Argus Edge — Prediction Market Betting Engine
v1.0.0Argus-style prediction market edge detection and betting strategy. Computes expected value from TA-implied probability vs market odds, sizes bets via Kelly c...
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name/description (Argus-style prediction-market betting strategy) matches the SKILL.md content (edge calculation, Kelly sizing, freshness/consensus rules). No unrelated credentials, binaries, or installs are requested.
Instruction Scope
The SKILL.md contains formulas, rules, and usage examples but no concrete implementation steps for obtaining market data or placing bets (no API endpoints, no commands). That makes the instructions intentionally high-level: coherent for a strategy doc, but it grants broad discretion to the agent to fetch market data or interact with exchanges if the agent is given such capabilities elsewhere.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing will be written to disk or installed by this skill itself.
Credentials
No environment variables, credentials, or config paths are requested. The skill does not ask for unrelated secrets or system access.
Persistence & Privilege
always:false (default) and normal autonomous invocation permitted. The skill does not request elevated persistence or modify other skills or agent-wide settings.
Assessment
This skill is essentially a strategy document — it doesn't install code or request credentials, so it's coherent with its stated purpose. Before using it: (1) recognize the win-rate/validation claims are unverifiable from the SKILL.md alone; treat them skeptically. (2) The skill does not provide market-data sources or execution instructions, so an agent using it will need to fetch market quotes and/or place bets — ensure the agent does not have API keys, exchange credentials, or automated trading permissions you don't intend it to use. (3) If you plan to implement these rules programmatically, validate with small, non-production stakes first and add safeguards (rate limits, bankroll caps, explicit confirmation before placing real bets). (4) If you want a fully-automated tool, insist on concrete data-source and execution steps (APIs, authentication model) before granting any credentials.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.