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 geohash-coloringgit 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/geohash-coloring)<a href="https://agentmods.dev/skills/plurigrid/asi/geohash-coloring"><img src="https://agentmods.dev/badge/skills/plurigrid/asi/geohash-coloring/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/plurigrid/asi/geohash-coloring"><img src="https://agentmods.dev/badge/skills/plurigrid/asi/geohash-coloring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.03061 |
| Opus 5 | $0.00000 | $0.01530 |
| Sonnet 5 | $0.00000 | $0.00612 |
| Haiku 4.5 | $0.00000 | $0.00306 |
Grade A, and why
geohash-coloring 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 8d 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 — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Geohash Coloring Skill
GF(3) colored geohashes for hierarchical spatial indexing with deterministic color derivation.
Trigger
- Geohash encoding/decoding
- Hierarchical spatial clustering
- Location-based coloring schemes
- Privacy-preserving location representation
GF(3) Trit: +1 (Generator)
Generates colored spatial identifiers from coordinates.
Geohash Basics
Geohash encodes lat/lon into a string where:
- Longer = more precise
- Prefix = parent cell
- Adjacent cells share prefixes
Precision | Cell Width | Cell Height
1 | 5,009 km | 4,992 km
2 | 1,252 km | 624 km
3 | 156 km | 156 km
4 | 39 km | 19 km
5 | 5 km | 5 km
6 | 1.2 km | 0.6 km
7 | 153 m | 153 m
8 | 38 m | 19 m
9 | 5 m | 5 m
Core Implementation
import hashlib
# Geohash alphabet (base32)
GEOHASH_CHARS = '0123456789bcdefghjkmnpqrstuvwxyz'
def encode_geohash(lat: float, lon: float, precision: int = 9) -> str:
"""Encode lat/lon to geohash string."""
lat_range = (-90.0, 90.0)
lon_range = (-180.0, 180.0)
geohash = []
bits = 0
bit_count = 0
is_lon = True
while len(geohash) < precision:
if is_lon:
mid = (lon_range[0] + lon_range[1]) / 2
if lon >= mid:
bits = (bits << 1) | 1
lon_range = (mid, lon_range[1])
else:
bits = bits << 1
lon_range = (lon_range[0], mid)
else:
mid = (lat_range[0] + lat_range[1]) / 2
if lat >= mid:
bits = (bits << 1) | 1
lat_range = (mid, lat_range[1])
else:
bits = bits << 1
lat_range = (lat_range[0], mid)
is_lon = not is_lon
bit_count += 1
if bit_count == 5:
geohash.append(GEOHASH_CHARS[bits])
bits = 0
bit_count = 0
return ''.join(geohash)
def decode_geohash(geohash: str) -> tuple[float, float, float, float]:
"""Decode geohash to bounding box (lat_min, lat_max, lon_min, lon_max)."""
lat_range = [-90.0, 90.0]
lon_range = [-180.0, 180.0]
is_lon = True
for char in geohash:
idx = GEOHASH_CHARS.index(char.lower())
for i in range(4, -1, -1):
bit = (idx >> i) & 1
if is_lon:
mid = (lon_range[0] + lon_range[1]) / 2
if bit:
lon_range[0] = mid
else:
lon_range[1] = mid
else:
mid = (lat_range[0] + lat_range[1]) / 2
if bit:
lat_range[0] = mid
else:
lat_range[1] = mid
is_lon = not is_lon
return lat_range[0], lat_range[1], lon_range[0], lon_range[1]
def geohash_center(geohash: str) -> tuple[float, float]:
"""Get center point of geohash cell."""
lat_min, lat_max, lon_min, lon_max = decode_geohash(geohash)
return (lat_min + lat_max) / 2, (lon_min + lon_max) / 2
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.
- 8d ago First seen · 338 lines · 0 tokens per session scan A 486bad9db039
geohash-coloring 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 3,061 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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