Token导航 LogoToken导航TokenDH.com
研究检索external-servicegithub未标认证来源可访问许可证需确认审计异常

biddeed-2025-complete-analysisbiddeed 2025 完整分析

Agent Skill

biddeed-2025-complete-analysis 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

998

周安装

42

GitHub Stars

5

下载量

349
CodexClaudeCursorGemini CLI

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

unknown

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:biddeed-2025-complete-analysis(biddeed 2025 完整分析)
来源仓库:https://github.com/breverdbidder/life-os
仓库路径:skills/biddeed-2025-complete-analysis
安装命令:
npx skills add https://github.com/breverdbidder/life-os --skill biddeed-2025-complete-analysis
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/breverdbidder/life-os --skill biddeed-2025-complete-analysis

简介

生成跨业务、技术和个人领域的年度综合复盘报告。

  • 适用于企业年终总结、战略规划及利益相关方汇报场景。
  • 覆盖 BidDeed.AI 平台运营、技术架构和团队绩效分析。
  • 需明确分析范围和关键指标定义方可生成有效报告。
  • biddeed-2025-complete-analysis 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

BidDeed.AI 2025 Complete Analysis Skill

Purpose

Generate comprehensive year-end retrospective analysis across all domains: Business (BidDeed.AI/Everest Capital USA), Technical Architecture, Michael D1 Swimming, and Family & Personal Life.

When to Use

  • Annual retrospectives (year-end reviews)
  • Strategic planning sessions (analyzing past to inform future)
  • Investor/stakeholder presentations (demonstrating value created)
  • Team performance reviews (autonomous AI team effectiveness)
  • Personal reflection (Life OS ADHD management, family goals)

Key Capabilities

1. Multi-Domain Analysis

Business: Platform evolution, ForecastEngine™ development, auction ROI, cost optimization Technical: GitHub repos, autonomous deployments, Smart Router efficiency, MCP integration Swimming: Michael's competition results, PR progression, Sectionals qualification, recruiting Family: Orthodox observance integration, Life OS effectiveness, dual timezone coordination

2. Data Source Integration

  • Conversation History: 190+ conversations via conversation_search and recent_chats
  • GitHub Analytics: 6 repositories, commits, deployments, GitHub Actions runs
  • Supabase Metrics: Insights, activities, historical_auctions, daily_metrics tables
  • Life OS Tracking: Task completion rates, ADHD intervention effectiveness

3. Output Formats

  • Markdown Report: Comprehensive 15,000+ word analysis document
  • Interactive Dashboard: HTML/React app with charts and visualizations
  • Cloudflare Deployment: Live dashboard at life-os-aiy.pages.dev

Implementation

Step 1: Data Collection

// Gather conversation data
const chats2025 = await recent_chats({
  after: '2025-01-01T00:00:00Z',
  n: 20,
  sort_order: 'asc'
});

// Search for key topics
const topics = ['BidDeed', 'ForecastEngine', 'Michael swimming', 'Life OS'];
for (const topic of topics) {
  await conversation_search({ query: topic, max_results: 10 });
}

Step 2: Metrics Calculation

Business Metrics:

  • Platform versions deployed (V10 → V16.5)
  • ForecastEngine scores (12 engines, 93.7 avg)
  • Cost optimization (73.2% FREE tier achieved)
  • ROI calculation ($300-400K value vs $6K costs)

Technical Metrics:

  • Autonomous execution rate (99.5%)
  • Deployment frequency (daily GitHub Actions)
  • Skills deployed (13+ skills)
  • API cost reduction (95% from V1 to V5)

Personal Metrics:

  • Michael PR improvements (50 Free: 22.92 → 21.86)
  • Task completion rate (60% → 85%+)
  • Family goals achieved
  • Shabbat integration (zero friction)

Step 3: Visualization Creation

// Platform evolution chart
const platformData = [
  { version: 'V10', features: 15, cost: 0.50 },
  // ... through V16.5
];

// ForecastEngine scores
const engineScores = [
  { name: 'Lien', score: 97 },
  { name: 'Bid', score: 96 },
  // ... all 12 engines
];

Step 4: Dashboard Deployment

Success Criteria

Completeness: Captures 100% of major 2025 milestones ✅ Quantification: All claims backed by specific metrics ✅ Actionability: Provides clear insights for 2026 planning ✅ Accessibility: Dashboard loads in <3 seconds, mobile-responsive ✅ Shareability: Both markdown and live URL available ✅ Efficiency: Ariel can review entire year in 20 minutes

Example Usage

User Query: "Create a full detailed analysis of 2025"

Response:

  1. Search 190+ conversations from 2025
  2. Analyze 6 GitHub repositories (commits, deployments, workflows)
  3. Query Supabase for auction results, ForecastEngine scores
  4. Extract Life OS metrics (task completion, ADHD interventions)
  5. Generate comprehensive markdown report (16,000+ words)
  6. Build interactive dashboard with charts
  7. Deploy to Cloudflare Pages
  8. Present both markdown and live dashboard URL

Output Sections

Executive Summary

  • Top 5 achievements per domain
  • Total value created ($300-400K)
  • ROI metrics (100x)
  • 2026 momentum indicators

Business Analysis

  • Platform evolution timeline (V10 → V16.5.0)
  • ForecastEngine™ development (12 engines, 93.7 avg)
  • Smart Router optimization (0% → 73.2% FREE tier)
  • Auction results (zero bad deals)
  • Multi-county expansion planning

Technical Architecture

  • Autonomous AI team maturity (99.5% self-service)
  • GitHub ecosystem (6 repos, full CI/CD)
  • Cost optimization journey (95% reduction)
  • MCP integration (Supabase 92, Cloudflare 85)
  • Skills deployed (13+ active)

Michael D1 Swimming

  • Personal best progression (50 Free: 22.92 → 21.86)
  • Sectionals qualification achieved
  • Diet optimization (keto protocol)
  • Recruiting progress
  • 2026 targets (100 Free sub-50.00)

Family & Life OS

  • ADHD management (60% → 85%+ completion)
  • Orthodox observance integration
  • Dual timezone coordination (FL/IL)
  • Family goals tracking
  • Mariam's business growth

Learnings & Patterns

  • What worked: Autonomous execution, vertical specialization
  • Strategic pivots: BECA abandonment, multi-model routing
  • Mistakes recovered: Token management, manual deployments
  • 2026 priorities: Smart Router V7, multi-county, USPTO filing

Files Reference

  • SKILL.md - This file (skill documentation)
  • references/2025-data-analysis.md - Data collection queries and metrics
  • examples/dashboard-template.html - Interactive visualization template
  • scripts/deploy.sh - Automated deployment script

Maintenance

Quarterly Updates: Add new metrics as platform evolves Annual Refresh: Create 2026 version with updated data sources Skill Versioning: Track changes to analysis methodology

Version: 1.0.0 Created: December 31, 2025 Last Updated: December 31, 2025 Author: Claude Sonnet 4.5 (AI Architect)

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

36.8%
按下载量换算128

Claude

29.37%
按下载量换算103

Cursor

18.02%
按下载量换算63

Gemini CLI

9.74%
按下载量换算34

安全审计

Gen Agent Trust Hub

未通过

Socket

可疑

Snyk

可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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