Agent setup
Use the agent-rule pages when the task is to define how a simulated trading agent should behave before any result exists.
Use these workflows to turn simulated trading into a repeatable operating loop: write the agent rules, check the planned entry, review paper risk, record the exit, and feed one clear improvement back into the next sample.
| Step | Owner page | Review output |
|---|---|---|
| 1. Define the agent | AI trading agent rules | Persona, market scope, cadence, setup criteria, skip rules, and review standard. |
| 2. Check market data | Paper trading market data review process | Source, freshness, gaps, timeframe, liquidity assumption, and sample status. |
| 3. Prepare the decision | Pre-trade review | Thesis, invalidation, planned paper size, risk-reward, and reason to skip if unclear. |
| 4. Check the entry | Trade entry checklist | A consistent record before the outcome is known. |
| 5. Review risk | Risk review | Paper exposure, drawdown, related positions, frequency, and rule-fit notes. |
| 6. Close the loop | Post-trade review | Outcome classification, behavior tag, and one next process action. |
| 7. Improve carefully | Trading feedback loop | A narrow change, more sample collection, or a decision to retire the setup. |
Use the agent-rule pages when the task is to define how a simulated trading agent should behave before any result exists.
Use pre-entry workflows when the trade needs clean market data, a written thesis, invalidation, risk plan, and skip condition before the outcome can bias the review.
Use review workflows after entries and exits to separate clean losses from broken process, and to avoid rewriting rules from one small sample.
Before entry: The agent identifies a simulated crypto setup. The trader opens the pre-trade review, records the thesis, checks paper size with the position size calculator, and confirms the invalidation.
During review: The risk workflow checks related exposure and max drawdown before the simulated entry remains eligible for the sample.
After exit: The post-trade review tags rule fit separately from PnL, then the feedback loop chooses one action: keep collecting samples, tighten one rule, or reduce simulated size.
Many SEO pages answer a definition and stop. Trading Boy needs workflows because the product value is the sequence: paper decision, risk context, journal record, review, and improvement. This directory gives crawlers and users a clear map of that sequence.
It also prevents search-intent overlap. Risk review owns exposure and drawdown questions. Pre-trade review owns setup readiness. Post-trade review owns outcome classification. The feedback loop owns rule changes.
These workflows are for simulated practice and review. They do not execute live trades, provide financial advice, or turn alerts into buy or sell signals.
Use AI trading agent rules first when you are setting up a system. Use pre-trade review first when the agent is already configured and a simulated entry is being considered.
The pre-trade page records the plan before outcome bias. The post-trade page reviews behavior after the outcome is known.
No. They are review structures for paper trading and should not be interpreted as live trading instructions.