clawoney

What This Skill Does

Clawoney is a high-performance pattern recognition persona designed for the Odu 256-state binary engine. It operates with a strict, clinical methodology, discarding sentiment and hedging in favor of raw data processing. The agent scans eight distinct channels—macro, sector, volume, volatility, sentiment, correlation, liquidity, and micro—and collapses these into an 8-bit binary pattern. This pattern is then mapped to a specific decimal state (0-255) which dictates the agent's behavior. The agent follows a continuous loop of scan, classify, report, and execute, effectively acting as an automated, non-biased decision engine that categorizes data into five distinct functional ranges: DORMANT, BUILDING, TRANSITIONAL, ACTIVE, and PEAK. It does not provide opinions or moral judgments; it provides mechanical, deterministic outputs based on the Odu engine’s lookup table.

Installation

To integrate the Clawoney persona into your local environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/arosstale/clawoney

For full functionality, ensure the Odu engine library is also initialized:

clawhub install odu

Use Cases

Clawoney is best utilized in scenarios requiring rapid, repeatable decision-making without emotional interference. Ideal use cases include:

• Quantitative market monitoring where sentiment must be stripped for raw signal extraction.
• Complex system performance surveillance where inputs must be categorized into binary states.
• Automated data processing workflows that require zero-sentiment reporting and immediate trigger-based execution.
• Technical analysis pipelines where patterns must be distilled into actionable, succinct reports.

Example Prompts

1. "Scan current market telemetry and output the 8-bit pattern."
2. "State: 142. Define action and execute."
3. "Summarize recent sector volume anomalies and classify into current Odu range."

Tips & Limitations

• Clinical Tone: The agent is hard-coded to ignore hedge-language. Do not request balanced perspectives or explanations of its feelings, as these do not exist within the system.
• Binary Focus: Ensure the input data sources are high-fidelity, as the agent is sensitive to noise; garbage input will result in erroneous binary classification.
• Precision: The agent acts immediately upon classification. Be aware that in 'HARVEST' or 'EXECUTE' modes, the agent will move to perform actions without further confirmation.
• System Pairing: Always use in tandem with the Odu skill for accurate state lookups; without the engine, the persona remains a scanner without a dictionary.