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Trading Assistant Minimal

v3.1.0

Trading analysis system with technical indicators, signals, and position management. Read-only market data, no trade execution.

0· 32·0 current·0 all-time
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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Purpose & Capability
Declared purpose (read-only trading analysis) aligns with required pieces: python/pip and two market-data API keys (Twelve Data, Alpha Vantage). However, repository includes modules whose names imply extra capabilities (live_trading_interface.py, realtime_monitor.py, news_sentiment_monitor.py, notifications) that could go beyond strictly read-only analysis. The presence of notification defaults (Feishu chat id in DEFAULT_CONFIG) and Docker examples that mount .env files are legitimate features for a monitoring tool but expand the skill's outward-capability surface beyond pure data-read.
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Instruction Scope
SKILL.md instructs only loading API keys from environment variables and running Python analysis scripts — that matches the manifest. The instructions explicitly say no runtime .env scanning. However documentation and README also include Docker usage that mounts .env and references notification channels; and codebase contains modules that persist data (reports, accuracy logs, portfolio files) and refer to external notification endpoints (Feishu). Without reviewing the notification and live_trading modules' implementation, it's unclear whether any data (including analysis results or watchlists) may be sent to external endpoints beyond the two market-data APIs.
Install Mechanism
No custom install script; dependencies are standard Python packages (requirements.txt, e.g., requests). No third-party downloads or archive extracts are present in the skill metadata. This is a low-risk install mechanism relative to arbitrary binaries or remote extracts.
Credentials
The required environment variables (TWELVE_DATA_API_KEY, ALPHA_VANTAGE_API_KEY) are proportional to the stated purpose. There are no unexpected required credentials. That said, the codebase contains a default Feishu chat_id and references to feishu_config.json and notification channels, yet no notification credentials are declared as required env vars — this means notification configuration may live in project files rather than environment variables, which expands where secrets/config can appear and deserves review.
Persistence & Privilege
The skill does read/write within its own project directories (data/, logs/, reports/, accuracy_log.json, portfolio/). It does not request always:true or system-wide privileges. Writing to its own storage is expected for reporting and logs; users should note these files will be created in the skill folder.
What to consider before installing
This package appears to be a coherent trading analysis toolkit that legitimately needs the two market-data API keys it requests. Before installing or running it: - Inspect live_trading_interface.py, realtime_monitor.py, and news_sentiment_monitor.py to confirm they do not accept or use broker/execution credentials and that they only call the declared market-data APIs. The module name live_trading_interface is worth special review for any trade-execution logic. - Check notification/Feishu code (feishu_config.json and any send/push functions) to see whether analysis or watchlist data will be posted to external endpoints and where notification credentials are stored. The skill includes a default Feishu chat_id in config; verify whether you need to provide tokens/URLs and whether they are stored in files or environment variables. - Prefer setting API keys as environment variables (export TWELVE_DATA_API_KEY=... ) rather than creating and mounting .env files; the documentation mixes both approaches. Mounting arbitrary .env files can accidentally expose unrelated secrets if you reuse files. - Run the tool in an isolated environment (virtualenv/venv or container) and with test API keys if possible. Avoid providing any broker or trading-execution credentials unless you have audited the code paths that would use them. If you want, I can scan the contents of specific files (live_trading_interface.py, realtime_monitor.py, news_sentiment_monitor.py, any notification helper) to give a precise assessment of outbound calls and any hidden endpoints.

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.

Runtime requirements

📊 Clawdis
Binspython3, pip
EnvTWELVE_DATA_API_KEY, ALPHA_VANTAGE_API_KEY
Primary envTWELVE_DATA_API_KEY

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