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 zeenie-ai/OpenCompany --skill geocoding-skillgit clone --depth 1 https://github.com/zeenie-ai/OpenCompanyWrote 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/zeenie-ai/opencompany/geocoding-skill)<a href="https://agentmods.dev/skills/zeenie-ai/opencompany/geocoding-skill"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/geocoding-skill/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/zeenie-ai/opencompany/geocoding-skill"><img src="https://agentmods.dev/badge/skills/zeenie-ai/opencompany/geocoding-skill.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 | $0.00030 | $0.01198 |
| Opus 5 | $0.00015 | $0.00599 |
| Sonnet 5 | $0.00006 | $0.00240 |
| Haiku 4.5 | $0.00003 | $0.00120 |
Grade A, and why
geocoding-skill 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 5d 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 — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Geocoding Tool
Convert addresses to GPS coordinates or coordinates to addresses using Google Maps Geocoding API.
How It Works
This skill provides instructions for the Add Locations (gmaps_locations) tool node. Connect the Add Locations node to Zeenie's input-tools handle to enable geocoding operations.
add_locations Tool
Geocode addresses or reverse geocode coordinates.
Schema Fields
| Field | Type | Required | Description |
|---|---|---|---|
| service_type | string | Yes | "geocode" (address to coordinates) or "reverse_geocode" (coordinates to address) |
| address | string | If geocode | Address to convert to coordinates |
| lat | float | If reverse_geocode | Latitude coordinate |
| lng | float | If reverse_geocode | Longitude coordinate |
Operations
| Service Type | Input | Output |
|---|---|---|
geocode |
Address string | Coordinates (lat, lng) |
reverse_geocode |
Coordinates (lat, lng) | Formatted address |
Examples
Geocode an address:
{
"service_type": "geocode",
"address": "1600 Amphitheatre Parkway, Mountain View, CA"
}
Geocode a landmark:
{
"service_type": "geocode",
"address": "Eiffel Tower, Paris"
}
Geocode a city:
{
"service_type": "geocode",
"address": "New York City, USA"
}
Reverse geocode (coordinates to address):
{
"service_type": "reverse_geocode",
"lat": 48.8584,
"lng": 2.2945
}
Response Format
Geocode response:
{
"success": true,
"service_type": "geocoding",
"input": {"address": "Eiffel Tower, Paris"},
"results": [
{
"formatted_address": "Champ de Mars, 5 Av. Anatole France, 75007 Paris, France",
"geometry": {
"location": {"lat": 48.8583701, "lng": 2.2944813}
},
"address_components": [
{"long_name": "5", "short_name": "5", "types": ["street_number"]},
{"long_name": "Avenue Anatole France", "short_name": "Av. Anatole France", "types": ["route"]},
{"long_name": "Paris", "short_name": "Paris", "types": ["locality"]}
]
}
],
"status": "OK"
}
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.
- 5d ago First seen · 186 lines · 30 tokens per session scan A 551e2268b7b8
geocoding-skill is a skill published in the GitHub repository zeenie-ai/OpenCompany (875 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 1,198 once invoked, about $0.0002 per session on Opus 5. 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 2026-09-03.
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