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Binance Futures Strategy Analysis
Analyze Binance USDT-margined perpetual futures symbols with public futures market data only and return a structured market analysis report with a clear BUY,...
What it does
Analyze Binance USDT-margined perpetual futures symbols with public futures market data only and return a structured market analysis report with a clear BUY,...
The skill document
Binance Futures Strategy Analysis
Overview
Use this skill to produce strategy decisions for Binance U-margined perpetual contracts from public market data only. Do not place orders, do not call any private API, and do not use spot market data.
Workflow
- Read the canonical strategy source at
../../../src/main/resources/system-prompt.txt. - Read
references/system-prompt-coverage.mdbefore analysis. It mirrors the canonical rules in skill-friendly form and includes the analysis-only output adaptation. - Read
../../../docs/core-feature-spec.mdonly if you need the project's original execution flow and field semantics. - Read
references/analysis-mode.mdbefore deciding, because this skill runs in analysis-only mode instead of live execution mode. - Normalize user input symbols to Binance USDT perpetual symbols:
BTC->BTCUSDTETH->ETHUSDTBTCUSDTstaysBTCUSDT
- Run
python3 scripts/binance_futures_snapshot.pywith the user symbols. - Use the script output as the only market data source unless the user gives additional account context.
- Apply the strategy rules from
system-prompt.txtexactly. Do not simplify the decision logic just because this skill is analysis-only. - Build the internal decision object in the canonical schema first, then render it as a human-readable structured report unless the user explicitly asks for raw JSON.
Analysis Mode Rules
- Default to analysis-only assumptions when the user gives only symbols:
equity_usdt = 10000free_usdt = 10000positions = []cooldown_ok = true
- Replace those defaults if the user provides account equity, free balance, cooldown status, or current positions.
- Because there is no live position context by default:
- Use
BUY,SELL, orHOLD. - Do not emit
ADD,REDUCE, orCLOSEunless the user explicitly supplies an existing position.
- Use
- Still fill every required field from the canonical schema:
tsinstIdactionposition_modesize_usdtorder_typestop_loss_pxexit_planreasonconfidenceleveragecooldown_ok
- Use
instIdinBTC-USDTstyle in the internal canonical decision. The script'sbinance_symbolis only for data fetching. - Set
order_typetoMARKET. - Keep
reasonin simplified Chinese and make it cite actual sequence evidence from the script output. - Respect the canonical leverage ladder, confidence buckets, sizing rules, and exit-plan rules even when the final answer is prose.
Default Output Format
Default to a structured Chinese analysis report, not raw JSON.
Include these sections in order unless the user explicitly asks for a different format:
结论- State the final recommended action:
BUY/SELL/HOLD. - State whether the recommendation is immediate action or wait-for-confirmation.
- State the final recommended action:
趋势判断- Explain the 2H strategic direction.
- Explain the 15m execution structure.
- Mention 5m only as supporting context.
关键理由- Explain why the chosen action is valid.
- Explain why the opposite direction is not preferred.
- Explain why now is or is not the right timing.
支撑与阻力- List near support, key support, near resistance, and key resistance.
- Distinguish short-term levels from higher-timeframe levels.
触发条件- Explain what price action would upgrade to
BUY. - Explain what price action would upgrade to
SELL. - Explain what invalidates the current bias.
- Explain what price action would upgrade to
风控与计划- Give stop-loss logic, target logic, and management logic in plain Chinese.
- Mention if current risk/reward is insufficient.
If the user explicitly asks for JSON, return the canonical JSON array instead.
How To Read The Script Output
Focus on these sections:
timeframes["2h"]- Use for strategic trend class:
STRONG_UP,MODERATE_UP,MODERATE_DOWN,STRONG_DOWN. - Check price structure, EMA alignment, MACD histogram, RSI, ADX, swing highs/lows, reversal candles, volume anomalies, and volume profile.
- Use for strategic trend class:
timeframes["15m"]- Use for execution quality.
- Check breakout confirmation, pullback hold, EMA21 behavior, ATR-based stop distance, recent swing levels, and risk/reward estimates.
timeframes["5m"]- Use only as short-term context. Do not let it override the 2H strategic filter.
funding- Use for cost evaluation.
depth- Use spread and slippage estimates to judge whether execution cost is acceptable.
open_interest- Use as supporting context, not as a standalone trigger.
Decision Discipline
- Enforce the 2H directional filter first.
- Require confirmed 15m structure before any
BUYorSELL. - Prefer
HOLDwhen confirmation is missing, risk/reward is poor, ATR expansion is too aggressive, or cost is unattractive. - For counter-trend setups, allow only the weaker reconnaissance logic that the canonical prompt permits.
- Always produce an
exit_planwith numerictpandsl, plus a Chineseinvmanagement rule. - If the data is incomplete or inconsistent, output
HOLD. - Internally evaluate all canonical controls:
- trend class
- entry confirmation
- counter-trend exception handling
- leverage bucket
- nominal size
- worst-case risk
- exit-plan priority
- cooldown
- simultaneous-position cap
- confidence bucket
Coverage Check
This skill is not allowed to rely on a partial summary anymore. Before answering, make sure your reasoning covers all canonical rule groups listed in references/system-prompt-coverage.md.
Script
- Main helper:
scripts/binance_futures_snapshot.py - Purpose:
- Fetch Binance U-margined perpetual public data
- Compute the indicators and structural helpers required by the strategy
- Output a compact JSON snapshot for one or more symbols
Output Contract
- Default:
- Return a structured Chinese market analysis report.
- Include a single explicit final recommendation per symbol:
BUY,SELL, orHOLD. - Include detailed reasons, support and resistance, invalidation conditions, and next-step triggers.
- If JSON is requested:
- Return one decision object per requested symbol in a single JSON array.
- Keep the field order exactly aligned with the canonical prompt.
If the user asks for BTC ETH, analyze both symbols separately in the same response.
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