whitebit-exchange WhiteBit Trade Review
Compute performance metrics from WhiteBit trade history.
When This Skill Activates
- User asks for a performance review of their trading
- User wants win rate, R:R, or P&L for a period
- User wants to find their biggest mistakes or best trades
- Scheduled weekly or monthly report
Tools
| Tool | Purpose |
|---|---|
account_trade__get_executed_history |
Filled spot orders (paginated) |
deals__get_trade_history |
Granular fills — one row per execution |
account_trade__get_history |
Order-level history |
account_collateral__get_positions_history |
Closed futures positions + realized PnL |
Instructions
Step 1 — Establish scope
Ask if not provided: date range, specific pair filter (optional).
Convert relative dates to absolute: "this month" → 2026-05-01 to 2026-05-27.
Step 2 — Fetch all trades
Call account_trade__get_executed_history with limit=50. Paginate with offset until result count < limit.
Call account_collateral__get_positions_history for any closed futures positions in the same period.
Record total trade count before computing.
Step 3 — Compute core metrics
| Metric | Formula |
|---|---|
| Win rate | winning closed trades / total closed trades × 100% |
| Average win | mean P&L of profitable trades (USDT) |
| Average loss | mean P&L of losing trades (USDT, positive number) |
| R:R ratio | average win / average loss |
| Net P&L | sum of all trade P&Ls (realized only) |
| Fee drag | total fees / gross P&L × 100% |
| Profit factor | gross profit / gross loss |
Count only closed trades in win rate. Exclude open orders.
Step 4 — Group by pair
Compute win rate and net P&L per market pair. Sort by net P&L descending. Surface the best pair (highest P&L) and worst pair (lowest P&L).
Step 5 — Find behavioral patterns
Scan for:
- Losses concentrated in specific UTC hours
- Repeated losses on the same pair
- Overtrading days (days with > 2× the session's daily average trade count)
- Average loss size vs average win size (asymmetry flag if loss > 1.5× win)
Step 6 — Report
May 2026 — 47 trades across 6 pairs
Win rate: 61.7% (29W / 18L)
Net P&L: +$820.90 (after $21.40 fees)
Fee drag: 2.5%
R:R ratio: 1.8
Profit factor: 2.3
Best pair: BTC_USDT +$540 (72% WR)
Worst pair: DOGE_USDT −$184 (33% WR)
Patterns
· 72% of losses opened 02:00–05:00 UTC
· Average DOGE loss 2.3× larger than average DOGE win
· 6 overtrading days (>8 trades/day)
Step 7 — Warnings
Emit warnings when:
- Fee drag > 30% of gross P&L → "High fee drag — consider larger sizes or lower frequency"
- R:R < 1.0 → "Average loss exceeds average win — adjust TP/SL ratios"
- Win rate < 40% → "Below breakeven for this R:R — review entry criteria"
Step 8 — Handle errors
| Error | Action |
|---|---|
| No trades in period | "No closed trades found for this period." — do not fabricate data |
| Partial data (API limit) | State: "Showing {n} trades — full history may require additional pages" |
Composability
Calls: whitebit-portfolio (raw history via account_trade__get_executed_history).
Definition of Done
- Date range and trade count stated at top of report
- All 6 core metrics computed
- By-pair breakdown included
- Behavioral patterns checked
- Applicable warnings emitted
- No fabricated data — empty periods reported as empty