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jb-catalyst-edgejb 催化剂边缘

Agent Skill

jb-catalyst-edge 用于补充运维相关能力,适合在 OpenClaw 中需要让 Agent 承接运维相关任务时使用。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

3,231

周安装

132

GitHub Stars

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下载量

1,035
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:jb-catalyst-edge(jb 催化剂边缘)
来源仓库:https://github.com/j3m2b/jb-catalyst-edge
安装命令:
openclaw skills install jb-catalyst-edge
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 jb-catalyst-edge

简介

通过每周扫描、季度回顾和 FIRE 信号分析来识别高可信度股票机会并跟踪 JB 的退休投资组合。

SKILL.md

Skill: Catalyst Edge

Purpose: High-conviction stock opportunities + JB's retirement portfolio tracker.

Trigger: Weekly (Sunday 10 AM CDT via cron) or on demand.


Part 1 — Stock Scanning

What It Looks For

PatternDescriptionConviction
Earnings SurpriseBeat estimates, raised guidance🟡-🟢
Catalyst EventFDA approval, contract win, merger🟡-🟠
Technical BreakoutVolume surge, breakout above resistance🟡
Insider BuyingExecutives buying heavily🟡
Sector RotationMoney flowing into our themes🟢

Target Themes

  • Healthcare/RCM tech
  • AI/automation
  • Dividend payers
  • Growth with value

Quality Criteria

  • Score ≥75 = alert JB immediately (Discord DM)
  • Score 60-75 = include in weekly summary
  • Score <60 = skip
  • Always include source + date

Output Format

🎯 CATALYST EDGE — [Date]

[Stock] — [Ticker]
Catalyst: [What it is]
Conviction: [🔵🟡🟢🟠]
Score: [0-100]
Thesis: [1-sentence why]

Watch List:
1. [Stock] - [reason]
2. [Stock] - [reason]

Part 2 — Quarterly Financial Review (Every 3 Months)

Trigger: January, April, July, October — first Sunday of the month at 10 AM CDT.

Steps

  1. Read the current state:

- /workspace/skills/catalyst-edge/FIRE_MODEL.md — current numbers - /workspace/skills/catalyst-edge/PORTFOLIO_ANALYSIS.md — portfolio - /workspace/memory/life-archive.md — personal context

  1. Post to Discord #retirement-edge:
   📊 QUARTERLY FINANCIAL REVIEW — [Month Year]
   
   Net Worth: $XX,XXX (vs $XX,XXX last quarter — +/- $X,XXX)
   This Quarter: [what changed — new savings, paid down debt, market movement]
   
   FIRE Progress: [X years to FI / age XX target]
   Next Quarter Goals:
   • [Action 1]
   • [Action 2]
   
   Action Items Due:
   • [Stale items from FIRE_MODEL.md priority list]
  1. Update the files:

- Note any account changes in PORTFOLIO_ANALYSIS.md - Flag any action items that are overdue - Log the quarter's net worth in a table at the bottom of FIRE_MODEL.md

  1. Alert JB if:

- A major milestone was hit (e.g., hit $100K, mortgage paid off early) - An action item is 60+ days overdue - Net worth dropped >15% (market downturn check)

Quality Standards

  • Keep it to 10 lines or less in Discord
  • Full details go in the .md files
  • Numbers over opinions always


Part 3 — FIRE Pipeline (Weekly)

Trigger: Runs alongside the weekly stock scan (Sunday 10 AM CDT).

What It Does

  1. Reads RSI results from /workspace/skills/catalyst-edge/stock_scanner/last_scan.json
  2. Applies FIRE model thresholds from /workspace/skills/catalyst-edge/fire_config.json
  3. Calculates signals: STRONG BUY / BUY / HOLD / WEAK / AVOID / TAKE PROFIT
  4. Posts a formatted signal report to Discord #retirement-edge

FIRE Signal Logic

RSI RangeSignalAction
≤ 30 (core) / ≤ 35 (income)🟢 STRONG BUYFI deployment window
30-40🟢 BUYAccumulation candidate
40-60🟡 HOLDNo action
60-70🟠 WEAKPartial profit taking
≥ 70 (core) / ≥ 75 (income)🔴 TAKE PROFIT / AVOIDBook gains; not an entry

Core Principle

VT/VTI/QYLD at RSI ~29-30 simultaneously = historically rare cluster bottom. When 2+ core holdings hit RSI < 30 → FI deployment signal. This has happened <5 times in the past 5 years.

Run the Pipeline

cd /workspace/skills/catalyst-edge/stock_scanner
python3 scan_once.py  # runs fresh scan
python3 ../fire_pipeline.py  # applies FIRE logic + posts to Discord

Files

  • /workspace/skills/catalyst-edge/SKILL.md (this)
  • /workspace/skills/catalyst-edge/FIRE_MODEL.md — current numbers
  • /workspace/skills/catalyst-edge/PORTFOLIO_ANALYSIS.md — portfolio details
  • /workspace/skills/catalyst-edge/HISTORICAL_PICKS.md — past picks + performance
  • /workspace/skills/catalyst-edge/fire_config.json — FIRE threshold config
  • /workspace/skills/catalyst-edge/fire_pipeline.py — signal engine
  • /workspace/skills/catalyst-edge/stock_scanner/last_scan.json — latest scan results

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

73.28%
按下载量换算758

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

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安装前确认

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来源信息

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