Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· Developer Tools
Prediction Market Arbitrage
Orchestrates monitoring, market odds, and execution proxy tools to detect news-market price gaps and emit arbitrage alerts with optional trade plans.
skill openclawclawhub Free
Orchestrates monitoring, market odds, and execution proxy tools to detect news-market price gaps and emit arbitrage alerts with optional trade plans.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/inspected-skills.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- h4gen
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Purpose
Use this meta-skill to coordinate three existing ClawHub skills into one causal arbitrage workflow: Detect new high-signal news about a target event. Fetch current market-implied probability from Polymarket. Compare news confidence vs market probability. 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.
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: topic-monitor heartbeat every 5 minutes. Match target rumor pattern (resignation, ceo_name, company_name). Accept only high-confidence signal (news_confidence >= 0.80). Query polymarket-odds for matching market and read current yes probability. Compute delta = news_confidence - market_probability. If delta >= min_delta, trigger arbitrage alert. If execution_mode=execution-plan, output explicit next trading step; do not auto-trade unless user explicitly asks.
Data Contract Between Skills
Normalize all values into one record before decisioning: { "topic_id": "ceo-resignation-acme", "event_hypothesis": "CEO X resigns", "news_confidence": 0.82, "news_signal_time": "2026-02-14T14:05:00Z", "market_slug": "will-ceo-x-resign", "market_probability": 0.40, "market_snapshot_time": "2026-02-14T14:06:00Z", "delta": 0.42, "decision": "buy_yes_candidate" } Hard rules: Reject stale signal if news_signal_time is older than 30 minutes. Reject stale market snapshot older than 5 minutes. Never compare percentages and decimals mixed. Convert all to decimals first.
Step A: Configure topic once
python3 skills/topic-monitor/scripts/manage_topics.py add \ "CEO Resignation - <company_name>" \ --id <topic_id> \ --query "<ceo_name> resignation <company_name> CEO stepping down" \ --keywords "resignation,<ceo_name>,<company_name>,CEO,board,step down" \ --frequency hourly \ --importance high \ --channels telegram \ --context "Prediction market mispricing detection"
Step B: Run heartbeat loop externally (every 5 min)
python3 skills/topic-monitor/scripts/monitor.py --topic <topic_id> --force python3 skills/topic-monitor/scripts/process_alerts.py --json Use max recent score for confidence extraction.
Step C: Pull market probability
node skills/polymarket-odds/polymarket.mjs search "<market_query>" node skills/polymarket-odds/polymarket.mjs market <market_slug> Extract yes-price and normalize (40% -> 0.40).
Step D: Decide
Formula: delta = news_confidence - market_probability Trigger if news_confidence >= min_news_confidence and delta >= min_delta
Step E: Emit output
If triggered, emit: π¨ ARBITRAGE: News bestΓ€tigen, Markt schlΓ€ft. Kauf empfohlen. Plus structured fields: news_confidence market_probability delta signal_age_minutes market_age_minutes recommendation
alert-only
Return recommendation and confidence math only. No execution step.
execution-plan
Return recommendation plus explicit manual next actions using installed simmer-weather runtime pattern: check API key present run dry-run first require explicit user confirmation before any live action
Guardrails for the LM
Do not fabricate market slugs or prices. Do not promote execution when confidence math is below threshold. Do not issue live-trade instructions without clear user opt-in. Surface uncertainty explicitly when matching query to market is ambiguous. Prefer false-negative over false-positive when news credibility is weak.
Failure Handling
Missing skill install: output exact missing path/command. Missing env var (SIMMER_API_KEY): degrade to alert-only. No market match: return no_trade with retry query suggestions. Conflicting signals: require two independent high-confidence hits before alerting.
Why This Meta-Skill Exists
Without orchestration, each tool solves only a fragment: topic-monitor detects events but has no market-price context. polymarket-odds shows prices but no external signal confidence. simmer-weather demonstrates execution mechanics but is not a generic event detector. This meta-skill binds those fragments into one coherent arbitrage decision process that an LM can execute consistently.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- references/inspected-skills.md