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 terrylica/cc-skills --skill exchange-session-detectorgit clone --depth 1 https://github.com/terrylica/cc-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/terrylica/cc-skills/exchange-session-detector)<a href="https://agentmods.dev/skills/terrylica/cc-skills/exchange-session-detector"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/exchange-session-detector/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/terrylica/cc-skills/exchange-session-detector"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/exchange-session-detector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Rogue Agent · line 185 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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 | $0.00032 | $0.02366 |
| Opus 5.5 | $0.00013 | $0.00946 |
| Sonnet 5.5 | $0.00006 | $0.00473 |
| Haiku 4.5 | $0.00003 | $0.00237 |
Grade A, and why
exchange-session-detector 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 22d 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exchange Session Detector
Production-grade pattern for detecting exchange trading sessions with full DST, holiday, and lunch break support. Validated in exness-data-preprocess across 10 global exchanges.
Self-Evolving Skill: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.
When to Use
- Adding session flags (is_nyse_session, is_lse_session, etc.) to time-series DataFrames
- Detecting whether a timestamp falls within trading hours for any major exchange
- Checking for holidays (NYSE, LSE, or "major" when both are closed)
- Handling lunch breaks for Asian exchanges (Tokyo, Hong Kong, Singapore)
- Upgrading from simplified hour-range checks to production accuracy
- Building ClickHouse materialized columns for session classification
Architecture Overview
ExchangeConfig registry (exchanges.py) SessionDetector (session_detector.py)
┌──────────────────────────────────┐ ┌──────────────────────────────────────┐
│ 10 frozen dataclasses │ │ Wraps exchange_calendars library │
│ ISO 10383 MIC codes │─────▶│ Pre-computes trading minutes (sets) │
│ IANA timezones for DST │ │ Vectorized .isin() lookup (2.2x) │
│ Local open/close hours │ │ Holiday detection (NYSE + LSE) │
└──────────────────────────────────┘ └──────────────────────────────────────┘
Quick Start
import exchange_calendars as xcals
import pandas as pd
# Single-exchange check
cal = xcals.get_calendar("XNYS") # NYSE via ISO 10383 MIC
cal.is_open_on_minute(pd.Timestamp("2024-07-04 14:30", tz="UTC")) # False (July 4th)
cal.is_open_on_minute(pd.Timestamp("2024-07-05 14:30", tz="UTC")) # True
# Full session detection across 10 exchanges
from session_detector import SessionDetector
detector = SessionDetector()
df = detector.detect_sessions_and_holidays(dates_df)
# Adds: is_us_holiday, is_uk_holiday, is_major_holiday, is_{exchange}_session
What ships with it
4 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.
- 22d ago Changed cb941337bc64
- 1mo ago First seen · 188 lines · 32 tokens per session scan A a65ebd1f0702
exchange-session-detector is a skill published in the GitHub repository terrylica/cc-skills (1 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 2,366 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-05.
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