Finml Toolkit

A curated list of practical financial machine learning tools and applications. financial machine learning, python, algorithmic-trading, cryptocurrency.

Security Scan

The skill is a small, self-contained logging/utility script that matches its description and has no network calls or unrelated credential requests.

Purpose & Capability

Name/description claim a curated financial-ML toolkit; included shell script implements a local logging/tracking utility for run/check/convert/analyze/etc. The requested resources (none) align with that purpose.

Instruction Scope

SKILL.md and the script direct all activity to a local data directory (~/.local/share/finml-toolkit by default). There are no commands that read unrelated system files, call external endpoints, or request credentials. Note: the tool records raw user inputs into log files and history.log — so any sensitive strings provided as command arguments will be stored locally.

Install Mechanism

No install spec — instruction-only. A shell script is included in the package but there is no download-from-URL or package installer. The only disk writes occur when the script is run and it creates its own data directory under the user's home.

Credentials

The skill declares no required environment variables or credentials. SKILL.md mentions an optional FINML_TOOLKIT_DIR to change the data directory (reasonable). The script relies on HOME (normal) but does not access unrelated secret env vars.

Persistence & Privilege

always:false and no modifications to other skills or system-wide configs. The script persists logs to its own directory only when executed — no privileged or persistent background components are requested.

Assessment

This appears to be a simple local logging utility matching its description. Before running: (1) review the included script (it will create ~/.local/share/finml-toolkit by default and append any arguments you pass to log files and history.log); (2) avoid passing secrets or API keys as command arguments (they will be stored in plaintext in logs); (3) if you prefer isolation, set FINML_TOOLKIT_DIR to a sandbox directory or inspect/modify the script to meet your needs; (4) note minor bugs/quirks (e.g., JSON export uses naive formatting and may not escape quotes properly). If you want networked features or integrations, ask the author for justification and code/endpoint details before enabling.

A utility toolkit for logging, tracking, and managing financial ML operations. Each command records timestamped entries to its own log file for auditing and review.

Commands

Core Operations

Command	Description
run <input>	Log a run entry (view recent entries if no input given)
check <input>	Log a check entry for verification tasks
convert <input>	Log a convert entry for format conversion tasks
analyze <input>	Log an analyze entry for analysis tasks
generate <input>	Log a generate entry for generation tasks
preview <input>	Log a preview entry for preview tasks
batch <input>	Log a batch entry for batch processing tasks
compare <input>	Log a compare entry for comparison tasks
export <input>	Log an export entry for export tasks
config <input>	Log a config entry for configuration tasks
status <input>	Log a status entry for status tracking
report <input>	Log a report entry for reporting tasks

Utility Commands

Command	Description
stats	Show summary statistics across all log files
export <fmt>	Export all data in json, csv, or txt format
search <term>	Search all log entries for a term (case-insensitive)
recent	Show the 20 most recent entries from history
status	Health check — version, data dir, entry count, disk usage
help	Show available commands
version	Show version (v2.0.0)

Data Storage

All data is stored in ~/.local/share/finml-toolkit/:

• Each command writes to its own log file (e.g., run.log, check.log, analyze.log)
• All actions are also recorded in history.log with timestamps
• Export files are written to the same directory as export.json, export.csv, or export.txt
• Log format: YYYY-MM-DD HH:MM|<input> (pipe-delimited)

Requirements

• Bash (no external dependencies)
• Works on Linux and macOS

When to Use

• When you need to log and track financial ML operations over time
• To maintain an audit trail of run, check, convert, analyze, or generate actions
• When you want to search or export historical operation records
• For batch tracking of ML processing pipelines
• To compare and report on financial data processing tasks
• When managing configurations for finml workflows

Examples

# Log operations
finml-toolkit run "backtest strategy alpha-3"
finml-toolkit check "validate portfolio weights"
finml-toolkit convert "csv to parquet format"
finml-toolkit analyze "correlation matrix on sector data"
finml-toolkit generate "monthly performance report"
finml-toolkit batch "process all Q4 earnings files"
finml-toolkit compare "strategy A vs strategy B returns"
finml-toolkit config "set risk_threshold=0.05"

# View recent entries for a command (no args)
finml-toolkit run
finml-toolkit analyze

# Search and export
finml-toolkit search "portfolio"
finml-toolkit export json
finml-toolkit stats
finml-toolkit recent
finml-toolkit status

Configuration

Set FINML_TOOLKIT_DIR environment variable to change the data directory. Default: ~/.local/share/finml-toolkit/

Output

All commands output to stdout. Redirect with finml-toolkit run > output.txt.

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