Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add agiprolabs/claude-trading-skills --skill trade-journalgit clone --depth 1 https://github.com/agiprolabs/claude-trading-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agiprolabs/claude-trading-skills/trade-journal)<a href="https://agentmods.dev/skills/agiprolabs/claude-trading-skills/trade-journal"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/trade-journal/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agiprolabs/claude-trading-skills/trade-journal"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/trade-journal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.02699 |
| Opus 5 | $0.00010 | $0.01350 |
| Sonnet 5 | $0.00004 | $0.00540 |
| Haiku 4.5 | $0.00002 | $0.00270 |
Grade A, and why
trade-journal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trade Journal
Structured trade journaling for systematic improvement. Log every trade with context, review performance at multiple cadences, detect behavioral patterns that destroy edge, and attribute returns to specific strategies.
Why Journaling Matters
Most traders fail not from bad strategies but from bad behavior. A trade journal transforms subjective "feel" into objective data:
- Strategy Attribution: Know which setups actually make money vs. which feel profitable
- Behavioral Detection: Catch revenge trading, FOMO entries, and premature exits before they compound
- Pattern Recognition: Discover that your Monday morning trades lose money, or that you cut SOL winners too early
- Accountability: Written rationale before entry forces deliberate decision-making
- Improvement Tracking: Measure whether changes to your process actually improve results
Without a journal, you optimize on noise. With one, you optimize on signal.
Trade Record Structure
Every trade record captures context at entry and outcome at exit. See references/record_format.md for the complete 18-field schema.
Minimum Required Fields
trade = {
"id": "T-20250310-001",
"token": "SOL",
"direction": "long",
"entry_date": "2025-03-10T14:30:00Z",
"entry_price": 142.50,
"size_sol": 5.0,
"strategy": "momentum-breakout",
"rationale": "Breaking above 4h resistance at 141.80 with volume confirmation",
"exit_date": "2025-03-10T16:45:00Z",
"exit_price": 146.20,
"pnl_sol": 0.648,
"outcome": "win",
"lessons": "Held through initial pullback to 143.0, rewarded for patience"
}
Strategy Tagging
Use consistent tags to enable performance attribution:
| Category | Tags |
|---|---|
| Momentum | momentum-breakout, trend-continuation, pullback-entry |
| Mean Reversion | range-fade, oversold-bounce, deviation-snap |
| Event-Driven | listing-play, catalyst-trade, news-reaction |
| On-Chain | whale-follow, wallet-copy, flow-signal |
| DeFi | lp-entry, yield-farm, arb-capture |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 302 lines · 21 tokens per session scan A 062e245fcc24
trade-journal is a skill published in the GitHub repository agiprolabs/claude-trading-skills (356 stars, last pushed 9d ago), licensed MIT. It adds 21 tokens to every session and 2,699 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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