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paiupgradepaiupgrade 搜索

Agent Skill

paiupgrade 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

1,922

周安装

77

GitHub Stars

11,773

下载量

622
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

3

许可证

MIT

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:paiupgrade(paiupgrade 搜索)
来源仓库:https://github.com/danielmiessler/personal_ai_infrastructure
仓库路径:skills/paiupgrade
安装命令:
npx skills add https://github.com/danielmiessler/personal_ai_infrastructure --skill PAIUpgrade
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/danielmiessler/personal_ai_infrastructure --skill PAIUpgrade

简介

paiupgrade 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装使用。
  • 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。
  • paiupgrade 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Customization

Before executing, check for user customizations at: ~/.claude/PAI/USER/SKILLCUSTOMIZATIONS/PAIUpgrade/

If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.

🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION)

You MUST send this notification BEFORE doing anything else when this skill is invoked.

  1. Send voice notification: curl -s -X POST http://localhost:8888/notify \ -H "Content-Type: application/json" \ -d '{"message": "Running the WORKFLOWNAME workflow in the PAIUpgrade skill to ACTION"}' \ > /dev/null 2>&1 &
  2. Output text notification: Running the **WorkflowName** workflow in the **PAIUpgrade** skill to ACTION...

This is not optional. Execute this curl command immediately upon skill invocation.

PAIUpgrade Skill

Primary Purpose: Generate prioritized upgrade recommendations for the user's existing PAI setup by understanding their context and discovering what's new in the ecosystem.

The skill runs three parallel agent threads that converge into personalized recommendations:

Thread 1: USER CONTEXT     Thread 2: SOURCE COLLECTION    Thread 3: INTERNAL REFLECTIONS
┌───────────────────┐     ┌───────────────────────┐      ┌───────────────────────┐
│ TELOS Analysis    │     │ Anthropic Sources     │      │ Algorithm Reflections │
│ Project Analysis  │     │ YouTube Channels      │      │ Q2: Algorithm fixes   │
│ Recent Work       │     │ Custom USER Sources   │      │ Q1: Execution errors  │
│ PAI System State  │     │ GitHub Trending       │      │ Sentiment weighting   │
│                   │     │ Community Updates     │      │                       │
└───────────────────┘     └───────────────────────┘      └───────────────────────┘
           │                         │                              │
           └─────────────┬───────────┴──────────────────────────────┘
                         ▼
           ┌─────────────────────────────┐
           │  PRIORITIZED RECOMMENDATIONS │
           │  (external + internal)       │
           └─────────────────────────────┘

Workflow Routing

WorkflowTriggerFile
Upgrade"check for upgrades", "check sources", "any updates", "check Anthropic", "check YouTube", "upgrade", "pai upgrade"Workflows/Upgrade.md
MineReflections"mine reflections", "check reflections", "what have we learned", "internal improvements", "reflection insights"Workflows/MineReflections.md
AlgorithmUpgrade"algorithm upgrade", "upgrade algorithm", "improve the algorithm", "algorithm improvements", "fix the algorithm"Workflows/AlgorithmUpgrade.md
ResearchUpgrade"research this upgrade", "deep dive on [feature]", "further research"Workflows/ResearchUpgrade.md
FindSources"find upgrade sources", "find new sources", "discover channels"Workflows/FindSources.md

Default workflow: If user says "upgrade" or "check for upgrades" without specifics, run the Upgrade workflow. The Upgrade workflow automatically includes internal reflection mining as Thread 3.


Primary Output Format

Discoveries first. Recommendations second. Technique details third.

The output has THREE major sections:

  1. Discoveries — Everything found, ranked by interestingness, showing source and PAI relevance at a glance
  2. Recommendations — What to actually integrate, organized by priority tier
  3. Technique Details — Full extraction with code examples and implementation steps
# PAI Upgrade Report
**Generated:** [timestamp]
**Sources Processed:** [N] release notes parsed | [N] videos checked | [N] docs analyzed | [N] GitHub queries run
**Findings:** [N] techniques extracted | [N] content items skipped

---

## ✨ Discoveries

Everything interesting we found, ranked by how compelling it is for PAI. This is the "what's out there" overview.

| # | Discovery | Source | Why It's Interesting | PAI Relevance |
|---|-----------|--------|---------------------|---------------|
| 1 | [Name of thing found] | [GitHub release / YouTube video / Docs / Blog] | [1-2 sentences: what makes this cool or notable] | [1 sentence: how it maps to PAI] |
| 2 | ... | ... | ... | ... |
| ... | ... | ... | ... | ... |

**Ranking rule:** Sort by interestingness — the most "whoa, that's cool" discoveries go at the top. This is NOT the same as implementation priority (that's the Recommendations section below). A LOW-priority awareness item can still be the most interesting discovery.

---

## 🔥 Recommendations

What to actually DO with these discoveries, organized by urgency and impact.

### 🔴 CRITICAL — Integrate immediately

These fix gaps, security issues, or unlock capabilities that PAI should already have.

| # | Recommendation | PAI Relevance | Effort | Files Affected |
|---|---------------|---------------|--------|----------------|
| 1 | [Short action name] | [Why this matters for PAI — what gap it fills or what breaks without it] | [Low/Med/High] | `[file1]`, `[file2]` |

### 🟠 HIGH — Integrate this week

These significantly improve PAI's capabilities or efficiency.

| # | Recommendation | PAI Relevance | Effort | Files Affected |
|---|---------------|---------------|--------|----------------|
| 2 | [Short action name] | [Which PAI component improves and how] | [Low/Med/High] | `[file1]` |

### 🟡 MEDIUM — Integrate when convenient

These add useful capabilities or align PAI with ecosystem best practices.

| # | Recommendation | PAI Relevance | Effort | Files Affected |
|---|---------------|---------------|--------|----------------|
| 3 | [Short action name] | [What becomes possible for PAI] | [Low/Med/High] | `[file1]` |

### 🟢 LOW — Awareness / future reference

These are nice-to-know or will become relevant later.

| # | Recommendation | PAI Relevance | Effort | Files Affected |
|---|---------------|---------------|--------|----------------|
| 4 | [Short action name] | [Why to keep this on the radar] | [Low/Med/High] | `[file1]` |

---

## 🎯 Technique Details

Full extracted techniques for reference. Each recommendation above maps to one or more techniques below.

### From Release Notes

#### [N]. [Feature/Change Name]
**Source:** GitHub claude-code v2.1.16, commit abc123
**Priority:** 🔴 CRITICAL | 🟠 HIGH | 🟡 MEDIUM | 🟢 LOW

**What It Is (16-32 words):**
[Describe the technique itself - what it does, how it works, what capability it provides. Must be 16-32 words, concrete and specific.]

**How It Helps PAI (16-32 words):**
[Describe the specific benefit to our PAI system - which component improves, what gap it fills, what becomes possible. Must be 16-32 words.]

**The Technique:**
> [Exact code pattern, configuration, or approach - quoted or code-blocked]

**Applies To:** `hooks/SecurityValidator.hook.ts`, ISC verification
**Implementation:**

// Before (what you have now) [current pattern]

// After (with this technique) [new pattern]


---

### From YouTube Videos

#### [N]. [Specific Technique Name]

**Source:** R Amjad - "Video Title" @ 12:34 **Priority:** 🔴 CRITICAL | 🟠 HIGH | 🟡 MEDIUM | 🟢 LOW

**What It Is (16-32 words):** [Describe the technique itself]

**How It Helps PAI (16-32 words):** [Describe the specific benefit]

**The Technique:**

> "[Exact quote or paraphrased technique from transcript]"

**Applies To:** Browser skill, delegation system **Implementation:** [Specific steps to apply this technique]

---

### From Documentation / Other Sources

#### [N]. [Specific Capability/Pattern]

**Source:** Claude Docs - Tool Use section, updated 2026-01-20 **Priority:** 🔴 CRITICAL | 🟠 HIGH | 🟡 MEDIUM | 🟢 LOW

**What It Is (16-32 words):** [Describe the technique itself]

**How It Helps PAI (16-32 words):** [Describe the specific benefit]

**The Technique:**

> [Exact documentation excerpt showing the capability]

**Applies To:** `PAI/SKILL.md`, agent spawning **Implementation:** [Specific changes needed]

---

## 📊 Summary

| # | Technique | Source | Priority | PAI Component | Effort |
| --- | --- | --- | --- | --- | --- |
| 1 | [name] | [source] | 🔴/🟠/🟡/🟢 | [component] | Low/Med/High |

**Totals:** [N] Critical | [N] High | [N] Medium | [N] Low | [N] Skipped

---

## ⏭️ Skipped Content

| Content | Source | Why Skipped |
| --- | --- | --- |
| [video/doc title] | [source] | [No extractable technique / Not relevant to PAI / Covers basics already implemented] |

---

## 🔍 Sources Processed

**Release Notes Parsed:**

- claude-code v2.1.14, v2.1.15, v2.1.16 → [N] techniques extracted
- MCP 2025-11-25 → [N] techniques extracted

**Videos Checked:**

- R Amjad: "Title" (23:45) → [N] techniques extracted
- AI Jason: "Title" (15:20) → 0 techniques (skipped: Gemini focus)

**Docs Analyzed:**

- Claude Tool Use docs → [N] techniques extracted

Extraction Rules

CRITICAL: Extract, don't summarize. Techniques, not recommendations.

  1. Every output item must be a TECHNIQUE - A specific pattern, code snippet, configuration, or approach
  2. Quote or code-block the actual content - Show exactly what was said/written
  3. Map to PAI components - Every technique must connect to a specific file, skill, workflow, or system component
  4. Two mandatory description fields (16-32 words each):

- What It Is: Describe the technique itself - what it does, how it works, what capability it provides - How It Helps PAI: Describe the specific benefit - which component improves, what gap it fills, what becomes possible

  1. Provide implementation - Show before/after code or specific steps
  2. Skip, don't dilute - If content has no extractable technique, put it in Skipped Content with reason

Anti-patterns to AVOID:

  • ❌ "Check out this video for more"
  • ❌ "This release has improvements"
  • ❌ "Consider looking into this"
  • ❌ Vague summaries without specific techniques
  • ❌ Links without extracted content

Source Type Labels:

LabelMeaning
GitHub: claude-code vX.Y.ZSpecific version release notes
YouTube: Creator @ MM:SSVideo with timestamp
Docs: Section NameDocumentation section
Blog: Post TitleBlog post

The Two-Thread Architecture

Thread 1: User Context Analysis

Purpose: Deeply understand the user to personalize recommendations.

Launch parallel agents to analyze:

AgentFocusSources
TELOS AgentUser's goals, challenges, current focusPAI/USER/TELOS/*.md
Project AgentActive projects, tech stacks, dependenciesTELOS/PROJECTS.md, recent work context
History AgentRecent work patterns, what's been doneMEMORY/WORK/, MEMORY/STATE/current-work.json
PAI State AgentSystem capabilities, installed skills, gapsskills/, hooks/, settings.json

Output: A context object that includes:

  • User's current focus areas and priorities
  • Active projects and their tech stacks
  • Recent work patterns and themes
  • PAI system state and existing capabilities

Thread 2: Source Collection

Purpose: Discover what's new in the ecosystem.

Launch parallel agents to check:

AgentFocusSources
Anthropic AgentOfficial Anthropic updatesTools/Anthropic.ts (30+ sources)
YouTube AgentConfigured channels for new videosUSER customization channels
Custom Source AgentAny USER-defined additional sourcesUSER/SKILLCUSTOMIZATIONS/PAIUpgrade/
GitHub Trending AgentTrending projects for PAI inspirationgh api search/repositories via user-sources.json queries

Output: A collection of discoveries:

  • New features, releases, changes from Anthropic
  • New videos with transcripts and key insights
  • Updates from custom sources

Process Flow

Step 1: Launch Both Threads in Parallel

Using BACKGROUNDDELEGATION, spawn both analysis threads simultaneously:

## Thread 1: User Context (4 parallel agents)

### Agent 1: TELOS Analysis
Read and analyze:
- ~/.claude/PAI/USER/TELOS/TELOS.md
- ~/.claude/PAI/USER/TELOS/GOALS.md
- ~/.claude/PAI/USER/TELOS/PROJECTS.md
- ~/.claude/PAI/USER/TELOS/CHALLENGES.md
- ~/.claude/PAI/USER/TELOS/STATUS.md

Extract: Current focus, priorities, active goals, project themes

### Agent 2: Recent Work Analysis
Read and analyze:
- ~/.claude/MEMORY/STATE/current-work.json
- Recent MEMORY/WORK/ directories

Extract: What user has been working on, patterns, open tasks

### Agent 3: PAI System State
Analyze:
- ~/.claude/skills/ (installed skills)
- ~/.claude/hooks/ (active hooks)
- ~/.claude/settings.json (configuration)

Extract: Current capabilities, potential gaps, system health

### Agent 4: Tech Stack Context
From PROJECTS and recent work, identify:
- Languages and frameworks in use
- Deployment targets
- Integration points

---

## Thread 2: Source Collection (3 parallel agents)

### Agent 1: Anthropic Sources
Run: bun ~/.claude/skills/Utilities/PAIUpgrade/Tools/Anthropic.ts
Check all 30+ official sources for updates

### Agent 2: YouTube Channels
Check configured channels for new videos
Extract transcripts from new content

### Agent 3: Custom Sources
Check any USER-defined additional sources

Step 2: Synthesize Results

Once both threads complete:

  1. Merge context: Combine user analysis into unified context object
  2. Filter discoveries: Remove items that don't apply to user's stack/focus
  3. Score relevance: Rate each discovery against user's TELOS and projects
  4. Prioritize: Sort by (relevance to user × impact × ease)

Step 3: Generate Recommendations

For each discovery that passes relevance filtering:

  1. Personalize: Explain why this matters for THIS user specifically
  2. Contextualize: Map to their projects, goals, and challenges
  3. Actionize: Provide concrete implementation steps
  4. Estimate: Rate effort relative to their experience level

Step 4: Output Report

Generate the prioritized recommendations report (see format above).


Configuration

Skill Files:

  • sources.json - Anthropic sources config (30+ sources)
  • youtube-channels.json - Base YouTube channels (empty by default)
  • State/last-check.json - Anthropic state
  • State/youtube-videos.json - YouTube state
  • State/github-trending.json - GitHub trending state (seen repos)

User Customizations (~/.claude/PAI/USER/SKILLCUSTOMIZATIONS/PAIUpgrade/):

  • EXTEND.yaml - Extension manifest
  • youtube-channels.json - User's personal YouTube channels
  • Additional source definitions

Tool Reference

ToolPurpose
Tools/Anthropic.tsCheck Anthropic sources for updates

Key Principles

  1. Extract, Don't Summarize: Pull specific techniques from content, never just link to sources
  2. Quote the Source: Show actual code, documentation quotes, or transcript excerpts
  3. PAI-Contextualized: Every technique maps to a specific PAI file, skill, or component
  4. Explain "Why You": Use phrases like "This helps because your [X] currently [Y]"
  5. TELOS-Connected: Reference user's goals and challenges when explaining relevance
  6. Skip Boldly: If content has no extractable technique, skip it entirely
  7. Implementation-Ready: Provide actual code changes, not vague recommendations

Examples

Example 1: Standard upgrade check

User: "check for upgrades"
→ Launch Thread 1 (4 agents analyzing user context)
→ Launch Thread 2 (3 agents checking sources)
→ Wait for both threads
→ Synthesize into prioritized recommendations
→ Output personalized upgrade report

Example 2: Quick Anthropic-only check

User: "check Anthropic only"
→ Run Anthropic.ts tool directly
→ Use cached user context from recent session
→ Quick-match against user focus areas
→ Output filtered recommendations

Workflows

  • Upgrade.md - Primary workflow: full two-thread analysis with prioritized recommendations
  • ResearchUpgrade.md - Deep dive on a specific upgrade opportunity
  • FindSources.md - Discover and evaluate new sources to monitor


Anti-Patterns (What NOT to Output)

These output patterns are FAILURES. If you produce these, you have not completed the skill correctly:

❌ Bad OutputWhy It's Wrong✅ Correct Output
"Check out R Amjad's video on Claude Code"Points to content instead of extracting it"@ 5:42, R Amjad shows this technique: [quote]"
"v2.1.16 has task management improvements"Vague summary, no technique"v2.1.16 adds addBlockedBy parameter: [code example]"
"Consider looking into MCP updates"Recommendation without extraction"MCP now supports [specific feature]: [docs quote]"
"This could be useful for your workflows"Vague relevance"This improves your Browser skill because [specific gap it fills]"
"Several videos covered AI agents"Count without content"[N] videos skipped - no extractable techniques"
"This helps because it improves things"Vague benefit, no word count"How It Helps PAI (16-32 words): Our SecurityValidator currently only blocks commands. This technique enables injecting reasoning context before tool execution, making security decisions more nuanced."
"A new hook feature"No description of what it IS"What It Is (16-32 words): PreToolUse hooks can return additionalContext that gets injected into the model's context before execution, enabling reasoning-based decisions rather than binary blocks."
"Top 3 Actions" or flat recommendation listNo priority tiers — everything looks equally importantRecommendations section with 🔴 CRITICAL / 🟠 HIGH / 🟡 MEDIUM / 🟢 LOW tiers, each with PAI Relevance column
Recommendations at the bottom of the reportActionable items buried after technique dump🔥 Recommendations section appears FIRST, technique details are reference material below

The test: If you can say "show me the technique" and there's nothing to show, you've failed.

Word count test: Each "What It Is" and "How It Helps PAI" field MUST be 16-32 words. Count them. If under 16, add specificity. If over 32, condense.


This skill embodies PAI's commitment to continuous, personalized improvement - understanding YOU first, then discovering what's new, then EXTRACTING the actual techniques that matter to your system.

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

04

需要参考平台分布和安装热度时

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

Claude Code

28.48%
按下载量换算177

Gemini CLI

26.61%
按下载量换算166

OpenCode

19.22%
按下载量换算120

github-copilot

13.08%
按下载量换算81

clawdbot

7.84%
按下载量换算49

Cursor

3.41%
按下载量换算21

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

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