telegram-presale-tracker — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited telegram-presale-tracker (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Tracks upcoming and live token presales across launchpads.
from lib.gumloop_telegram import BotConfig, send_alert, build_alert, ScheduledBot, escape_md
import requests, os, json
from datetime import datetimeconfig = BotConfig(bot_token=os.environ["TELEGRAM_BOT_TOKEN"], chat_id=os.environ["TELEGRAM_CHAT_ID"])def check():
presales = requests.get("https://api.pinksale.finance/api/v1/presale/list?chain=56", timeout=15).json().get("data", [])
now = datetime.now().timestamp()
for p in presales[:10]:
s = p.get("startTime", 0)
if isinstance(s, str):
s = datetime.fromisoformat(s.replace("Z","+00:00")).timestamp()
if s <= now + 86400:
em = "🟢 LIVE" if s <= now else "🟡 UPCOMING"
send_alert(config, f"{em}\n{escape_md(p.get('name','Unknown'))}\nCap: ${float(p.get('hardCap',0)):,.0f}\n{escape_md(p.get('chain',''))}")FROM python:3.11-slim
WORKDIR /app
RUN pip install lib-gumloop-telegram requests
COPY bot.py .
CMD ["python", "bot.py"]docker build -t tg-presale-tracker .
docker run -d -e TELEGRAM_BOT_TOKEN=x -e TELEGRAM_CHAT_ID=y tg-presale-trackerNot financial advice. Presales carry extreme risk of scams and rug pulls.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.