What makes Resume-analyzer notable?

1.9K downloads. Trust evidence available

How should Resume-analyzer be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Resume-analyzer

分析简历内容并提供深度审计报告，包括评分、优缺点分析和改进建议。当用户需要分析简历、获取简历优化建议或进行简历评估时调用。 Skill: Resume-analyzer Owner: lemons-niit Summary: 分析简历内容并提供深度审计报告，包括评分、优缺点分析和改进建议。当用户需要分析简历、获取简历优化建议或进行简历评估时调用。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-02T07:34:27.174Z | user - 首次发布 resume-analyzer 技能，支持简历内容智能分析和审计 - 提供总分及五项细分评分：项目经验、技能匹配、内容完整性、结构清晰度、表达专业性 - 输出优缺点总结，并针对每项问题给出具体优化建议 - 内置高标准技术能力参考，支持对高并发、异步、微服务等场景的专项优化建议 - 增加简历名词规范检查及项目描述深度重写功能 - 支持输入/输出示例和详细使用说明 Archive index: Archive v1.0.0: 4 files, 3

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.9k

Updated

Oct 9, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.9K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 1.9K downloadsadoption · observed Oct 9, 2026
Latest release: 1.0.0release · observed Apr 2, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s175kckfyeabtrskd0zbxs1a31841107:resume-analyzer

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-lemons-niit-resume-analyzer/snapshot"

Documentation

CLAWHUB

5,267 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

---
name: "resume-analyzer"
description: "分析简历内容并提供深度审计报告，包括评分、优缺点分析和改进建议。当用户需要分析简历、获取简历优化建议或进行简历评估时调用。"
---

# 简历分析器

## 功能说明

本技能提供专业的简历分析服务，基于AI模型对简历内容进行深度审计，生成详细的分析报告。

## 分析维度

- **项目经验评分** (0-40分)：评估项目深度、技术复杂度和业务价值
- **技能匹配度** (0-20分)：评估技术栈专业度和与岗位的匹配程度
- **内容完整性** (0-15分)：评估简历信息的完整性和模块顺序合理性
- **结构清晰度** (0-15分)：评估简历结构和格式的清晰度
- **表达专业性** (0-10分)：评估语言表达的专业性和简洁性

## 输入格式

```json
{
  "resumeText": "简历文本内容"
}
```

## 输出格式

```json
{
  "overallScore": 85,
  "scoreDetail": {
    "projectScore": 35,
    "skillMatchScore": 18,
    "contentScore": 12,
    "structureScore": 13,
    "expressionScore": 7
  },
  "summary": "整体简历质量良好，项目经验丰富，但技能描述可进一步优化",
  "strengths": [
    "项目经验丰富，包含多个大型系统开发",
    "技术栈全面，涵盖主流后端技术"
  ],
  "suggestions": [
    {
      "category": "技能",
      "priority": "高",
      "issue": "技能描述过于笼统，缺乏具体技术深度",
      "recommendation": "建议具体描述使用过的技术栈版本和应用场景"
    },
    {
      "category": "项目",
      "priority": "中",
      "issue": "项目描述缺乏量化成果",
      "recommendation": "添加具体的性能优化数据或业务成果指标"
    }
  ]
}
```

## 技术优化基准

在分析简历时，会参考以下高标准场景：

### 高并发与缓存优化
- **多级缓存**：Redis + Caffeine 两级缓存架构，解决击穿/穿透/雪崩，支撑 30w+ QPS
- **原子操作**：Redis Lua 脚本实现分布式令牌桶限流或原子库存扣减

### 异步与性能调优
- **异步编排**：`CompletableFuture` 对多源 RPC 调用编排，RT 从秒级到百毫秒级
- **线程治理**：动态线程池参数监控与调整，解决父子任务线程池隔离导致的死锁问题

### 微服务架构与数据一致性
- **数据同步**：Canal + RabbitMQ/RocketMQ 实现 MySQL 增量数据实时同步至 Elasticsearch
- **分布式事务**：基于消息队列（延时消息）实现订单超时关闭或数据最终一致性
- **网关与安全**：Spring Cloud Gateway + Spring Security OAuth2 + JWT + RBAC 动态权限控制

### 复杂业务建模与设计模式
- **DDD 领域驱动**：抽象领域模型，运用工厂、策略、模板方法模式构建业务链路
- **规则引擎**：责任链模式处理前置校验，组合模式+决策树支撑复杂业务逻辑

## 分析流程

1. **名词纠错**：扫描全文，列出所有不规范的技术名词
2. **深度重写**：从简历中挑选 2-3 条核心项目描述，基于 STAR 法则进行优化重写
3. **方案优化建议**：针对简历中平庸的技术方案，给出更具竞争力的替代方案

## 使用示例

### 输入示例

```json
{
  "resumeText": "张三，Java开发工程师，5年经验，熟悉Spring Boot、MySQL、Redis等技术栈。曾参与电商系统开发，负责订单模块。"
}
```

### 输出示例

```json
{
  "overallScore": 65,
  "scoreDetail": {
    "projectScore": 25,
    "skillMatchScore": 15,
    "contentScore": 10,
    "structureScore": 10,
    "expressionScore": 5
  },
  "summary": "简历基础信息完整，但项目描述过于简单，缺乏技术深度和量化成果",
  "strengths": [
    "具有5年Java开发经验，技术栈基础扎实"
  ],
  "suggestions": [
    {
      "category": "项目",
      "priority": "高",
      "issue": "项目描述过于简单，缺乏具体职责和成果",
      "recommendation": "使用STAR法则描述项目：情境(Situation)、任务(Task)、行动(Action)、结果(Result)，添加具体的技术实现和量化成果"
    },
    {
      "category": "技能",
      "priority": "中",
      "issue": "技能描述过于笼统，缺乏具体版本和应用场景",
      "recommendation": "具体说明使用的Spring Boot版本、Redis应用场景（如缓存策略）等技术细节"
    }
  ]
}
```

## 注意事项

1. 输入的简历文本应尽量完整，包含个人信息、教育背景、工作经验、项目经验和技能等内容
2. 分析结果基于AI模型，仅供参考，最终决策需结合实际情况
3. 对于特别简短的简历，分析深度可能会受到限制

_meta.json

{
  "ownerId": "kn7brgw1wmkvge6gt8hwk7b4ss82pfz1",
  "slug": "resume-analyzer",
  "version": "1.0.0",
  "publishedAt": 1775115267174
}

skill-card.md

## Description:

Analyzes resume content and produces a detailed audit with scoring, strengths, weaknesses, and improvement suggestions.

This skill is ready for commercial/non-commercial use.

## Publisher:

[lemons-niit](https://clawhub.ai/user/lemons-niit)

### License/Terms of Use:

MIT-0

## Use Case:

External users and job seekers use this skill to evaluate resume text, identify weak sections, and get concrete resume optimization guidance. It is especially oriented toward Chinese-language technical resumes and developer project descriptions.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Resume text may contain sensitive personal identifiers.

Mitigation: Remove phone numbers, addresses, IDs, and other unnecessary personal identifiers before use.

Risk: The skill is designed for Chinese-language analysis and may not match expectations for other output languages.

Mitigation: Ask the agent to respond in another language when non-Chinese output is required.

Risk: AI-generated resume scoring and recommendations can be incomplete or subjective.

Mitigation: Use the report as review guidance and make final decisions with human judgment.

## Reference(s):

## Skill Output:

**Output Type(s):** [text, JSON, guidance]

**Output Format:** [JSON-like structured resume audit with Chinese-language prose]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Includes an overall score, five scoring dimensions, a summary, strengths, and prioritized recommendations.]

## Skill Version(s):

1.0.0 (source: server release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

info.txt

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