Trading-Journal-AI: Local-first AI trading journal

by simonro · Claude Skill · ★ 97

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 69/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

anthropicclaudeclaude-codeday-tradingfastapiinteractive-brokerslocal-firstpythonreactself-hosted

Quick Facts

Stars97
Forks42
LanguageJavaScript
CategoryClaude Skill
LicenseMIT
Quality Score69/100
Open Issues11
Last Updated2026-11-05
Created2026-09-06
Platformsclaude-code, node
Est. Tokens~17k

About Trading-Journal-AI

Trading Journal AI A trading journal that runs on your own machine. Import your broker's CSV and it rebuilds your round-trip trades, tracks the numbers that matter (win rate, profit factor, expectancy, drawdown, MFE/MAE, exit efficiency), and, if you want it to, uses Claude to read your trading diary and grade your days on process. Your data stays on your computer.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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