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Agent Skill · 研究检索

aeo-escalation(航空航天升级)

aeo-escalation 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。

aeo-escalation 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 64,698。

总安装 294周安装 12GitHub Stars 公开资料未说明下载 94核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:aeo-escalation(航空航天升级)
来源仓库:https://github.com/ivzc07/aeo-skills
仓库路径:skills/aeo-escalation
安装命令:
npx skills add https://github.com/ivzc07/aeo-skills --skill aeo-escalation
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/ivzc07/aeo-skills --skill aeo-escalation

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

AEO 升级助手用于在置信度低或关键问题出现时发起人工介入请求。适用于任务失败、成本超限或架构违规等需要决策支持的复杂场景。提供标准化的升级模板,记录上下文与可选方案,便于团队协作处理。安装前建议检查维护状态,确认是否涉及敏感信息或生产环境操作。

aeo-escalation 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/aeo-escalation

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ivzc07/aeo-skills --skill aeo-escalation;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

aeo-escalation 怎么安装?

在终端执行 npx skills add https://github.com/ivzc07/aeo-skills --skill aeo-escalation。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

aeo-escalation 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

aeo-escalation 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

aeo-escalation 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

aeo-escalation 用的人多吗?

公开数据是累计安装 294 次,近一周安装 12 次,下载 94 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

aeo-escalation 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
aeo-escalation

航空航天升级 · 本页

294—需要联网MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

AEO Escalation

Purpose: Human-AI interface for when to interrupt and involve humans. Presents clear, actionable options and records decisions for learning.

When to Escalate

Invoke this skill when:

  • Confidence score < 0.70 (advisory/blocking from aeo-core)
  • Spec score < 40 (refuse from aeo-spec-validator)
  • QA veto occurs (from aeo-qa-agent)
  • Failure pattern can't be resolved (from aeo-failure-patterns)
  • Cost limit approaching (if cost-governor enabled)
  • Architecture violation detected (if architecture skill enabled)

Escalation Framework

All escalations must follow this format:

⚠️ ESCALATION REQUIRED

[Clear one-line summary of the issue]

Context:
• [Why we're here - what triggered escalation]
• [What we've tried so far]
• [What's blocking progress]

Options:
1. [Clear, actionable option] - [Expected outcome]
2. [Clear, actionable option] - [Expected outcome]
3. [Clear, actionable option] - [Expected outcome]

Recommended: [Option X] - [Brief rationale]

Your choice (1-3):

Escalation Scenarios

Scenario 1: Low Confidence (Blocking)

Trigger: Confidence 0.50-0.69

⚠️ CONFIDENCE BELOW THRESHOLD

Confidence: 0.62
Threshold: 0.70 (Autonomous)

Task: Add user authentication with email verification

Context:
• Spec score: 68/100 (minor gaps)
• Risk: Touching authentication system
• Missing: Email service configuration
• Similar tasks: 2 successful, 1 failed

Concerns:
• [Spec] No email service specified
• [Risk] Auth changes require review
• [Context] Need email provider details

Options:
1. Proceed with Resend for emails (default) - Autonomously complete with assumptions
2. Provide email service details first - Improve spec, then execute autonomously
3. Break into smaller tasks - Create subtasks for review and approval

Recommended: Option 2 - Specify email service to improve confidence

Your choice (1-3):

After user responds:

  • Record decision to $PAI_DIR/MEMORY/aeo-escalations.jsonl
  • Update confidence model based on outcome
  • Continue with chosen path

Scenario 2: Spec Refused (Unacceptable)

Trigger: Spec score < 40

❌ CANNOT EXECUTE - SPEC TOO UNCLEAR

Spec Score: 28/100
Threshold: 40 (Minimum)

Task: Improve the signup

Why this was refused:
• Objective vague (5/15) - "improve" is subjective
• No acceptance criteria (0/15) - What defines "done"?
• Missing context (0/10) - Which signup flow?
• No dependencies listed (0/10)
• Ambiguity penalty: -10 (vague verb "improve")

What's needed:
1. **Clear Objective:** What specific improvement?
2. **Acceptance Criteria:** How do we measure success?
3. **Context:** Which page/component?
4. **Dependencies:** Libraries, APIs, services?

Good spec example:
"Add email validation to /pages/auth/signup.tsx using validator.js.
 Must validate RFC 5322, reject + aliases, show inline errors.
 Tests for valid, invalid, duplicate emails."

Options:
1. Provide improved spec - I'll wait for your updated specification
2. Answer clarifying questions - I'll ask specific questions to build spec
3. Use template - I'll provide a spec template for you to fill

Recommended: Option 2 - Answer questions to build spec together

Your choice (1-3):

Scenario 3: QA Veto (Security Issue)

Trigger: Security vulnerability detected

🚨 SECURITY VETO - CANNOT PROCEED

Issue: SQL Injection vulnerability
File: /routes/users.js:Line 47
Severity: CRITICAL

Current Code:

const query = SELECT * FROM users WHERE id = ${userId}


Why this is dangerous: • User input directly interpolated into SQL query • Attacker can execute arbitrary SQL commands • Can expose, modify, or delete all data

Required Fix:

const query = 'SELECT * FROM users WHERE id = $1' await db.query(query, [userId])


Action Required: • This MUST be fixed before commit • No exceptions - security is non-negotiable • All changes with security issues are blocked

Options:

1. Fix immediately - I'll apply the required fix now
2. Review fix together - I'll show you the fix for approval
3. Explain more - I'll provide detailed explanation of vulnerability

Recommended: Option 1 - Fix immediately (this is a critical issue)

Your choice (1-3):

Scenario 4: Failure Pattern Not Recognized

Trigger: Error not in core patterns or project patterns


❌ CANNOT AUTO-FIX - PATTERN NOT RECOGNIZED

Error: TypeError: Cannot read properties of undefined (reading 'data')

Searched: • 20 core patterns - No match • 12 project patterns - No match • Fuzzy match: None with confidence ≥ 0.70

Context: • File: /src/services/UserService.js:125 • Function: fetchUserData() • Error occurred during: API call processing

Stack trace: TypeError: Cannot read properties of undefined (reading 'data') at UserService.fetchUserData (/src/services/UserService.js:125) at async Component.render (/src/components/UserList.tsx:45)

What I've tried: • Verified module is installed ✓ • Checked imports - all valid ✓ • Reviewed recent changes - no obvious issues ✗

Options:

1. Provide fix - If you know the solution, I'll apply it
2. Investigate together - I'll add logging and we'll debug
3. Create new pattern - After we fix it, I'll save this pattern for future

Recommended: Option 2 - Investigate together to understand root cause

Your choice (1-3):

Scenario 5: Cost Limit Warning

Trigger: Budget 80% consumed


⚠️ COST LIMIT APPROACHING

Budget Status: • Daily budget: $10.00 • Used so far: $8.47 (84.7%) • Remaining: $1.53 • Tasks completed: 7

Current task estimate: ~$0.75 Projected overage: ~$0.22 if we continue

Options:

1. Continue anyway - Proceed with current task (may exceed budget)
2. Pause and review - Review completed work, decide what's essential
3. Adjust scope - Complete current task with reduced scope

Recommended: Option 2 - Review progress before continuing

Your choice (1-3):

Scenario 6: Architecture Violation

Trigger: Circular dependency detected


⚠️ ARCHITECTURE VIOLATION DETECTED

Issue: Circular dependency between modules

Circular Path: → fileA.js imports fileB.js → fileB.js imports fileA.js → (cycle detected)

Why this matters: • Creates tight coupling • Makes code hard to test • Can cause runtime errors • Violates clean architecture principles

Options:

1. Extract shared code - Create new module for shared functionality
2. Refactor dependencies - Restructure to remove cycle
3. Defer to architect - Let architecture skill analyze and propose solution

Recommended: Option 1 - Extract shared code (most common pattern)

Your choice (1-3):

Decision Recording

After human chooses an option, record to memory:

# Append to escalation log
echo '{
  "timestamp": "$(date -u +%Y-%m-%dT%H:%M:%SZ)",
  "task_id": "unique-id",
  "escalation_type": "low_confidence|spec_refused|qa_veto|pattern_unknown|cost_warning|arch_violation",
  "confidence_before": 0.62,
  "option_presented": [1, 2, 3],
  "option_chosen": 2,
  "human_input": "User provided email service details",
  "resolution": "Improved spec, confidence increased to 0.85",
  "success": true,
  "learning": "Context details improve confidence by ~0.20"
}' >> ~/.claude/MEMORY/aeo-escalations.jsonl

Learning from Escalations

Weekly Analysis:

# Read escalation patterns
jq -s 'group_by(.escalation_type) | map({type: .[0].escalation_type, count: length})' \
  ~/.claude/MEMORY/aeo-escalations.jsonl

Insights to track:

  • Most common escalation types
  • Which options are chosen most frequently
  • Average confidence after escalation
  • Resolution time
  • Success rate of different options

Integration Flow

  1. Trigger received from another AEO skill
  2. Format escalation with clear options
  3. Present to human with recommended option
  4. Wait for response
  5. Record decision to memory
  6. Execute chosen option
  7. Follow up - Was the resolution successful?
  8. Learn - Update escalation patterns

Best Practices

DO:

  • Always provide 2-4 clear, actionable options
  • Include a recommended option with rationale
  • Explain context clearly (what led to escalation)
  • Keep options mutually exclusive
  • Make options specific and actionable
  • Record outcome for future learning

DON'T:

  • Present vague options like "continue or stop"
  • Overwhelm with >4 options
  • Skip the recommendation
  • Forget to explain the context
  • Present options that aren't actually available
  • Skip recording the outcome

Example Session

AEO-Core: Confidence 0.52 - below threshold
        [Invokes aeo-escalation]

Escalation: ⚠️ CONFIDENCE BELOW THRESHOLD

           Confidence: 0.52
           Threshold: 0.70

           Task: Refactor authentication system

           Concerns:
           • [Spec] No clear requirements defined
           • [Risk] Touching critical auth system
           • [Scope] Large, unclear boundaries

           Options:
           1. Define requirements first - Create detailed spec
           2. Break into smaller tasks - Create manageable subtasks
           3. Get architect approval - Ensure approach is sound

           Recommended: Option 1 - Define requirements

Human: 1

Escalation: [Recording choice]
           What specific requirements do you need documented?

Human: We need to support OAuth, JWT, and API keys

Escalation: [Updating spec]
           [Recalculating confidence...]
           New confidence: 0.78 ✓

           Proceeding with implementation.

[Records to memory: escalation_type=low_confidence, option_chosen=1, success=true]

Escalation Outcomes

Track outcomes to improve escalation quality:

Successful Outcomes:

  • Human provides needed info → Task completes
  • Issue resolved → Continue autonomously
  • Learning captured → Better future decisions

Unsuccessful Outcomes:

  • Wrong option recommended → Adjust recommendation logic
  • Unclear options → Improve option clarity
  • Missing context → Add more context to escalation
  • Repeated escalations → Identify root cause

Use outcomes to refine escalation patterns and recommendations.

平台分布

Claude Code

33.22%
按下载量换算31

OpenCode

21.89%
按下载量换算21

Codex

17.64%
按下载量换算17

windsurf

12.6%
按下载量换算12

trae

7.43%
按下载量换算7

Cursor

3.23%
按下载量换算3

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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