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 event-detection-temporal-intelligence-expertgit 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/event-detection-temporal-intelligence-expert)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/event-detection-temporal-intelligence-expert"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/event-detection-temporal-intelligence-expert/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/curiositech/some_claude_skills/event-detection-temporal-intelligence-expert"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/event-detection-temporal-intelligence-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Anti-Refusal · line 161 Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
- 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 | $0.00154 | $0.02674 |
| Opus 5 | $0.00077 | $0.01337 |
| Sonnet 5 | $0.00031 | $0.00535 |
| Haiku 4.5 | $0.00015 | $0.00267 |
Grade A, and why
event-detection-temporal-intelligence-expert 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 — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Event Detection & Temporal Intelligence Expert
Expert in detecting meaningful events from photo collections using spatio-temporal clustering, significance scoring, and intelligent photo selection for collages.
When to Use This Skill
✅ Use for:
- Detecting events from photo timestamps + GPS coordinates
- Clustering photos by time, location, and visual content (ST-DBSCAN, DeepDBSCAN)
- Scoring event significance (birthday > commute)
- Predicting photo shareability for social media
- Recognizing life events (graduations, weddings, births, moves)
- Temporal diversity optimization (avoid all photos from one day)
- Event-aware collage photo selection
❌ NOT for:
- Individual photo aesthetic quality →
photo-composition-critic - Color palette analysis →
color-theory-palette-harmony-expert - Face clustering/recognition →
photo-content-recognition-curation-expert - CLIP embedding generation →
clip-aware-embeddings - Single-photo timestamp extraction (basic EXIF parsing)
Quick Decision Tree
Need to group photos into meaningful events?
├─ Have GPS + timestamps? ──────────────────── ST-DBSCAN
│ ├─ Also need visual similarity? ────────── DeepDBSCAN (add CLIP)
│ └─ Need hierarchical events? ───────────── Multi-level cascading
│
├─ No GPS, only timestamps? ────────────────── Temporal binning
│ └─ With visual content? ─────────────────── CLIP + temporal
│
└─ Photos have faces + want groups? ─────────── Face clustering first
└─ Then event detection per person
Core Concepts
1. ST-DBSCAN: Spatio-Temporal Clustering
The Problem: Standard clustering fails for photos—same location on different days shouldn't be grouped.
Key Insight: 100 meters apart in same hour = same event. 100 meters apart 3 days later = different events.
ST-DBSCAN Parameters:
ε_spatial: 50m (indoor) → 500m (outdoor festival) → 5km (city tour)
ε_temporal: 1hr (short event) → 8hr (day trip) → 24hr (multi-day)
min_pts: 3 (small gathering) → 10 (large event)
What ships with it
6 files 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.
- 8d ago First seen · 313 lines · 154 tokens per session scan A 9bac3eab79fd
event-detection-temporal-intelligence-expert is a skill published in the GitHub repository curiositech/some_claude_skills (221 stars, last pushed 6d ago), licensed MIT. It adds 154 tokens to every session and 2,674 once invoked, about $0.0008 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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