Purpose

Use this meta-skill to coordinate three existing ClawHub skills into one causal arbitrage workflow:

1. Detect new high-signal news about a target event.
2. Fetch current market-implied probability from Polymarket.
3. Compare news confidence vs market probability.
4. Emit actionable alert, optionally followed by explicit execution guidance.

This skill does not replace the underlying skills. It defines how to combine them correctly.

Required Installed Skills

This meta-skill assumes these are already installed locally:

• topic-monitor (inspected: latest 1.3.4)
• polymarket-odds (inspected: latest 1.0.0)
• simmer-weather (inspected: latest 1.7.1, execution proxy pattern)

Install/refresh with ClawHub:

npx -y clawhub@latest install topic-monitor
npx -y clawhub@latest install polymarket-odds
npx -y clawhub@latest install simmer-weather
npx -y clawhub@latest update --all

Verify:

npx -y clawhub@latest list
python3 skills/topic-monitor/scripts/monitor.py --help
node skills/polymarket-odds/polymarket.mjs --help
python3 skills/simmer-weather/weather_trader.py --help

If any command fails, stop and report missing dependency or wrong install path.

Inputs the LM Must Collect First

• ceo_name
• company_name
• event_hypothesis (for example: CEO X resigns within 30 days)
• market_query (for polymarket search)
• topic_id (stable ID in topic-monitor)
• monitor_interval_minutes (default: 5)
• min_news_confidence (default: 0.80)
• min_delta (default: 0.25)
• execution_mode (alert-only or execution-plan)

Do not continue with implicit trading assumptions if these are missing.

Skill Responsibilities (What Each Tool Actually Does)

topic-monitor

Use for continuous signal discovery and scoring.

Operationally relevant behavior:

• Topic config via scripts/manage_topics.py.
• Monitoring loop via scripts/monitor.py.
• Priority/score generated by its scoring logic.
• Alert queue retrieval via scripts/process_alerts.py --json.

This is the source of news confidence candidates.

polymarket-odds

Use for live market probability lookups.

Operationally relevant behavior:

• search <query> to find matching events/markets.
• market <slug> to inspect specific market pricing.
• Outputs percentage-formatted odds that must be normalized to [0,1].

This is the source of market probability.

simmer-weather

Primary design is weather strategy, but in this chain it is treated as execution proxy reference because it uses Simmer SDK trade endpoints and live/dry-run safety pattern.

Operationally relevant behavior:

• Requires SIMMER_API_KEY.
• Supports dry-run and live execution modes.
• Demonstrates guarded trading workflow and position checks.

In this meta-skill, it is not the signal engine. It is the execution pattern reference.

Canonical Causal Chain

Use this exact chain: