theaisingularity/hermesclaw/market-alerts

Claude Code and agent skill by theaisingularity/hermesclaw

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Market price monitoring and alerts — checks your watchlist against thresholds, sends Telegram alerts on breaches, generates daily pre-market briefings, and tracks trade notes in memory

Install

npx vskill@latest install theaisingularity/hermesclaw/market-alerts

SKILL.md

market-alerts

This skill monitors your watchlist for price threshold breaches, sends Telegram alerts, and generates daily pre-market briefings. Trade notes and strategy observations are stored in MEMORY.md for future reference.

When to invoke

  • On a cron schedule during market hours (every 15 minutes, 9:30am–4pm ET)
  • For daily pre-market briefing (9:25am ET weekdays)
  • When the user explicitly asks to check their watchlist
  • When the user wants to record a trade note

Steps to execute

Mode 1: Real-time monitoring check (cron)
  1. Load watchlist and thresholds from memory
  • Read MEMORY.md for: ticker symbols, alert thresholds (high/low per ticker), alert preferences
  • If no watchlist is configured, ask the user to set one before proceeding
  1. Fetch current prices
  • Use web_extract to get current prices for each ticker
  • Preferred sources: finance.yahoo.com, Google Finance, or similar public price feeds
  • Use scripts/monitor.py to parse price data and compute threshold status
  1. Check thresholds
  • For each ticker: compare current price to high and low thresholds
  • A breach = price is above high threshold OR below low threshold
  1. Send Telegram alert on breach
  • Alert format: see Output Format section below
  • Include: ticker, current price, threshold breached, % from threshold, relevant context from MEMORY.md (e.g., "your thesis was X", "last time this happened Y")
  • Do NOT send duplicate alerts for the same breach within 60 minutes (track in memory)
  1. Update memory
  • Record last check timestamp and prices in MEMORY.md
  • Track breach history
Mode 2: Pre-market briefing
  1. Fetch pre-market prices for all watchlist tickers
  2. Fetch overnight/morning news relevant to each ticker (via web_search)
  3. Check MEMORY.md for any open position notes or pending thesis items
  4. Generate structured briefing (see Output Format)
  5. Send to Telegram
Mode 3: Record trade note

When the user says "record trade" or "save my thesis":

  1. Extract: ticker, direction (long/short), entry price, thesis, target, stop
  2. Save to MEMORY.md under "Trade journal"
  3. Confirm to user

Output format

Threshold breach alert:

ALERT — [TICKER] [direction] breach
[TIME]
[TICKER]: $[PRICE] ([+/-]%% from threshold)
Your [high/low] threshold: $[THRESHOLD]
From your notes: [relevant trade context from MEMORY.md, if any]
RSI/momentum context: [brief technical note from web data if available]

Pre-market briefing:

Pre-market — [DATE] [TIME]
[TICKER]: $[PRE-MKT PRICE] ([+/-]%% vs yesterday)
Context: [1-line news or catalyst]
[TICKER]: ...
Open positions from your notes:
• [TICKER] long entry $[X] — [brief thesis]
Today's macro: [1-2 sentences on scheduled events: FOMC, jobs data, earnings]

Trade note confirmation:

Trade recorded:
[TICKER] [LONG/SHORT] | Entry: $[X] | Target: $[Y] | Stop: $[Z]
Thesis: [summary]

Error handling

  • If price fetch fails for a ticker: skip it, note in output, retry next cycle
  • If Telegram delivery fails: save alert to /sandbox/alert-[timestamp].txt
  • If all price sources are unreachable: log the failure and stop the cron check gracefully

Notes

  • This skill is for monitoring and analysis only — it does not place orders
  • Never store API keys or brokerage credentials in memory
  • The scripts/monitor.py helper handles price parsing and threshold comparison as JSON — no fragile string parsing in the LLM
  • After 3 months of use, Hermes will auto-create a personalized MarketAlert skill that knows your trading style and typical reaction patterns

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
70
Repository forks
10
7-day trend score
21

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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