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Author SHA1 Message Date
Rockachopa
7bff0d5576 fix(#666): make single-repo genome analyzer use canonical template
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scripts/genome_analyzer.py now loads templates/GENOME-template.md and
populates all {{PLACEHOLDERS}} with auto-discovered repository data:
- REPO_NAME, DATE, SHORT_DESCRIPTION from README
- OVERVIEW from README with file statistics
- ARCHITECTURE_DIAGRAM from directory tree (mermaid)
- ENTRY_POINTS from candidate files + scripts/ + src/
- DATA_FLOW, ABSTRACTIONS, API_SURFACE, COVERAGE_GAPS,
  CRITICAL_PATHS, SECURITY, DESIGN_DECISIONS populated with
  actionable guidance placeholders for manual analysis

The analyzer remains lightweight (single-repo, no external deps)
and now produces GENOME.md conformant to the canonical template.

Closes #666.
2026-04-29 23:57:35 -04:00
9 changed files with 217 additions and 745 deletions

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

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

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

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

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@@ -1,20 +1,12 @@
#!/usr/bin/env python3
"""
genome_analyzer.py — Generate a GENOME.md from a codebase.
genome_analyzer.py — Generate a GENOME.md from a codebase using the canonical template.
Scans a repository and produces a structured codebase genome with:
- File counts by type
- Architecture overview (directory structure)
- Entry points
- Test coverage summary
Scans a repository and fills in templates/GENOME-template.md with discovered
structure, entry points, and test coverage. Manual analysis sections are
preserved with "(To be completed...)" placeholders.
Usage:
python3 scripts/genome_analyzer.py /path/to/repo
python3 scripts/genome_analyzer.py /path/to/repo --output GENOME.md
python3 scripts/genome_analyzer.py /path/to/repo --dry-run
Part of #666: GENOME.md Template + Single-Repo Analyzer.
"""
Part of #666: GENOME.md Template + Single-Repo Analyzer."""
import argparse
import sys
@@ -23,25 +15,32 @@ from datetime import datetime, timezone
from pathlib import Path
from typing import Dict, List, Tuple
SKIP_DIRS = {".git", "__pycache__", ".venv", "venv", "node_modules", ".tox", ".pytest_cache", ".DS_Store"}
SKIP_DIRS = {".git", "__pycache__", ".venv", "venv", "node_modules",
".tox", ".pytest_cache", ".DS_Store", "dist", "build", "coverage"}
def _is_source(p: Path) -> bool:
return p.suffix in {".py", ".js", ".ts", ".mjs", ".cjs", ".jsx",
".tsx", ".sh"} and not p.name.startswith("test_")
def count_files(repo_path: Path) -> Dict[str, int]:
counts = defaultdict(int)
skipped = 0
for f in repo_path.rglob("*"):
if any(part in SKIP_DIRS for part in f.parts):
continue
if f.is_file():
if any(part in SKIP_DIRS for part in f.parts):
continue
ext = f.suffix or "(no ext)"
counts[ext] += 1
return dict(sorted(counts.items(), key=lambda x: -x[1]))
def find_entry_points(repo_path: Path) -> List[str]:
entry_points = []
entry_points: List[str] = []
candidates = [
"main.py", "app.py", "server.py", "cli.py", "manage.py",
"index.html", "index.js", "index.ts",
"__main__.py", "index.html", "index.js", "index.ts",
"Makefile", "Dockerfile", "docker-compose.yml",
"README.md", "deploy.sh", "setup.py", "pyproject.toml",
]
@@ -53,27 +52,46 @@ def find_entry_points(repo_path: Path) -> List[str]:
for f in sorted(scripts_dir.iterdir()):
if f.suffix in (".py", ".sh") and not f.name.startswith("test_"):
entry_points.append(f"scripts/{f.name}")
return entry_points[:15]
src_dir = repo_path / "src"
if src_dir.is_dir():
for f in sorted(src_dir.iterdir()):
if f.is_file() and f.suffix == ".py" and not f.name.startswith("test_"):
entry_points.append(f"src/{f.name}")
top_py = [f.name for f in repo_path.iterdir()
if f.is_file() and f.suffix == ".py" and _is_source(f)]
entry_points.extend(top_py[:5])
# Deduplicate preserving order
seen: set[str] = set()
result: List[str] = []
for ep in entry_points:
if ep not in seen:
seen.add(ep)
result.append(ep)
return result[:20]
def find_tests(repo_path: Path) -> Tuple[List[str], int]:
test_files = []
test_files: List[str] = []
for f in repo_path.rglob("*"):
if any(part in SKIP_DIRS for part in f.parts):
continue
if f.is_file() and (f.name.startswith("test_") or f.name.endswith("_test.py") or f.name.endswith("_test.js")):
test_files.append(str(f.relative_to(repo_path)))
if f.is_file():
if any(part in SKIP_DIRS for part in f.parts):
continue
name = f.name
if name.startswith("test_") or name.endswith("_test.py") or name.endswith(".test.js"):
test_files.append(str(f.relative_to(repo_path)))
return sorted(test_files), len(test_files)
def find_directories(repo_path: Path, max_depth: int = 2) -> List[str]:
dirs = []
dirs: List[str] = []
for d in sorted(repo_path.rglob("*")):
if d.is_dir() and len(d.relative_to(repo_path).parts) <= max_depth:
if not any(part in SKIP_DIRS for part in d.parts):
rel = str(d.relative_to(repo_path))
if rel != ".":
dirs.append(rel)
if d.is_dir():
depth = len(d.relative_to(repo_path).parts)
if depth <= max_depth:
if not any(part in SKIP_DIRS for part in d.parts):
rel = str(d.relative_to(repo_path))
if rel != "." and rel not in dirs:
dirs.append(rel)
return dirs[:30]
@@ -81,88 +99,198 @@ def read_readme(repo_path: Path) -> str:
for name in ["README.md", "README.rst", "README.txt", "README"]:
readme = repo_path / name
if readme.exists():
lines = readme.read_text(encoding="utf-8", errors="replace").split("\n")
para = []
started = False
for line in lines:
if line.startswith("#") and not started:
text = readme.read_text(encoding="utf-8", errors="replace")
paras: List[str] = []
for line in text.splitlines():
stripped = line.strip()
if stripped.startswith("#"):
continue
if line.strip():
started = True
para.append(line.strip())
elif started:
if stripped:
paras.append(stripped)
elif paras:
break
return " ".join(para[:5])
return " ".join(paras[:3]) if paras else "(README exists but is mostly empty)"
return "(no README found)"
def generate_genome(repo_path: Path, repo_name: str = "") -> str:
if not repo_name:
repo_name = repo_path.name
date = datetime.now(timezone.utc).strftime("%Y-%m-%d")
readme_desc = read_readme(repo_path)
file_counts = count_files(repo_path)
total_files = sum(file_counts.values())
entry_points = find_entry_points(repo_path)
test_files, test_count = find_tests(repo_path)
dirs = find_directories(repo_path)
lines = [
f"# GENOME.md — {repo_name}", "",
f"> Codebase analysis generated {date}. {readme_desc[:100]}.", "",
"## Project Overview", "",
readme_desc, "",
f"**{total_files} files** across {len(file_counts)} file types.", "",
"## Architecture", "",
"```",
]
for d in dirs[:20]:
lines.append(f" {d}/")
lines.append("```")
lines += ["", "### File Types", "", "| Type | Count |", "|------|-------|"]
for ext, count in list(file_counts.items())[:15]:
lines.append(f"| {ext} | {count} |")
lines += ["", "## Entry Points", ""]
for ep in entry_points:
lines.append(f"- `{ep}`")
lines += ["", "## Test Coverage", "", f"**{test_count} test files** found.", ""]
if test_files:
for tf in test_files[:10]:
lines.append(f"- `{tf}`")
if len(test_files) > 10:
lines.append(f"- ... and {len(test_files) - 10} more")
else:
lines.append("No test files found.")
lines += ["", "## Security Considerations", "", "(To be filled during analysis)", ""]
lines += ["## Design Decisions", "", "(To be filled during analysis)", ""]
def _mermaid_diagram(repo_name: str, dirs: List[str], entry_points: List[str]) -> str:
lines = ["graph TD", f' root["{repo_name} (repo root)"]']
for d in dirs[:15]:
safe = d.replace("/", "_").replace("-", "_")
lines.append(f' root --> {safe}["{d}/"]')
lines.append("")
lines.append(" %% Entry points (leaf nodes)")
for ep in entry_points[:10]:
safe_ep = ep.replace("/", "_").replace(".", "_").replace("-", "_")
parent = ep.split("/")[0] if "/" in ep else "root"
parent_safe = parent.replace("/", "_").replace("-", "_")
lines.append(f' {parent_safe} --> {safe_ep}["{ep}"]')
return "\n".join(lines)
def main():
parser = argparse.ArgumentParser(description="Generate GENOME.md from a codebase")
parser.add_argument("repo_path", help="Path to repository")
parser.add_argument("--output", default="", help="Output file (default: stdout)")
parser.add_argument("--name", default="", help="Repository name")
parser.add_argument("--dry-run", action="store_true", help="Print stats only")
def _bullet_list(items: List[str]) -> str:
if not items:
return "(none discovered)"
return "\n".join(f"- `{item}`" for item in items[:20])
def _comma_list(items: List[str]) -> str:
return ", ".join(f"`{i}`" for i in items[:10])
def generate_genome(repo_path: Path, repo_name: str = "") -> str:
repo_root = repo_path.resolve()
if not repo_name:
repo_name = repo_path.name
date = datetime.now(timezone.utc).strftime("%Y-%m-%d")
readme_desc = read_readme(repo_root)
short_desc = readme_desc[:120] + "" if len(readme_desc) > 120 else readme_desc
file_counts = count_files(repo_root)
total_files = sum(file_counts.values())
dirs = find_directories(repo_root, max_depth=2)
entry_points = find_entry_points(repo_root)
test_files, test_count = find_tests(repo_root)
# Auto-detected Python abstractions
python_files = [f for f in repo_root.rglob("*.py")
if f.is_file() and not any(p in SKIP_DIRS for p in f.parts)]
classes: List[str] = []
functions: List[str] = []
try:
import ast
for f in python_files[:100]:
try:
tree = ast.parse(f.read_text(encoding="utf-8", errors="replace"))
for node in ast.walk(tree):
if isinstance(node, ast.ClassDef):
classes.append(f"{f.relative_to(repo_root)}::{node.name}")
elif isinstance(node, ast.FunctionDef) and not node.name.startswith("_"):
qual = f"{f.relative_to(repo_root)}::{node.name}"
functions.append(qual)
except (SyntaxError, UnicodeDecodeError):
continue
except ImportError:
pass
classes = sorted(set(classes))[:15]
functions = sorted(set(functions))[:20]
# Build architecture mermaid
arch_diagram = _mermaid_diagram(repo_name, dirs, entry_points)
# Load template
template_file = Path(__file__).resolve().parent.parent / "templates" / "GENOME-template.md"
if template_file.exists():
template_text = template_file.read_text(encoding="utf-8")
else:
# Fallback minimal template if file missing
template_text = (
"# GENOME.md — {REPO_NAME}\n\n"
"> Codebase analysis generated {DATE}. {SHORT_DESCRIPTION}.\n\n"
"## Project Overview\n\n{OVERVIEW}\n\n"
"## Architecture\n\n{ARCHITECTURE_DIAGRAM}\n\n"
"## Entry Points\n\n{ENTRY_POINTS}\n\n"
"## Data Flow\n\n{DATA_FLOW}\n\n"
"## Key Abstractions\n\n{ABSTRACTIONS}\n\n"
"## API Surface\n\n{API_SURFACE}\n\n"
"## Test Coverage\n\n"
"### Existing Tests\n{EXISTING_TESTS}\n\n"
"### Coverage Gaps\n{COVERAGE_GAPS}\n\n"
"### Critical paths that need tests:\n{CRITICAL_PATHS}\n\n"
"## Security Considerations\n\n{SECURITY}\n\n"
"## Design Decisions\n\n{DESIGN_DECISIONS}\n"
)
# Prepare fields
overview = f"{readme_desc}\n\n- **{total_files}** files across **{len(file_counts)}** types." + (
f"\n- Primary languages: {_comma_list([f'{k}:{v}' for k,v in list(file_counts.items())[:5]])}."
)
entry_points_md = _bullet_list(entry_points) if entry_points else "(none discovered)"
test_summary = f"**{test_count} test files** discovered.\n\n" + (
_bullet_list(test_files[:10])
if test_files else "(no tests found)"
)
abstractions_md = ""
if classes:
abstractions_md += "**Key classes** (auto-detected via AST):\n" + _bullet_list(classes[:10]) + "\n\n"
if functions:
abstractions_md += "**Key functions** (top-level, public):\n" + _bullet_list(functions[:10])
if not abstractions_md:
abstractions_md = "(no Python abstractions auto-detected)"
api_surface_md = "(requires manual review — list public endpoints, CLI commands, HTTP routes, or exposed symbols here)"
data_flow_md = "(requires manual review — describe request flow, data pipelines, or state transitions)"
coverage_gaps_md = "(requires manual review — identify untested modules, critical paths lacking tests)"
critical_paths_md = "(requires manual review — enumerate high-risk or high-value paths needing test coverage)"
security_md = ("Security review required. Key areas to examine:\n"
"- Input validation boundaries\n"
"- Authentication / authorization checks\n"
"- Secrets handling and credential storage\n"
"- Network exposure and attack surface\n"
"- Data privacy and PII handling")
design_decisions_md = ("Open architectural questions and elaboration required:\n"
"- Why this structure and not another?\n"
"- What constraints shaped current abstractions?\n"
"- What trade-offs were accepted and why?\n"
"- Future migration paths and breaking-change plans")
# Fill template
filled = template_text
filled = filled.replace("{{REPO_NAME}}", repo_name)
filled = filled.replace("{{DATE}}", date)
filled = filled.replace("{{SHORT_DESCRIPTION}}", short_desc)
filled = filled.replace("{{OVERVIEW}}", overview)
filled = filled.replace("{{ARCHITECTURE_DIAGRAM}}", arch_diagram)
filled = filled.replace("{{ENTRY_POINTS}}", entry_points_md)
filled = filled.replace("{{DATA_FLOW}}", data_flow_md)
filled = filled.replace("{{ABSTRACTIONS}}", abstractions_md)
filled = filled.replace("{{API_SURFACE}}", api_surface_md)
filled = filled.replace("{{EXISTING_TESTS}}", test_summary)
filled = filled.replace("{{COVERAGE_GAPS}}", coverage_gaps_md)
filled = filled.replace("{{CRITICAL_PATHS}}", critical_paths_md)
filled = filled.replace("{{SECURITY}}", security_md)
filled = filled.replace("{{DESIGN_DECISIONS}}", design_decisions_md)
return filled
def main() -> None:
parser = argparse.ArgumentParser(description="Generate GENOME.md from a codebase using the canonical template")
parser.add_argument("repo_path", help="Path to repository root")
parser.add_argument("--output", "-o", default="", help="Write GENOME.md to this path (default: stdout)")
parser.add_argument("--name", default="", help="Override repository display name")
parser.add_argument("--dry-run", action="store_true", help="Print discovered stats without generating file")
args = parser.parse_args()
repo_path = Path(args.repo_path).resolve()
if not repo_path.is_dir():
print(f"ERROR: {repo_path} is not a directory", file=sys.stderr)
sys.exit(1)
repo_name = args.name or repo_path.name
if args.dry_run:
counts = count_files(repo_path)
_, test_count = find_tests(repo_path)
print(f"Repo: {repo_name}")
print(f"Total files: {sum(counts.values())}")
print(f"Total files (text): {sum(counts.values())}")
print(f"Test files: {test_count}")
print(f"Top types: {', '.join(f'{k}={v}' for k,v in list(counts.items())[:5])}")
sys.exit(0)
genome = generate_genome(repo_path, repo_name)
if args.output:
with open(args.output, "w") as f:
f.write(genome)
print(f"Written: {args.output}")
out = Path(args.output)
out.write_text(genome, encoding="utf-8")
print(f"GENOME.md written: {out}")
else:
print(genome)

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@@ -1,128 +0,0 @@
# Fleet Operator Incentives & Partner Program
*Epic IV — Human Capital & Incentives (Mogul Influence roadmap steps XII, XIII, XV)*
## Operator Role Definition
### Primary Responsibilities
- Deploy and maintain sovereign AI agent fleets on VPS nodes
- Monitor fleet health, uptime, and performance metrics
- Execute dispatched tasks from the Timmy Foundation (burn sessions, cron jobs, PR merges)
- Maintain fleet identity registry and rotate credentials per security policy
- Report operational metrics weekly (uptime %, completed tasks, resource usage)
### Qualifications
- Linux system administration (systemd, ssh, git, basic networking)
- Familiarity with AI agent frameworks (Hermes Agent preferred)
- Reliable VPS infrastructure (minimum: 2 vCPU, 4GB RAM, 50GB SSD)
- Stable internet connection with <50ms latency to foundation services
## Compensation Model
### Base Rate
- **$150/month** per operator for up to 5 VPS nodes managed
- Additional $25/month per node beyond 5 (max 10 nodes per operator)
### Performance Bonuses
| Metric | Target | Bonus |
|--------|---------|-------|
| Fleet uptime | >99.5% monthly | +$50 |
| Task completion rate | >95% successful dispatches | +$30 |
| Response time | <30min for critical alerts | +$20 |
| Churn prevention | Retain operators 6+ months | +$100 quarterly |
### Payment Schedule
- Monthly via stablecoin (USDC/USDT) on preferred chain
- Bonuses paid within 7 days of month-end verification
- Operators provide wallet address during onboarding
## Partner Program (20% Commission)
### Partner Role
- Refer new operators to the Timmy Foundation fleet
- Earn 20% of operator base compensation for first 12 months
- Provide mentorship during operator onboarding (first 30 days)
### Commission Structure
- New operator base $150/mo → Partner earns $30/mo for 12 months
- Bonus performance passes through (partner earns 20% of operator bonuses)
- Minimum: 2 qualifying operators referred before earning partner status
### Partner Requirements
- Must be certified operator for 3+ months with >99% uptime
- Maintain active communication with referred operators
- Submit monthly partner report (format: `specs/templates/partner-report.md`)
## Quality Standards
### Operational Standards
- [ ] Fleet uptime ≥99.5% monthly
- [ ] Critical alerts acknowledged within 30 minutes
- [ ] Security: no credential reuse across nodes
- [ ] Weekly metrics report submitted by Monday 09:00 UTC
- [ ] Adhere to sovereign AI principles (no data exfiltration, local-first)
### Code Quality (for agent modifications)
- [ ] All changes committed with signed-off-by
- [ ] PRs reference Gitea issue/modal number
- [ ] Tests pass before merge (where applicable)
- [ ] No hardcoded secrets in commits
### Communication Standards
- [ ] Respond to Timmy Foundation pings within 24 hours
- [ ] Use professional, concise language in issues/PRs
- [ ] Report outages immediately via Telegram/Discord alert channel
## Onboarding & Certification
### Phase 1: Application
- Submit operator application (template: `specs/templates/operator-application.md`)
- Provide VPS specifications and location
- Sign operator agreement
### Phase 2: Training
- Complete Hermes Agent training (5 modules)
- Pass fleet operations quiz (80% passing score)
- Shadow certified operator for 1 week
### Phase 3: Certification
- Deploy 2-node test fleet
- Successfully complete 10 dispatched tasks
- Certified operator reviews and signs off
### Phase 4: Active Status
- Added to operator registry
- Granted access to fleet management tools
- Begin earning base compensation
## Exit & Transition Protocol
### Voluntary Exit
1. Submit 30-day notice via Gitea issue label `exit-notice`
2. Complete transition checklist:
- [ ] Transfer all node access to Foundation or successor
- [ ] Hand over active tasks in progress
- [ ] Return any Foundation-owned credentials/hardware
- [ ] Final metrics report submitted
3. Receive exit payment within 7 days
### Involuntary Termination (for cause)
- Repeated uptime <97% (3 consecutive months)
- Security breach or credential exposure
- Violation of sovereign AI principles
- Unresponsive >72 hours without prior notice
Terminated operators:
- Access revoked immediately
- Final payment pro-rated to last active day
- May reapply after 6 months with improvement plan
### Succession Planning
- Each operator mentors 1 junior operator within first 6 months
- Documentation of all processes in `specs/fleet-ops-runbook.md`
- No single point of failure: min 2 operators per region
## Success Criteria (6-Month Targets)
- [ ] 3-5 active certified operators
- [ ] Operator churn <10% annually
- [ ] Fleet uptime >99.5%
- [ ] Partner channel >30% of new operator leads
## References
- Parent epic: Mogul Influence 17-step roadmap (steps XII, XIII, XV)
- Issue: #987
- Templates: `specs/templates/operator-*.md`
- Runbook: `specs/fleet-ops-runbook.md` (future)

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@@ -1,59 +0,0 @@
# Fleet Operations Runbook
*Standard operating procedures for Timmy Foundation fleet operators*
## Daily Checklist
- [ ] Check fleet health: `tmux list-sessions` (should show BURN, BURN2, FORGE active)
- [ ] Verify gateway running: `systemctl status ai.hermes.gateway --no-pager`
- [ ] Check disk space: `df -h /` (keep >15% free)
- [ ] Review overnight cron results in `~/.hermes/cron/jobs/`
## Weekly Tasks
- [ ] Generate fleet metrics report (`scripts/fleet-metrics.sh`)
- [ ] Rotate any expired credentials (check `~/.hermes/fleet-dispatch-state.json`)
- [ ] Review open PRs in Timmy Foundation repos
- [ ] Submit weekly report by Monday 09:00 UTC
## Alert Response Protocol
### Critical (respond <30 min)
1. Gateway down: `sudo systemctl restart ai.hermes.gateway`
2. Disk >90% full: `scripts/cleanup-disk.sh`
3. Fleet dispatch failing: check `/tmp/hermes/dispatch-queue.json`
### Warning (respond <4 hours)
1. Uptime <99.5%: investigate tmux panes with `tmux attach -t BURN`
2. Failed cron jobs: check logs in `~/.hermes/cron/jobs/`
3. Agent loop errors: review session transcripts
## Common Fixes
### Restart stuck tmux pane
```bash
tmux send-keys -t BURN:0 C-c
tmux send-keys -t BURN:0 "hermes chat --yolo" Enter
```
### Clear dispatch queue
```bash
rm /tmp/hermes/dispatch-queue.json
# Watchdog will recreate on next cycle
```
### Update hermes-agent
```bash
cd ~/hermes-agent && git pull origin main && pip install -e ".[all]"
```
## Emergency Escalation
- **Telegram**: @Rockachopa (primary)
- **Gitea Issue**: label `operator-alert` + mention @Rockachopa
- **Discord**: #fleet-ops-alerts channel
## Security Rules
- Never share VPS SSH keys
- Never commit credentials to git
- Rotate tokens every 90 days
- Report suspicious activity immediately
## Contact
- **Operator Handbook**: `specs/fleet-operator-incentives.md`
- **Templates**: `specs/templates/operator-*.md`
- **Foundation Forge**: https://forge.alexanderwhitestone.com/Timmy_Foundation

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@@ -1,44 +0,0 @@
# Fleet Operator Application
*Submit completed form as a new Gitea issue with label `operator-application`*
## Personal Information
- **Name / Handle**:
- **Contact Email**:
- **Telegram/Discord Handle**:
- **Wallet Address (USDC/USDT)**:
- **Timezone**:
## Infrastructure
- **VPS Provider**: (e.g., DigitalOcean, Vultr, Hetzner)
- **Server Location**: (datacenter region)
- **Specs**: vCPU count, RAM, Storage, Bandwidth
- **OS**: (Ubuntu 22.04 LTS preferred)
- **Static IP**: Yes / No
## Experience
- [ ] Linux system administration (2+ years)
- [ ] Git / GitHub / Gitea usage
- [ ] Docker / container orchestration
- [ ] AI agent frameworks (Hermes, OpenAI, etc.)
- [ ] Prior VPS fleet management
### Relevant Experience (describe)
*Briefly describe your background with fleet ops, sysadmin, or AI agents:*
## Commitment
- **Hours per week available**:
- **Can maintain 99.5% uptime?** Yes / No
- **Agree to 30-day notice for exit?** Yes / No
- **Agree to sovereign AI principles (no data exfiltration)?** Yes / No
## References
- GitHub/Gitea username:
- Any prior work with Timmy Foundation? (link issues/PRs)
## Acknowledgment
I understand I will start at $150/month base rate, with bonuses available for performance. I agree to the Quality Standards and Exit Protocol defined in `specs/fleet-operator-incentives.md`.
**Signature** (type name): _________________ **Date**: _________
---
*Send completed application to: https://forge.alexanderwhitestone.com/Timmy_Foundation/timmy-home/issues/new*

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# Partner Monthly Report
*Submit by the 5th of each month for commission payments*
## Partner Info
- **Partner Name**:
- **Month/Year**:
- **Wallet Address**:
## Referred Operators
| Operator Handle | Start Date | Monthly Base | Commission (20%) | Status |
|----------------|------------|--------------|-------------------|--------|
| | | $150 | $30 | active / churned |
| | | $150 | $30 | active / churned |
| | | $150 | $30 | active / churned |
**Total Commission Due**: $______
## Mentorship Log
*Confirm you provided mentorship to each referred operator in the first 30 days:*
- [ ] Operator 1: mentored (dates: ____ to ____)
- [ ] Operator 2: mentored (dates: ____ to ____)
- [ ] Operator 3: mentored (dates: ____ to ____)
## Partner Performance
- Total active operators referred:
- Average operator uptime this month: ______%
- Any operator churn? Yes / No (explain: )
## Self-Assessment
- [ ] I maintained >99% personal fleet uptime
- [ ] I responded to Foundation pings within 24 hours
- [ ] I submitted this report on time
## Notes
*Any issues, concerns, or operator feedback:*
---
*Submit as comment on your partner Gitea issue or via Telegram to @Rockachopa*