> ## Documentation Index
> Fetch the complete documentation index at: https://docs.trinigence.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Common Missing Details
> The most frequent details traders forget - and why strategies behave unexpectedly.
## Why strategies often “don’t work”
Most failed strategies don’t fail because the idea is bad.
They fail because something important was left implicit.
This page highlights the most common missing details - so you can spot them early and iterate faster.
If a strategy behaves unexpectedly, it’s almost always due to a missing or misunderstood assumption.
***
## 1. Missing or weak exits
### The problem
Traders focus heavily on entries and treat exits as an afterthought.
Example:
```text theme={null}
Buy when EMA(20) crosses above EMA(50).
```
What’s missing:
* when to exit
* how much risk is acceptable
* what happens if the trade goes nowhere
Entries define when you trade.\
Exits define how you survive.
### How to fix it
Always include at least:
* one take profit
* one stop loss
***
## 2. Implicit timeframes
### The problem
You think in one timeframe - ATI can’t guess which.
Example:
```text theme={null}
Trade RSI oversold conditions.
```
Missing detail:
* Is this 5m, 1h, or 1D?
Even the same indicator behaves completely differently across timeframes.
### How to fix it
Always state the timeframe explicitly, especially early on.
***
## 3. Direction not clearly defined
### The problem
Some ideas imply buying, but never say it.
Example:
```text theme={null}
Trade pullbacks using RSI.
```
Questions ATI must answer:
* long only?
* short only?
* both?
### How to fix it
Be explicit when possible:
```text theme={null}
Go long on RSI pullbacks.
```
***
## 4. Risk assumptions left vague
### The problem
Words like:
* “small stop”
* “tight risk”
* “controlled drawdown”
mean different things to different traders.
ATI cannot translate intent without numbers or rules.
### How to fix it
Even rough numbers are better than none:
```text theme={null}
Use a 1% stop loss.
```
***
## 5. Overly abstract language
### The problem
Human intuition doesn’t always map to deterministic logic.
Bad examples:
```text theme={null}
Enter on strong momentum.
Exit when price looks exhausted.
```
These cannot be backtested.
### How to fix it
Translate intuition into observable conditions:
```text theme={null}
Enter when RSI(14) > 60.
Exit when RSI(14) crosses below 50.
```
***
## 6. Filters that silently block trades
### The problem
You add a filter and forget it’s there.
Examples:
* trading only on certain days
* session filters
* strict confirmations
Result:
* very few trades
* or none at all
### How to fix it
If a strategy produces no trades:
* remove filters first
* confirm baseline behavior
* reintroduce filters one by one
***
## 7. Backtest range assumptions
### The problem
You assume a long history - data may be shorter.
Example:
```text theme={null}
Backtest from 2018 onwards.
```
But:
* symbol launched later
* timeframe data starts later
### How to fix it
Always check:
* effective backtest start date
* number of trades generated
***
## 8. Expecting AI to “know what you meant”
### The problem
ATI is powerful - but not telepathic.
If multiple interpretations exist, ATI must choose or ask.
### How to fix it
When results surprise you:
* inspect inferred assumptions
* rewrite only the unclear part
* don’t start over
See which gaps ATI safely fills - and which require your input.
***
## A quick self-check before submitting
Before you run a strategy, ask:
* Is the timeframe explicit?
* Is direction clear?
* Is there a defined exit?
* Is risk bounded?
* Are filters intentional?
If yes - your strategy is structurally sound.
***
## What to read next
Learn when to stay intuitive and when to be precise.
The mental model behind clear strategy ideas.
How missing details map to strategy components.
Common issues and fixes.
Most strategy problems aren’t logic problems -\
they’re communication problems.