binance-leaderboard

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Original

English

🇨🇳

Translation

Chinese

Binance Leaderboard Skill

Binance Leaderboard 技能

On-chain wallet leaderboard ranking and address analysis. Query top traders by PnL, win rate, and more. Evaluate wallet quality with a 6-dimension scoring model.

链上钱包排行榜排名与地址分析工具。可按PnL、胜率等查询顶级交易者，通过六维评分模型评估钱包质量。

Prerequisites

前置条件

This skill requires the

baw

CLI (

@binance/agentic-wallet

npm package). If

baw

is not found:

bash

npm install -g @binance/agentic-wallet

Verify:

baw --version

should print

1.6.2

or higher. If installation fails or the user doesn't have Node.js, inform them that Node.js >= 18 is required.

本技能需要

baw

CLI（

@binance/agentic-wallet

npm包）。若未找到

baw

：

bash

npm install -g @binance/agentic-wallet

验证：执行

baw --version

应显示

1.6.2

或更高版本。若安装失败或用户未安装Node.js，需告知用户需要Node.js >= 18版本。

When to Use

使用场景

User intent	Command
Query top traders by PnL/win rate/volume	`baw leaderboard query`
Analyze a single wallet address (6-dim score + AI archetype)	`baw leaderboard analyze`
Find wallets holding specific tokens (Gem Hunter)	`baw leaderboard alpha-radar`
Save/load preset filter conditions	`baw leaderboard preset save/list`
Save/load Gem Hunter configs	`baw leaderboard alpha-radar-config save/list`

用户意图	命令
按PnL/胜率/交易量查询顶级交易者	`baw leaderboard query`
分析单个钱包地址（六维评分+AI原型）	`baw leaderboard analyze`
查找持有特定代币的钱包（Gem Hunter）	`baw leaderboard alpha-radar`
保存/加载预设筛选条件	`baw leaderboard preset save/list`
保存/加载Gem Hunter配置	`baw leaderboard alpha-radar-config save/list`

Supported Chains

支持的链

Chain	chainId
BSC	`56`
Solana	`CT_501`
Base	`8453`
Ethereum	`1`

链	chainId
BSC	`56`
Solana	`CT_501`
Base	`8453`
Ethereum	`1`

Command Tree

命令树

baw leaderboard
  query                     # Leaderboard query (Public, no auth)
  analyze                   # Single address analysis (6-dim score + AI overlay)
  alpha-radar              # Gem Hunter query (Private, agentSessionId)
  preset
    save                    # Save preset filters (Private)
    list                    # List preset filters (Private)
  alpha-radar-config
    save                    # Save Gem Hunter config (Private)
    list                    # List Gem Hunter config (Private)

All commands support

--json

for structured output.

baw leaderboard
  query                     # 排行榜查询（公开，无需授权）
  analyze                   # 单地址分析（六维评分+AI覆盖）
  alpha-radar              # Gem Hunter查询（私有，需agentSessionId）
  preset
    save                    # 保存预设筛选条件（私有）
    list                    # 列出预设筛选条件（私有）
  alpha-radar-config
    save                    # 保存Gem Hunter配置（私有）
    list                    # 列出Gem Hunter配置（私有）

所有命令均支持

--json

参数以输出结构化数据。

Leaderboard Query

排行榜查询

bash

undefined

bash

undefined

Basic query — top 20 by PnL on BSC, 7d period

基础查询——BSC链上7天周期内PnL排名前20的交易者

baw leaderboard query -c 56 -p 7d -t ALL --json

Sort by win rate, KOL tag only

仅筛选KOL标签，按胜率排序

baw leaderboard query -c 56 -p 30d -t KOL --sort-by 20 --json

Pagination (page from 0, size max 20)

分页查询（从第0页开始，每页最大20条）

baw leaderboard query -c 56 -p 7d --page 0 --size 20 --json


**Public endpoint** — no auth required. Returns per-address PnL, win rate, volume, trade count, token distribution, daily PNL, and top earning tokens.

Key query parameters: `-c/--chain-id` (required), `-p/--period` (7d/30d/90d), `-t/--tag` (ALL/KOL/MPC), `--sort-by` (0=PnL · 20=Win Rate · 30=Total Volume · 50=Trade Count · 60=Recent Activity · 70=Profit Rate · 80=Token Count), `--order-by` (0/2=Descending · 1=Ascending), `--page` (from 0), `--size` (max 20).

Full parameter and return field reference: [`references/cli.md`](references/cli.md)

baw leaderboard query -c 56 -p 7d --page 0 --size 20 --json


**公开端点**——无需授权。返回每个地址的PnL、胜率、交易量、交易次数、代币分布、每日PNL及盈利最高的代币。

关键查询参数：`-c/--chain-id`（必填）、`-p/--period`（7d/30d/90d）、`-t/--tag`（ALL/KOL/MPC）、`--sort-by`（0=PnL · 20=胜率 · 30=总交易量 · 50=交易次数 · 60=近期活跃度 · 70=利润率 · 80=代币数量）、`--order-by`（0/2=降序 · 1=升序）、`--page`（从0开始）、`--size`（最大20）。

完整参数及返回字段参考：[`references/cli.md`](references/cli.md)

Single Address Analyze

单地址分析

bash

undefined

bash

undefined

Analyze a wallet address — 6-dim scoring + AI archetype

分析钱包地址——六维评分+AI原型

Default scans top 1000 entries

默认扫描前1000条记录

baw leaderboard analyze -c 56 -a 0xabc... --json

Scan more entries (up to 5000) for long-tail addresses

为长尾地址扫描更多记录（最多5000条）

baw leaderboard analyze -c 56 -a 0xabc... --top-n 5000 --json


Evaluates the address across 6 dimensions (winrate 25 + stability 20 + drawdown 20 + tags 15 + pnl 10 + follow_friendly 10 = 100), then applies an AI overlay (archetype + behavior_flags + ai_adjustment ±10).

**Flow**: Query leaderboard top 1000 (configurable via `--top-n`) → reverse-lookup the target address → compute scores → apply AI overlay → output rating.

**Rating**: ⭐⭐⭐ ≥ 80 · ⭐⭐ ≥ 65 · ⭐ ≥ 50 · ❌ < 50

If the address is not in the top N (default 1000), returns "N beyond top". Use `--top-n` to increase scan range up to 5000.

Full scoring model details: [`references/scoring.md`](references/scoring.md)

baw leaderboard analyze -c 56 -a 0xabc... --top-n 5000 --json


从六个维度评估地址（胜率25分 + 稳定性20分 + 回撤20分 + 标签15分 + PnL10分 + 易追踪性10分 = 总分100），然后应用AI覆盖（原型+行为标记+AI调整±10分）。

**流程**：查询排行榜前1000条记录（可通过`--top-n`配置）→反向查找目标地址→计算分数→应用AI覆盖→输出评级。

**评级标准**：⭐⭐⭐ ≥80分 · ⭐⭐ ≥65分 · ⭐ ≥50分 · ❌ <50分

若地址不在前N条（默认1000），返回“N beyond top”。用户可通过`--top-n`将扫描范围扩大至最多5000条。

完整评分模型详情：[`references/scoring.md`](references/scoring.md)

Gem Hunter

bash

undefined

bash

undefined

Find wallets holding specific tokens

查找持有特定代币的钱包

baw leaderboard alpha-radar -c 56
-t 0xtoken1,0xtoken2
-m 1 --json


**Private endpoint** — requires `agentSessionId`. Extra required params: `-t/--tokens` (comma-separated token addresses), `-m/--match-count` (≥ 1). Supports `-p/--period`, `--page`, `--size` like query.

Returns records with the same fields as leaderboard query, but `topEarningTokens` replaced by `marchedTokens` (matched tokens).

**Note**: The field is spelled `marchedTokens` (not "matched") in the CLI output.

baw leaderboard alpha-radar -c 56
-t 0xtoken1,0xtoken2
-m 1 --json


**私有端点**——需要`agentSessionId`。额外必填参数：`-t/--tokens`（逗号分隔的代币地址）、`-m/--match-count`（≥1）。支持与查询命令相同的`-p/--period`、`--page`、`--size`参数。

返回字段与排行榜查询相同，但`topEarningTokens`替换为`marchedTokens`（匹配的代币）。

**注意**：CLI输出中该字段拼写为`marchedTokens`（非“matched”）。

Preset & Gem Hunter Config

预设与Gem Hunter配置

bash

undefined

bash

undefined

Save preset filter conditions (pass null/empty to clear all)

保存预设筛选条件（传入null/空数组可清除所有预设）

baw leaderboard preset save --config '[{"name":"MyPreset","period":"7d","winRateMin":50}]' --json

List saved presets

列出已保存的预设

baw leaderboard preset list --json

Save Gem Hunter config (pass null/empty to clear)

保存Gem Hunter配置（传入null/空数组可清除配置）

baw leaderboard alpha-radar-config save -c 56
--config '[{"uuid":"u1","name":"MyRadar","matchTokenCount":2,"tokenAddressList":[{"tokenAddress":"0xabc"}]}]' --json

List saved configs

列出已保存的配置

baw leaderboard alpha-radar-config list -c 56 --json

undefined

baw leaderboard alpha-radar-config list -c 56 --json

undefined

Core Rules

核心规则

Scoring Model Overview

评分模型概述

6-dimension model (total 100) + AI overlay (±10). Dimensions: winrate (25), stability (20), drawdown (20), tags (15), pnl (10), follow_friendly (10). Full tiered scoring tables and AI overlay rules:

references/scoring.md

六维模型（总分100）+AI覆盖（±10分）。维度包括：胜率（25）、稳定性（20）、回撤（20）、标签（15）、PnL（10）、易追踪性（10）。完整分层评分表及AI覆盖规则：

references/scoring.md

Top-N Reverse Lookup

前N条反向查找

analyze

queries the leaderboard's top 1000 entries (configurable via

--top-n

, max 5000) and reverse-looks-up the target address. If not found, returns "N beyond top" — inform the user they can increase

--top-n

or use

binance-wallet-tracker

's address list for long-tail wallets.

analyze

命令查询排行榜前1000条记录（可通过

--top-n

配置，最多5000条）并反向查找目标地址。若未找到，返回“N beyond top”——告知用户可增大

--top-n

或使用

binance-wallet-tracker

的地址列表来分析长尾钱包。

Preset & Config Clearing

预设与配置清除

Passing

null

or empty array to

preset save

alpha-radar-config save

clears all saved items.

向

preset save

或

alpha-radar-config save

传入

null

或空数组可清除所有已保存项。

Cross-Skill Scenarios

跨技能场景

Some scenarios require both leaderboard and wallet-tracker skills:

evaluate follow list: Use
```
binance-wallet-tracker
```
's
```
tracker follow
```
to get the user's followed addresses, then
```
leaderboard analyze
```
each one.
leaderboard diff: Query leaderboard top N, then diff against
```
binance-wallet-tracker
```
's
```
address list
```
to find untracked wallets.
batch import: Query leaderboard with filters → output address list → feed to
```
binance-wallet-tracker
```
's
```
address batch
```
command.

部分场景需同时使用排行榜和钱包追踪技能：

评估关注列表：使用
```
binance-wallet-tracker
```
的
```
tracker follow
```
获取用户关注的地址，再用
```
leaderboard analyze
```
逐个分析。
排行榜差异对比：查询排行榜前N条记录，与
```
binance-wallet-tracker
```
的
```
address list
```
对比，找出未追踪的钱包。
批量导入：带筛选条件查询排行榜→输出地址列表→导入至
```
binance-wallet-tracker
```
的
```
address batch
```
命令。

Write-Back Confirmation

回写确认

After preset/config save operations, re-fetch via

list

to confirm the operation succeeded — don't assume success from the API response alone. If readback shows the saved data is missing, tell the user "Save may not have taken effect, please try again later" — never mention backend bugs or silent failures.

执行预设/配置保存操作后，需通过

list

命令重新获取数据以确认操作成功——不要仅通过API响应判断成功。若回读显示保存的数据缺失，告知用户“保存可能未生效，请稍后重试”——绝不要提及后端bug或静默失败。

User-Facing Presentation

用户端展示规范

This skill serves end users, not developers. Internal field names, error codes, and CLI internals must never appear in user-facing output.

1. Term Mapping (internal → user-facing)

Internal value	User-facing term	Notes
`archetype: sniper`	Sniper
`archetype: swing`	Swing Trader
`archetype: accumulator`	Accumulator
`archetype: farmer`	Farmer
`archetype: mixed`	Mixed
`sort-by: 0`	Sort by PnL
`sort-by: 20`	Sort by Win Rate
`sort-by: 30`	Sort by Total Volume
`sort-by: 50`	Sort by Trade Count
`sort-by: 60`	Sort by Recent Activity
`sort-by: 70`	Sort by Profit Rate
`sort-by: 80`	Sort by Token Count
`address` (in display)	omit	Don't show raw address unless user asks; use `{addressLabel}`
`finalScore`	Score	Don't show the formula `totalScore + aiAdjustment`

Raw enum values (

sniper

swing

, etc.) may appear in CLI syntax examples and internal lookup tables, but never in user-facing replies.

2. Never expose internal identifiers

```
groupId
```
,
```
displayOrder
```
— internal IDs, never shown to users
Error codes (
```
70001001
```
, etc.) — translate to natural-language messages only
Backend behavior details (e.g. preset save returning
```
data: true
```
without persisting) — never mention "backend bug" or "silent failure"

3. Display template hygiene

Use user-facing terms in all output. The

archetype

field should be translated to its Chinese term (Sniper, Swing Trader, etc.) — never show the raw English enum value. Score should be shown as a number, not as a formula.

本服务面向终端用户，而非开发者。内部字段名、错误码及CLI内部细节绝不能出现在用户端输出中。

1. 术语映射（内部→用户端）

内部值	用户端术语	说明
`archetype: sniper`	狙击手
`archetype: swing`	波段交易者
`archetype: accumulator`	囤币者
`archetype: farmer`	收益耕种者
`archetype: mixed`	混合型
`sort-by: 0`	按PnL排序
`sort-by: 20`	按胜率排序
`sort-by: 30`	按总交易量排序
`sort-by: 50`	按交易次数排序
`sort-by: 60`	按近期活跃度排序
`sort-by: 70`	按利润率排序
`sort-by: 80`	按代币数量排序
`address` （展示时）	省略	除非用户要求，否则不显示原始地址；使用 `{addressLabel}`
`finalScore`	评分	不要显示公式 `totalScore + aiAdjustment`

原始枚举值（如

sniper

、

swing

等）可出现在CLI语法示例和内部查找表中，但绝不能出现在用户端回复中。

2. 绝不暴露内部标识符

```
groupId
```
、
```
displayOrder
```
——内部ID，绝不展示给用户
错误码（如
```
70001001
```
等）——仅转换为自然语言消息
后端行为细节（如预设保存返回
```
data: true
```
但未持久化）——绝不要提及“后端bug”或“静默失败”

3. 展示模板规范

所有输出均使用用户端术语。

archetype

字段应转换为对应的中文术语（狙击手、波段交易者等）——绝不显示原始英文枚举值。评分应显示为数字，而非公式。

Error Codes

错误码

Error codes are for internal lookup only — never show numeric codes or internal names to users. Translate to natural-language messages.

Code	Internal Name	User-Facing Message
70001001	TRACKER_API_ERROR	Query failed, please try again later
70004001	TRACKER_LEADERBOARD_EMPTY	Leaderboard data is empty
70004002	TRACKER_ADDRESS_NOT_RANKED	Address not ranked (beyond top 250)

错误码仅用于内部查询——绝不向用户显示数字代码或内部名称。需转换为自然语言消息。

代码	内部名称	用户端消息
70001001	TRACKER_API_ERROR	查询失败，请稍后重试
70004001	TRACKER_LEADERBOARD_EMPTY	排行榜数据为空
70004002	TRACKER_ADDRESS_NOT_RANKED	地址未上榜（超出前250名）

Display Templates

展示模板

Leaderboard entry:

{addressLabel} | PnL: {realizedPnl} ({realizedPnlPercent}%) | Win Rate: {winRate}% | Trades: {totalTxCnt} | Tokens: {totalTradedTokens}

Address analysis rating:

📊 {addressLabel} Address Analysis

Rating: ⭐⭐⭐ (85/100)
Trading Style: Sniper
Behavior Patterns: High Frequency Small Amount, Nocturnal Active

Dimension Scores:
  Win Rate: 22/25 | Stability: 18/20 | Drawdown: 16/20
  Tags: 15/15 | PnL: 8/10 | Trackability: 6/10

AI Adjustment: +5 (consistent trading style, stable pattern)

排行榜条目：

{addressLabel} | PnL: {realizedPnl} ({realizedPnlPercent}%) | 胜率: {winRate}% | 交易次数: {totalTxCnt} | 交易代币数: {totalTradedTokens}

地址分析评级：

📊 {addressLabel} 地址分析

评级: ⭐⭐⭐ (85/100)
交易风格: 狙击手
行为模式: 高频小额交易、夜间活跃

维度评分:
  胜率: 22/25 | 稳定性: 18/20 | 回撤: 16/20
  标签: 15/15 | PnL: 8/10 | 可追踪性: 6/10

AI调整: +5（交易风格一致，模式稳定）

Full CLI Reference

完整CLI参考

```
references/cli.md
```
— All commands with parameter tables, return field tables, and examples
```
references/scoring.md
```
— 6-dimension scoring model, AI overlay, rating standards

```
references/cli.md
```
— 所有命令的参数表、返回字段表及示例
```
references/scoring.md
```
— 六维评分模型、AI覆盖、评级标准