Token导航 LogoToken导航TokenDH.com
效率只读clawhub未标认证来源可访问clear审计通过

al-brooks-price-action艾尔布鲁克价格行动

Agent Skill

al-brooks-price-action 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,851

周安装

120

GitHub Stars

1

下载量

998
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:al-brooks-price-action(艾尔布鲁克价格行动)
来源仓库:https://github.com/ovels/al-brooks-price-action
安装命令:
openclaw skills install al-brooks-price-action
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install al-brooks-price-action

简介

用于补充效率相关能力,适合在 OpenClaw 中处理价格行为分析任务。

  • 提供 Al Brooks 风格的 OHLC 条形图、烛台序列和交易环境可视化。
  • 适用于学习价格行动策略或复盘交易逻辑的场景。
  • 安装命令:openclaw skills install al-brooks-price-action,来自指定仓库。
  • 使用前需确认权限范围、维护状态及是否依赖外部绘图资源。

SKILL.md

name
al-brooks-price-action
description
|

Al Brooks Price Action

Use this skill for discretionary price action analysis. Prioritize context, current tradeability, and the hard right edge of the chart. Do not drift into macro or indicator-heavy analysis unless the user explicitly asks for it.

Load References Selectively

Accepted Inputs

  • OHLC text or tables
  • chart screenshots
  • notes from another analyst or agent
  • multi-timeframe summaries

If the input is incomplete, state what is missing and continue with the visible evidence instead of blocking.

Operating Rules

  1. Start with context, not the signal bar. Higher timeframe and recent structure outrank a single candle.
  2. Focus on the live area. The active trade trigger should come from the latest 1-3 bars, not from an old pattern that already played out.
  3. Default to trading_range or no trade when evidence is mixed.
  4. Separate actionable, watch, and none. Do not force a trade.
  5. Use Brooks-style terms, but explain the bottom line in plain language.
  6. Counter-trend setups are lower quality unless the reversal evidence is unusually strong and location is excellent.
  7. Do not hallucinate hidden bars or unreadable prices from screenshots. If a value is unclear, say so.

Analysis Workflow

  1. Identify instrument, timeframe, and whether the user cares about scalp, swing, or both.
  2. Classify context:

- market_phase: trending, trading_range, broad_channel, or unknown - always_in: long, short, or unknown - nearby magnets: prior high/low, breakout point, EMA, measured move target, range edge, gap close, session extreme

  1. Decide the dominant story:

- trend continuation - breakout test / breakout pullback - reversal attempt - breakout mode / two-sided range

  1. Evaluate only the setup nearest the hard right edge:

- setup name - direction - signal bar quality - context fit - whether confirmation is still needed

  1. Produce one of three outcomes:

- actionable - watch - none

  1. If the setup is tradable, explain trigger, invalidation, first target, and whether it is better framed as scalp or swing.
  2. If it is not tradable, say what would need to change to make it tradable.

Preferred Output

Use this shape unless the user asks for a different format.

Market Context

  • market_phase
  • always_in
  • dominant side
  • magnets / important levels

Active Setup

  • setup name
  • long, short, or none
  • why it qualifies
  • why it might fail

Tradeability

  • actionable, watch, or none
  • entry trigger
  • stop logic
  • target logic
  • scalp, swing, or none
  • invalidation

Bottom Line

One short paragraph in plain language.

Optional Machine-Readable Block

When the user wants structured output, append a JSON block using this schema:

{
  "market_phase": "trending|trading_range|broad_channel|unknown",
  "always_in": "long|short|unknown",
  "setup_status": "actionable|watch|none",
  "setup_type": "string",
  "direction": "long|short|none",
  "signal_bar_quality": "high|medium|low|none",
  "entry_trigger": "string",
  "stop_logic": "string",
  "target_1": "string",
  "target_2": "string",
  "trade_style": "scalp|swing|none",
  "invalidation": "string",
  "confidence": 0.0
}

Special Cases

  • For screenshots: describe only what is visible, then infer cautiously.
  • For multi-timeframe requests: analyze higher timeframe first, lower timeframe second.
  • For post-trade reviews: separate "what the chart offered then" from "what is tradable now".
  • For automation prompts: keep labels stable and concise so downstream parsers can consume them.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

71.79%
按下载量换算716

安全审计

VirusTotal

未展示

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills