Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add plurigrid/asi --skill geodesic-manifoldgit clone --depth 1 https://github.com/plurigrid/asiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/plurigrid/asi/geodesic-manifold)<a href="https://agentmods.dev/skills/plurigrid/asi/geodesic-manifold"><img src="https://agentmods.dev/badge/skills/plurigrid/asi/geodesic-manifold.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01469 |
| Opus 5 | $0.00000 | $0.00734 |
| Sonnet 5 | $0.00000 | $0.00294 |
| Haiku 4.5 | $0.00000 | $0.00147 |
Grade A, and why
geodesic-manifold scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Geodesic Manifold Skill
Spherical geometry, great circles, and Riemannian manifolds with Gay.jl coloring.
Trigger
- Geodesic calculations, great circle routes
- Spherical trigonometry, haversine distance
- Riemannian geometry on Earth's surface
- Flight paths, navigation, ship routing
GF(3) Trit Assignment
- +1 (Generator): Creates geodesic paths, generates waypoints
- 0 (Ergodic): Distance calculations, coordinate transforms
- -1 (Validator): Verifies shortest path optimality
Core Concepts
Great Circle Distance (Haversine)
import math
def haversine(lat1, lon1, lat2, lon2):
"""Distance in km between two points on Earth."""
R = 6371 # Earth radius km
phi1, phi2 = math.radians(lat1), math.radians(lat2)
dphi = math.radians(lat2 - lat1)
dlambda = math.radians(lon2 - lon1)
a = math.sin(dphi/2)**2 + math.cos(phi1) * math.cos(phi2) * math.sin(dlambda/2)**2
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a))
return R * c
Geodesic Waypoints with Color
def geodesic_waypoints(lat1, lon1, lat2, lon2, n_points, seed):
"""Generate colored waypoints along great circle."""
from math import radians, degrees, sin, cos, atan2, sqrt
# Convert to radians
phi1, lambda1 = radians(lat1), radians(lon1)
phi2, lambda2 = radians(lat2), radians(lon2)
waypoints = []
for i in range(n_points + 1):
f = i / n_points # Fraction along path
# Spherical interpolation (slerp)
d = haversine(lat1, lon1, lat2, lon2) / 6371
a = sin((1 - f) * d) / sin(d)
b = sin(f * d) / sin(d)
x = a * cos(phi1) * cos(lambda1) + b * cos(phi2) * cos(lambda2)
y = a * cos(phi1) * sin(lambda1) + b * cos(phi2) * sin(lambda2)
z = a * sin(phi1) + b * sin(phi2)
lat = degrees(atan2(z, sqrt(x**2 + y**2)))
lon = degrees(atan2(y, x))
# Color from seed + index
wp_seed = (seed + i * 0x9E3779B97F4A7C15) & 0x7FFFFFFFFFFFFFFF
color = color_from_seed(wp_seed)
waypoints.append({
'index': i,
'lat': lat,
'lon': lon,
'fraction': f,
'color': color['hex'],
'trit': color['trit']
})
return waypoints
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 190 lines · 0 tokens per session scan A 763e49031a78
geodesic-manifold is a skill published in the GitHub repository plurigrid/asi (62 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,469 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-01.
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