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 curiositech/some_claude_skills --skill large-scale-map-visualizationgit clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote 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/curiositech/some_claude_skills/large-scale-map-visualization)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/large-scale-map-visualization"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/large-scale-map-visualization.svg" alt="Measured on agentmods" 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 | $0.00053 | $0.04384 |
| Opus 5 | $0.00026 | $0.02192 |
| Sonnet 5 | $0.00011 | $0.00877 |
| Haiku 4.5 | $0.00005 | $0.00438 |
Grade A, and why
large-scale-map-visualization 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 4d 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 — 561 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Large-Scale Map Visualization Expert
Master of high-performance web map implementations handling 5,000-100,000+ geographic data points. Specializes in Leaflet.js optimization, spatial clustering algorithms, viewport-based loading, and progressive disclosure UX patterns for map-based applications.
Activation Triggers
Activate on: "map performance", "too many markers", "slow map", "clustering", "10k points", "marker clustering", "leaflet performance", "spatial visualization", "geospatial clustering", "viewport loading", "map data optimization", "real-time map", "Supercluster", "marker cluster"
NOT for: Static map images (use Mapbox/Google Static) | 3D visualizations (use Maplibre GL) | Non-geographic data visualization (use D3.js/Chart.js) | Simple maps with <100 markers (vanilla Leaflet is fine)
Core Expertise
Performance Architecture
┌─────────────────────────────────────────────────────────────┐
│ MAP PERFORMANCE TIERS │
├─────────────────────────────────────────────────────────────┤
│ │
│ 0-100 markers → Vanilla Leaflet (no optimization) │
│ 100-1,000 → Basic clustering (react-leaflet-cluster)│
│ 1,000-10,000 → Supercluster + viewport loading │
│ 10,000-50,000 → Supercluster + canvas + sampling │
│ 50,000-500,000 → Web Workers + server-side clustering │
│ 500,000+ → MVT tiles + backend pre-aggregation │
│ │
└─────────────────────────────────────────────────────────────┘
Technology Stack Decisions
| Use Case | Best Library | Why |
|---|---|---|
| React + <5k points | react-leaflet-cluster |
Simple drop-in, wraps Leaflet.markercluster |
| React + 5-50k points | use-supercluster hook |
3-5x faster, viewport-aware, GeoJSON native |
| React + 50k+ points | supercluster + Web Workers |
Offload clustering to background thread |
| Static sites | Server-side clustering | Pre-compute at build time |
| Real-time updates | Canvas renderer + sampling | Minimize DOM manipulation |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 561 lines · 53 tokens per session scan A a7de2ae82660
large-scale-map-visualization is a skill published in the GitHub repository curiositech/some_claude_skills (214 stars, last pushed yesterday), licensed MIT. It adds 53 tokens to every session and 4,384 once invoked, about $0.0003 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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