trade-memorySave a trade or signal event to local memory log file (trades.jsonl). Use when a trade signal is confirmed and needs to be recorded, saved, or logged for fut...
Install via ClawdBot CLI:
clawdbot install newbienodes/trade-memoryGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 21, 2026
Traders use this skill to automatically log confirmed buy or sell signals from technical analysis tools like btc-analyzer into a persistent JSONL file. It ensures all trade decisions are recorded for backtesting and performance review, helping maintain a disciplined trading history.
Retail investors manually input trade details such as entry price, stop loss, and take profit after executing trades on exchanges. The skill saves these entries locally, allowing users to track their portfolio and analyze past trades without relying on external platforms.
Trading firms or analysts aggregate signals from various sources like Telegram bots, manual inputs, and automated scanners. This skill consolidates all signals into a single JSONL log file, enabling centralized monitoring and reducing data fragmentation across different tools.
In trading courses or simulators, students practice recording hypothetical trades to learn risk management and journaling. The skill provides a simple way to log simulated trades, helping learners build habits of tracking entries, exits, and reasoning behind each decision.
Professional traders use this skill to maintain a local audit trail of all trade signals and executions, which can be exported for regulatory compliance checks. It ensures transparency and accountability by timestamping each entry and storing it in an immutable JSONL format.
Offer this skill as a free feature within a larger trading platform, with premium upgrades for advanced analytics on the logged trades. Revenue comes from subscription fees for enhanced backtesting, AI insights, or cloud storage of trade histories.
License the skill's underlying technology to financial institutions or trading firms as an API, allowing them to integrate trade logging into their proprietary systems. Revenue is generated through one-time licensing fees or annual contracts based on usage volume.
Collect anonymized trade data from users (with consent) to provide aggregated market insights and benchmarking reports. Revenue comes from selling these analytics to hedge funds, researchers, or media outlets interested in trading trends and behaviors.
💬 Integration Tip
Ensure the Python script is accessible and the trades.jsonl file path is correctly configured in the workspace to avoid permission errors during logging.
Scored Jun 19, 2026
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