How does the Pre-Trade Risk Auditor define 'risk' when evaluating a trade plan?

The auditor focuses on 'Total Heat'—calculating the exact dollar amount lost if every stop loss in your plan is hit simultaneously—helping you avoid catastrophic account drawdown.

What specific data do I need to provide for the tool to audit my trades?

You need a CSV file with five required columns: symbol, direction, entry, stop, and size; you can optionally include targets and sector labels for more advanced concentration analysis.

Does this tool automatically sync with my live brokerage account to see my current open positions?

No, the auditor prices a specific plan in isolation; to include open positions in the risk calculation, simply list them alongside your planned trades in your CSV input.

Can I integrate this auditor into an automated AI trading agent workflow?

The skill is a standalone Python-based utility that outputs results to your console or as JSON, making it compatible with any AI agent or workflow capable of executing shell scripts.

What components are included in the purchase of this skill?

You receive the core Python auditing engine, a sample trade plan for testing, and a comprehensive reference guide explaining the logic behind each of the seven risk thresholds.

Is it possible to customize the risk limits, such as the maximum allowable sector concentration?

While limits like the 2% position cap are pre-set based on industry standards, you can manually adjust these constants at the top of the script to align with your personal risk tolerance.

About this skill

Pre-Trade Risk Auditor™ v1.0.0

Prices a set of planned trades before any of them is sent. Answers one question first: if every stop is hit, what does this plan cost?

Seven rules in four families — Heat, Exposure, Asymmetry, Thesis. No forecasts, no signals, no instrument picks.

Run it in ten seconds

python3 scripts/check_plan.py

No arguments prices the bundled sample on a 100,000 account and labels it a demonstration.

Run it on your plan

python3 scripts/check_plan.py my-plan.csv --account 250000
python3 scripts/check_plan.py my-plan.csv --account 250000 --json

Required columns: symbol, direction, entry, stop, size Optional: target (reward:risk), sector (concentration, correlation), note (rationale)

The rules

| ID | Rule | Default limit | |---|---|---| | R1 | Oversized position | risk > 2% of account | | R2 | Total heat | combined risk > 6% | | R3 | Concentration | > 40% of risk in one sector | | R4 | Thin payoff | reward:risk < 1.5 | | R5 | Inverted stop | stop on the profitable side — BLOCK | | R6 | Correlated pair | same-direction positions in one sector | | R7 | Missing rationale | blank, or a reactive note |

Every limit has a written reason in references/risk-thresholds.md, and every constant is at the top of scripts/check_plan.py. Change a number deliberately rather than arguing with a verdict.

Verdicts

BLOCK → DO NOT SEND · HIGH → RESIZE BEFORE SENDING · MEDIUM → SEND WITH THE TRADE-OFF NAMED · none → WITHIN PLAN

What it does not know

Real correlation (sector is a label you supply), volatility, your existing open book unless you include it, and whether any of it will work. It prices the plan. It does not judge it.

Pairs with

Trade Post-Mortem Engine™ — the same discipline after the trades close. One prices the commitment, the other audits the execution.

Verified

monna-verify v1.0.0 · 2026-08-22 · CLEAN · 30/30 · 0 blockers · 0 fails · 0 AI-language hits. Scanned by Skill Security Auditor™: CLEAR.

Disclaimer

For educational and self-review use. Not financial, investment, or tax advice. The author is not a licensed advisor. Trading carries risk of loss.

Frequently Asked Questions

pretrade risk auditor