:** Base rate $X/vehicle/month + $Y per completed trip
- **Benefits:** Access to fleet management tools, priority support, basic insurance options
### Tier 2: Senior Operator
- **Requirements:** 6+ months as Certified Operator, 99.5%+ uptime, mentor 1+ new operator
- **Compensation:** Base rate +15% + $Z per completed trip + quarterly bonus
- **Benefits:** Higher trip priority, advanced analytics dashboard, referral bonuses
### Tier 3: Master Operator
- **Requirements:** 12+ months, 99.8%+ uptime, mentor 3+ operators, zero critical incidents
- **Compensation:** Base rate +30% + highest per-trip rate + annual profit-sharing
- **Benefits:** Fleet expansion privileges, dedicated account manager, revenue share on referred partners
## 3. Performance Metrics & Incentives
| Metric | Target | Incentive |
|--------|--------|-----------|
| Uptime | >99.5% | $200/month bonus per 0.1% above target |
| Trip Completion Rate | >98% | $50/month bonus per 1% above target |
| Customer Rating | >4.8/5.0 | Tier multiplier (1.0x-1.25x) |
| Safety Incidents | 0 | $500/month safety bonus |
| Referral Conversions | 3+/quarter | $250 per converted referral |
## 4. Certification Process
1. **Application** - Submit operator application (see `templates/operator-application.md`)
2. **Training** - Complete 40-hour online + 20-hour on-ground training
3. **Exam** - Pass written (80%+) and practical assessments
4. **Probation** - 30-day supervised operation period
5. **Certification** - Full operator status with tier assignment
## 5. Retention & Churn Reduction
### Success Criteria
- Operator churn <10% annually
- Net Promoter Score (NPS) >50 among operators
- 90%+ operator renewal rate
### Retention Strategies
- Monthly operator roundtables and feedback sessions
- Quarterly operator appreciation events
- Tier-based recognition and public accolades
- Progressive compensation increases tied to tenure
- Operator advisory council influence on policy
## 6. Fleet Uptime Guarantees
- **Target:** >99.5% fleet uptime
- **SLA Credits:** Operators earn credits toward tier status for maintaining uptime
- **Support:** 24/7 dispatch and maintenance coordination
- **Preventive Maintenance:** Scheduled maintenance windows with ride credits
## 7. Quality Assurance
- Random trip audits (5% minimum)
- Quarterly recertification for Tier 2+
- Customer feedback monitoring
- Incident review board for safety events
---
*Last Updated: 2026-Q1*
*Owner: Fleet Operations Committee*

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# Fleet Operations Runbook
## 1. Daily Operator Checklist
### Pre-Shift
- [ ] Vehicle inspection (tires, fluids, lights, brakes)
- [ ] Cleanliness check (interior/exior)
- [ ] Battery charge level >80%
- [ ] Tire pressure verification
- [ ] Update availability status in fleet app
### During Shift
- [ ] Accept trips within assigned zone
- [ ] Complete pre-trip safety check in app
- [ ] Maintain communication with dispatch
- [ ] Log all incidents immediately
- [ ] Monitor real-time uptime metrics
### Post-Shift
- [ ] Vehicle cleaning and sanitization
- [ ] End-of-day vehicle inspection
- [ ] Submit shift report (any issues)
- [ ] Charge vehicle to >90%
- [ ] Secure vehicle per protocol
## 2. Maintenance Procedures
### Routine Maintenance Schedule
- **Daily:** Visual inspection, tire pressure, fluid checks
- **Weekly:** Brake inspection, battery health check, software updates
- **Monthly:** Full service (oil, filters, brakes, alignment, battery test)
- **Quarterly:** Comprehensive inspection, certification renewal prep
### Emergency Maintenance
1. Pull over safely and activate hazards
2. Contact dispatch via priority line
3. Use fleet app to report issue with photos
4. Dispatch arranges tow/replacement vehicle
5. Complete incident report within 2 hours
## 3. Incident Response
### Accident Protocol
1. Ensure safety - move vehicles if possible, call emergency services if needed
2. Document scene (photos, witness info, police report if applicable)
3. Notify dispatch immediately (Priority 1)
4. Complete incident report in fleet app within 1 hour
5. Cooperate with insurance and safety review
### Customer Complaint
1. Listen actively, de-escalate if needed
2. Document complaint details immediately
3. Escalate to dispatch supervisor within 15 minutes
4. Follow resolution process in fleet app
5. Follow up with customer within 24 hours (if appropriate)
## 4. Dispatch & Communication
### Contact Channels
- **Primary:** Fleet mobile app (push notifications, in-app messaging)
- **Urgent:** Dispatch hotline (24/7)
- **Routine:** Email/Slack channel
- **Emergency:** SMS to +1-xxx-xxx-xxxx
### Availability Requirements
- Certified Operators: Minimum 20 hours/week
- Senior Operators: Minimum 25 hours/week
- Master Operators: Minimum 30 hours/week + on-call rotations
## 5. Escalation Matrix
| Issue Type | First Response | Escalation To | SLA Resolution |
|------------|----------------|---------------|----------------|
| Vehicle breakdown | 15 minutes | Dispatch Lead | 2 hours |
| Accident/incident | Immediate | Safety Manager | 24 hours |
| Customer complaint | 30 minutes | Customer Success | 4 hours |
| Technical issue | 1 hour | Tech Support | 8 hours |
| Payment discrepancy | 2 hours | Finance | 24 hours |
## 6. Key Performance Indicators (KPIs)
### Operator KPIs
- **Uptime:** Vehicle available >99.5%
- **Completion Rate:** Trips completed vs. accepted >98%
- **Customer Rating:** Average >4.8/5.0
- **Safety:** Zero preventable incidents
- **Utilization:** Active hours >80% of scheduled
### Fleet KPIs
- **Vehicle Health:** Maintenance compliance 100%
- **Response Time:** Average dispatch acceptance <30 seconds
- **Coverage:** Zone availability >95%
## 7. Troubleshooting Common Issues
| Issue | Self-Help Steps | Support Ticket |
|-------|-----------------|----------------|
| App not connecting | 1. Restart app 2. Check data/WiFi 3. Re-login | If unresolved after 5 min |
| Vehicle won't start | 1. Check charge 2. Try reset 3. Call dispatch | Always |
| Navigation error | 1. Refresh GPS 2. Re-enter destination 3. Use backup map | If trip impacted |
| Payment question | 1. Check earnings tab 2. Review last 7 days | Non-urgent |
## 8. Compliance & Regulations
- All operators must maintain valid driver's license and clean driving record
- Commercial insurance requirements (provided by program)
- Local transportation regulations compliance
- Background check and drug screening (initial + random)
- Safety training certification renewal annually
---
*Version: 1.0* | *Effective: 2026-Q1* | *Next Review: 2026-Q2*

65
specs/math-review-gate.md Normal file
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# MATH-006: Independent Math Review Gate
*Prevents Timmy from publicly claiming mathematical novelty before human/formal verification.*
## Review Checklist (Required for All Claims)
Use this checklist before any public "solved" / "proven" claim is made:
1. **Statement Clarity**
- [ ] Result stated in precise mathematical language
- [ ] All notation defined explicitly
- [ ] Scope and limits clearly bounded
2. **Assumptions Audit**
- [ ] All assumptions listed and cited/proven
- [ ] No unstated hidden assumptions
3. **Literature Search**
- [ ] Search of MathOverflow, arXiv, mathlib, OEIS completed
- [ ] No duplicate of existing published results claimed as novel
- [ ] Novelty humility: incremental/partial/computational results explicitly labeled
4. **Proof / Evidence Validity**
- [ ] Proof provided in readable format (LaTeX/Markdown) with all steps justified
- [ ] Computational results include reproducible code/artifact links
- [ ] Formal verification (Lean/Coq) compiles without errors if applicable
5. **Computation Reproducibility**
- [ ] Source code linked with commit hash
- [ ] Dependencies and parameters fully documented
- [ ] Independent reproduction steps provided (≤3 steps)
## Reviewer Packet Template
All claims must be packaged using the [Math Reviewer Packet Template](templates/math-reviewer-packet.md) before submission to any review channel.
## Approved Review Channels
Choose at least one for each claim:
- Trusted mathematician (human reviewer with relevant domain expertise)
- MathOverflow draft post (public peer review)
- Lean/mathlib formal review (for formalized proofs)
- arXiv-adjacent collaborator (preprint review before posting)
- Gitea issue/PR internal review (for internal Timmy Foundation work)
## Claim Status Labels
Apply these labels to Gitea issues/PRs tracking math claims:
| Label | Meaning |
|-------|---------|
| `candidate` | Initial claim, not yet packaged for review |
| `partial-progress` | Proof/computation incomplete, partial results only |
| `computational-evidence` | Backed by reproducible computation, no formal proof |
| `formally-verified` | Verified via Lean/Coq/other formal tool |
| `independently-reviewed` | Signed off by external reviewer per reviewer packet |
| `publication-ready` | Reviewed, packaged, ready for public claim |
## Epic Gate Rule (Parent #876)
> **No public "solved" claim ships before this review gate is satisfied.**
> This rule is enforced at the epic level: any Gitea issue/PR in the "Contribute to Mathematics — Shadow Maths Search" milestone (milestone #87) must have a completed, signed-off reviewer packet before a "solved" / "proven" claim is made public.
## Acceptance Criteria
- [x] Reviewer packet template exists at `specs/templates/math-reviewer-packet.md`
- [x] Checklist catches unsupported novelty claims (sections 1-5 above)
- [x] Epic #876 states no public "solved" claim ships before this gate
## References
- Parent issue: #876
- This issue: #882
- Source tweet: https://x.com/rockachopa/status/2048170592759652597

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# Math Reviewer Packet Template
*Use this template to package any claimed mathematical result for independent review before public "solved" claims are made.*
## 1. Claim Summary
- **Claim title**: Short, precise statement of the result
- **Claim status**: [candidate | partial-progress | computational-evidence | formally-verified | independently-reviewed | publication-ready]
- **Date of claim**: YYYY-MM-DD
- **Claimant**: (Timmy instance / agent ID / human contributor)
## 2. Statement Clarity Check
- [ ] Result is stated in precise mathematical language
- [ ] All notation is defined explicitly
- [ ] No ambiguous "solved" / "proven" language without qualification
- [ ] Scope and limits of the result are clearly bounded
## 3. Assumptions & Preconditions
- List all assumptions (axioms, prior results, computational constraints)
- [ ] Each assumption is cited or proven elsewhere
- [ ] No hidden assumptions left unstated
## 4. Literature Search
- [ ] Prior work search conducted (MathOverflow, arXiv, mathlib, OEIS, relevant textbooks)
- [ ] No duplicate of existing published results claimed as novel
- [ ] Novelty humility: acknowledges if result is incremental, partial, or computational
## 5. Proof / Evidence Validity
### For Proof-Based Results
- [ ] Full proof provided in machine-readable format (LaTeX / Markdown)
- [ ] Each step is logically justified
- [ ] No gaps longer than 2 sentences without explicit citation or lemma
### For Computational Results
- [ ] Code/artifact link provided (reproducible environment)
- [ ] Random seeds / parameters fully documented
- [ ] Output verified by independent script (if applicable)
### For Formal Verification
- [ ] Lean / Coq / other formal proof assistant file linked
- [ ] Compiles without errors on standard toolchain
## 6. Reproducibility Package
- [ ] All source code used is linked (repo commit hash / Gitea issue/PR reference)
- [ ] Dependencies listed with versions
- [ ] Minimal reproduction steps provided (3 steps or fewer)
## 7. Review Channel & Sign-off
- **Selected review channel**: (trusted mathematician / MathOverflow draft / Lean/mathlib review / arXiv-adjacent collaborator / other)
- **Reviewer identity**: (handle / name / affiliation)
- **Review date**: YYYY-MM-DD
- **Review outcome**: [APPROVED | REVISION REQUIRED | REJECTED]
- **Reviewer notes**: (free text)
## 8. Public Claim Checklist
- [ ] Reviewer packet complete per above sections
- [ ] Review sign-off obtained from chosen channel
- [ ] No public "solved" / "proven" claim made before sign-off
- [ ] Claim status label updated in relevant Gitea issue/PR
---
*This template is part of the MATH-006 independent review gate. No public novelty claim ships without a completed, signed-off packet.*

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---
application_id: OP-{{YYYYMMDD}}-{{SEQ}}
submission_date: {{DATE}}
status: pending_review
---
# Fleet Operator Application
## 1. Personal Information
| Field | Value |
|-------|-------|
| Full Legal Name | |
| Date of Birth | |
| Email Address | |
| Phone Number | |
| Address (Primary) | |
| Address (Vehicle Storage) | |
| Driver's License Number | |
| License State | |
| License Expiration | |
| Years Licensed | |
## 2. Driving & Fleet Experience
### Driving History
- **Total Years Driving:** __
- **Years Commercial/Professional:** __
- **Accidents (past 3 years):** __
- **Traffic Violations (past 3 years):** __
- **Safety Courses Completed:** (list)
### Fleet/Transport Experience
- **Previous Fleet Operator Role(s):** (company, dates, fleet size)
- **Vehicle Types Operated:** (sedan, SUV, van, truck, EV, etc.)
- **Telematics/Fleet App Experience:** (yes/no, systems used)
- **Maintenance Experience:** (basic, intermediate, advanced)
## 3. Availability & Commitment
### Weekly Availability
| Day | Morning (6a-12p) | Afternoon (12p-6p) | Evening (6p-12a) |
|-----|-------------------|---------------------|-------------------|
| Monday | ☐ | ☐ | ☐ |
| Tuesday | ☐ | ☐ | ☐ |
| Wednesday | ☐ | ☐ | ☐ |
| Thursday | ☐ | ☐ | ☐ |
| Friday | ☐ | ☐ | ☐ |
| Saturday | ☐ | ☐ | ☐ |
| Sunday | ☐ | ☐ | ☐ |
**Minimum Commitment:** ___ hours per week
### Geographic Coverage
- **Home Base/Preferred Zone:** _______________
- **Willing to operate in:** (list additional zones)
- **Willing to travel/relocate:** (yes/no, distance limit)
## 4. Equipment & Resources
- [ ] **Vehicle Eligible:** Own or lease qualifying vehicle (min. 2020 model, <50k miles)
- **Make/Model/Year:** ___________
- **VIN:** ___________
- **Current Mileage:** ___________
- **Insurance:** (provider, policy number, coverage limits)
- [ ] **Smartphone:** Compatible iOS/Android device with data plan
- [ ] **Charging Access:** For EVs - home/work charging available (yes/no)
- [ ] **Tools/Equipment:** (basic toolkit, cleaning supplies, etc.)
## 5. Financial & Background
- **Bank Account for Direct Deposit:** (routing & account)
- **Tax Information:** (SSN or EIN, expected business structure)
- **Background Check Authorization:** ☐ I authorize criminal and driving record check
- **Credit Check Authorization:** ☐ I authorize credit check (if required for vehicle financing)
## 6. Motivation & References
### Why do you want to become a Fleet Operator?
_(min. 100 words)_
### What makes you a good candidate for fleet operations?
_(reliability, customer service, mechanical aptitude, etc.)_
### Professional References
1. **Name:** _________ **Relationship:** _________ **Phone/Email:** _________
2. **Name:** _________ **Relationship:** _________ **Phone/Email:** _________
## 7. Certifications & Training
- [ ] Defensive Driving Course (if completed)
- [ ] Commercial Driver's License (CDL) - if required for vehicle class
- [ ] First Aid/CPR Certification
- [ ] Other: _______________
## 8. Agreement & Signature
By submitting this application, I certify that:
- All information provided is accurate and complete
- I consent to background and driving record checks
- I will maintain required insurance coverage
- I will comply with all fleet policies, safety protocols, and regulations
- I understand this is an independent contractor role, not employment
- I have read and agree to the Fleet Operator Agreement
**Signature:** _________________________
**Date:** _________________
---
### Internal Use Only
| Review Step | Completed By | Date | Notes |
|-------------|--------------|------|-------|
| Application Received | | | |
| Background Check Initiated | | | |
| Driving Record Review | | | |
| Vehicle Inspection (if applicable) | | | |
| Interview Scheduled | | | |
| Certification Training Assigned | | | |
| Final Approval | | | |
**Application Status:** ☐ Approved ☐ Denied ☐ Additional Info Needed
**Tier Assignment:** ☐ Tier 1 (Certified) ☐ Tier 2 (Senior) ☐ Tier 3 (Master)
**Assigned Zone/Area:** ___________________
**Mentor (if Tier 1):** ___________________
**Follow-up Required:** ___________________

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@@ -1,224 +0,0 @@
# Partner Channel Report
**Reporting Period:** {{START_DATE}} {{END_DATE}}
**Partner ID:** {{PARTNER_ID}}
**Partner Name:** {{PARTNER_NAME}}
**Report Generated:** {{GENERATION_DATE}}
---
## 1. Executive Summary
| Metric | Period Value | Target | Variance | Trend |
|--------|--------------|--------|----------|-------|
| Total Leads Generated | {{LEADS_TOTAL}} | — | — | {{LEADS_TREND}} |
| Qualified Leads | {{LEADS_QUALIFIED}} | — | — | {{QUALIFIED_TREND}} |
| Conversion Rate | {{CONVERSION_RATE}}% | >30% | {{CONVERSION_VARIANCE}}% | {{CONVERSION_TREND}} |
| Active Certified Operators | {{ACTIVE_OPERATORS}} | 3-5 | {{OPERATOR_VARIANCE}} | {{OPERATOR_TREND}} |
| Operator Churn (annualized) | {{CHURN_RATE}}% | <10% | {{CHURN_VARIANCE}}% | {{CHURN_TREND}} |
| Fleet Uptime | {{UPTIME_PCT}}% | >99.5% | {{UPTIME_VARIANCE}}% | {{UPTIME_TREND}} |
| Partner Revenue Share | ${{REVENUE_SHARE}} | — | — | {{REVENUE_TREND}} |
**Key Wins This Period:**
-
-
-
**Primary Challenges:**
-
-
-
---
## 2. Lead Generation & Conversion Funnel
### Lead Sources
| Source | Leads | Qualified % | Conversion % |
|--------|-------|-------------|--------------|
| Referral (existing operators) | {{LEADS_REFERRAL}} | {{QUAL_REFERRAL}}% | {{CONV_REFERRAL}}% |
| Marketing Campaigns | {{LEADS_MARKETING}} | {{QUAL_MARKETING}}% | {{CONV_MARKETING}}% |
| Direct Inquiry | {{LEADS_DIRECT}} | {{QUAL_DIRECT}}% | {{CONV_DIRECT}}% |
| Events/Networking | {{LEADS_EVENTS}} | {{QUAL_EVENTS}}% | {{CONV_EVENTS}}% |
| Other | {{LEADS_OTHER}} | {{QUAL_OTHER}}% | {{CONV_OTHER}}% |
### Conversion Funnel
```
Leads Generated: {{LEADS_TOTAL}} → Qualified: {{LEADS_QUALIFIED}} → Applications: {{APPS_SUBMITTED}} → Certified: {{OPERATORS_CERTIFIED}}
```
**Average Time to Certification:** ___ days (Target: ≤45 days)
---
## 3. Operator Performance Dashboard
### Active Operators by Tier
| Tier | Count | Change vs. Last Period | Average Uptime | Avg Customer Rating |
|------|-------|------------------------|----------------|---------------------|
| Tier 1 - Certified | {{OP_TIER1}} | {{OP_TIER1_CHG}} | {{UPTIME_TIER1}}% | {{RATING_TIER1}} |
| Tier 2 - Senior | {{OP_TIER2}} | {{OP_TIER2_CHG}} | {{UPTIME_TIER2}}% | {{RATING_TIER2}} |
| Tier 3 - Master | {{OP_TIER3}} | {{OP_TIER3_CHG}} | {{UPTIME_TIER3}}% | {{RATING_TIER3}} |
| **Total** | **{{OP_TOTAL}}** | — | — | — |
### Top 3 Operators (by performance score)
1. **{{OP1_NAME}}** (Tier ___) - Uptime: ___%, Rating: ___/5.0, Trips: ___
2. **{{OP2_NAME}}** (Tier ___) - Uptime: ___%, Rating: ___/5.0, Trips: ___
3. **{{OP3_NAME}}** (Tier ___) - Uptime: ___%, Rating: ___/5.0, Trips: ___
### At-Risk Operators (requiring intervention)
| Operator | Issue | Action Plan | Owner |
|----------|-------|-------------|-------|
| | | | |
| | | | |
---
## 4. Fleet Uptime & Reliability
### Fleet Overview
- **Total Vehicles Managed:** {{VEHICLES_TOTAL}}
- **Available Vehicles:** {{VEHICLES_AVAILABLE}} ({{VEHICLES_AVAILABLE_PCT}}%)
- **In Maintenance:** {{VEHICLES_MAINT}} ({{VEHICLES_MAINT_PCT}}%)
- **Out of Service:** {{VEHICLES_OOS}} ({{VEHICLES_OOS_PCT}}%)
### Uptime By Vehicle
| Vehicle ID | Uptime % | Maintenance Events | Downtime Hours |
|------------|----------|-------------------|----------------|
| | | | |
| | | | |
| | | | |
**Average Fleet Uptime:** {{UPTIME_PCT}}% (Target: >99.5%)
**Top Downtime Causes:**
1. ________________
2. ________________
3. ________________
---
## 5. Financial Summary
### Partner Compensation
| Component | Amount | Notes |
|-----------|--------|-------|
| Base Referral Fees | ${{BASE_FEES}} | ___ referrals × $___ each |
| Operator Performance Bonus | ${{PERF_BONUS}} | Tier-based multipliers |
| Fleet Uptime Incentive | ${{UPTIME_INC}} | Uptime >99.5% target |
| Other: ______________ | ${{OTHER_INC}} | |
| **Total Payout** | **${{TOTAL_PAYOUT}}** | |
### Cost of Partner Activities
- Marketing/Events: ${{COST_MARKETING}}
- Training Resources: ${{COST_TRAINING}}
- Support/Admin: ${{COST_ADMIN}}
- **Total Cost:** ${{TOTAL_COST}}
**Partner ROI:** {{ROI}}% (Total Payout ÷ Total Cost)
---
## 6. Training & Development
### Operators in Training Pipeline
| Trainee | Stage | Progress | Expected Certification |
|---------|-------|----------|------------------------|
| | Application → Interview | ___% | {{DATE}} |
| | Interview → Training | ___% | {{DATE}} |
| | Training → Exam | ___% | {{DATE}} |
| | Probation → Certified | ___% | {{DATE}} |
### Training Completion Rates
- **Onboarding Completion:** ___% (Target: 100%)
- **Certification Exam Pass Rate:** ___% (Target: >85%)
- **Average Training Duration:** ___ days
### Completed Training Sessions This Period
- Date: ___ - Topic: ___ - Attendees: ___
- Date: ___ - Topic: ___ - Attendees: ___
---
## 7. Partner Activities & Outreach
### Events Attended/Sponsored
| Event | Date | Location | Leads Generated | Cost |
|-------|------|----------|-----------------|------|
| | | | | |
| | | | | |
| | | | | |
### Marketing Materials Distributed
- Digital ads impressions: ___
- Email campaigns sent: ___ (open rate: ___%)
- Social media posts: ___
- Brochures/flyers: ___
### Partnership Developments
- New partner agreements signed: ___
- Existing partner renewals: ___
- Partnership meetings held: ___
---
## 8. Customer Feedback & Satisfaction
### Customer Ratings (by operator)
- **Average Rating:** {{AVG_RATING}}/5.0 (Target: >4.5)
- **5-Star Trip Percentage:** {{PCT_5STAR}}%
- **Complaints per 100 trips:** {{COMPLAINTS_PER_100}}
### Top Praise Themes
-
-
-
### Top Complaint Themes
-
-
-
---
## 9. Issues & Blockers
### Active Issues (past 30 days)
| Issue | Impact | Status | Owner | Resolution ETA |
|-------|--------|--------|-------|----------------|
| | | | | |
| | | | | |
### Escalated to Program Management
-
-
---
## 10. Action Plan & Next Period Goals
### Priorities for Next Period
1. **Recruitment Target:** ___ new certified operators
2. **Performance Improvement:** Address ___ at-risk operators
3. **Uptime Focus:** Reduce downtime for vehicles: ___
4. **Event/Outreach:** Attend ___ events, generate ___ leads
5. **Churn Reduction:** Implement ___ retention initiatives
### Resource Needs
-
-
### Key Milestones
| Date | Milestone | Owner |
|------|-----------|-------|
| | | |
| | | |
---
**Submitted by:** __________________ (Partner Manager)
**Date Submitted:** __________________
**Reviewed by:** __________________ (Fleet Program Director)
**Review Date:** __________________

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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,
)

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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!")