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Agent Skill · 研究检索

integrity(integrity 搜索)

integrity 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。

integrity 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,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 67,721。

总安装 242周安装 10GitHub Stars 9下载 79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
unknown

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:integrity(integrity 搜索)
来源仓库:https://github.com/florianbuetow/claude-code
仓库路径:skills/integrity
安装命令:
npx skills add https://github.com/florianbuetow/claude-code --skill integrity
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/florianbuetow/claude-code --skill integrity

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。

用于基于关键词检索和筛选相关信息源。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。适合在知识库或文档集合中快速定位候选内容。可自定义相关性评分和来源优先级规则。输出结果建议人工二次验证准确性。

integrity 属于研究检索类 Skill,可作为该场景下的辅助能力补充。注意该技能可能访问外部网站并产生网络请求。

来源仓库内路径:skills/integrity

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/florianbuetow/claude-code --skill integrity;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

    它需要调用外部服务,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

integrity 怎么安装?

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

integrity 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。

integrity 需要什么权限?

权限级别是调用外部服务。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。

integrity 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

integrity 用的人多吗?

公开数据是累计安装 242 次,近一周安装 10 次,下载 79 次,GitHub 9 星。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。

integrity 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
integrity

integrity 搜索 · 本页

2429调用外部服务未明确有提醒

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

Software and Data Integrity Failures

Analyze source code, CI/CD configurations, and dependency manifests for integrity violations. Detect insecure deserialization, unverified auto-updates, missing subresource integrity, CI/CD pipeline injection, and untrusted dependency sources. Produce actionable findings with severity ratings, code locations, and concrete remediation steps.

Supported Flags

All flags from ../../shared/schemas/flags.md are supported:

FlagRelevant Behavior
--scope <value>Determines which files to analyze (default: changed)
--depth <value>quick: pattern scan only. standard: full read + analysis. deep: trace data flows and dependency chains cross-file. expert: red team simulation with DREAD scoring
--severity <value>Filter findings by minimum severity
--format <value>Output format: text, json, sarif, md
--fixChain into remediation after analysis
--quietFindings only, no explanations
--explainAdd learning context to each finding

Framework Context

OWASP Top 10 2021 - A08: Software and Data Integrity Failures

Code and infrastructure that does not protect against integrity violations. This category covers a broad set of concerns around trusting the provenance and authenticity of software, data, and infrastructure:

  • Relying on plugins, libraries, or modules from untrusted sources, repositories, or CDNs
  • Insecure CI/CD pipelines that allow unauthorized code or configuration changes
  • Auto-update functionality that downloads and applies updates without integrity verification
  • Insecure deserialization where untrusted data is deserialized into objects, enabling remote code execution, replay attacks, injection, or privilege escalation

STRIDE Mapping: Tampering, Elevation of Privilege

CWE References: CWE-502 (Deserialization of Untrusted Data), CWE-829 (Inclusion of Functionality from Untrusted Control Sphere), CWE-494 (Download of Code Without Integrity Check), CWE-915 (Improperly Controlled Modification of Dynamically-Determined Object Attributes), CWE-353 (Missing Support for Integrity Check)

Detection Patterns

Read references/detection-patterns.md before performing analysis. It contains detailed Grep heuristics, language-specific code examples, scanner coverage, and false positive guidance for each vulnerability pattern.

Workflow

1. Determine Scope

Parse --scope flag and resolve to a concrete file list:

  1. Apply scope resolution per ../../shared/schemas/flags.md.
  2. Filter to files relevant to integrity:

- Serialization/deserialization code (data processing, API handlers) - CI/CD configuration files (.github/workflows/*.yml, .gitlab-ci.yml, Jenkinsfile, .circleci/config.yml, azure-pipelines.yml, bitbucket-pipelines.yml) - Dependency manifests and lockfiles (package.json, package-lock.json, yarn.lock, requirements.txt, Pipfile.lock, go.sum, Cargo.lock, pom.xml, build.gradle) - HTML files with CDN script/link tags - Update/installer scripts and auto-update mechanisms - Pre/post-install hooks in package configurations - Dockerfile and container build configurations

  1. Include infrastructure-as-code files that reference external resources or images.

2. Check for Scanners

Detect available scanners in order of preference:

ScannerDetectRelevant Rules
semgrepwhich semgrepInsecure deserialization, unsafe YAML/pickle loading
trivywhich trivyDependency vulnerabilities, misconfigurations, secret detection
osv-scannerwhich osv-scannerKnown vulnerabilities in dependencies across ecosystems
checkovwhich checkovCI/CD misconfigurations, IaC integrity issues
banditwhich banditPython-specific: pickle, yaml, marshal (B301, B506)

If no scanner is available, proceed with Claude analysis using Grep patterns from references/detection-patterns.md. Note in output: "No scanner available -- findings based on code pattern analysis only."

3. Run Scanners

For each available scanner:

  1. Execute against the scoped file list.
  2. Parse JSON output.
  3. Filter to integrity-related rules only.
  4. Normalize findings to the schema in ../../shared/schemas/findings.md.
  5. Set scanner.confirmed: true for scanner-detected findings.

4. Claude Analysis

Regardless of scanner availability, perform manual code analysis:

  1. Read references/detection-patterns.md for the full pattern catalog.
  2. Use Grep with the regex patterns to locate suspicious constructs.
  3. Read surrounding code context (30-50 lines) to assess each match.
  4. Trace data flows from untrusted sources to deserialization sinks.
  5. At --depth deep or higher: follow imports, trace dependency chains, analyze CI/CD workflow trigger conditions and secret exposure, map update mechanisms end-to-end.
  6. Deduplicate against scanner findings (same file + line = same finding).
  7. Set confidence: medium for Claude-only findings, confidence: high when confirmed by a scanner.

5. Report Findings

Format output per --format flag. Each finding uses the schema from ../../shared/schemas/findings.md with these specifics:

  • ID prefix: INTEG (e.g., INTEG-001, INTEG-002)
  • references.owasp: A08:2021
  • references.stride: T (Tampering) or E (Elevation of Privilege)
  • metadata.tool: integrity
  • metadata.framework: owasp
  • metadata.category: A08

Summary block (appended after all findings):

## Summary

| Severity | Count |
|----------|-------|
| CRITICAL | N     |
| HIGH     | N     |
| MEDIUM   | N     |
| LOW      | N     |

**Scanners used**: [list or "none"]
**Scanners missing**: [list of recommended but unavailable]
**Top priorities**: [top 3 findings to fix first and why]

What to Look For

These are the primary vulnerability patterns. See references/detection-patterns.md for detailed regex patterns and code examples.

  1. Insecure deserialization -- Using pickle.loads, yaml.load (without SafeLoader), Java ObjectInputStream, or JSON.parse on untrusted input to reconstruct objects that can execute arbitrary code.
  2. CI/CD pipeline injection -- GitHub Actions or other CI workflows that interpolate untrusted input (PR titles, branch names, issue bodies) into run: blocks, enabling command injection in the build environment.
  3. CDN resources without SRI -- Loading JavaScript or CSS from third-party CDNs without integrity attributes, allowing a compromised CDN to inject malicious code.
  4. Auto-update without verification -- Download-and-execute update mechanisms that do not verify digital signatures or checksums before applying updates.
  5. Malicious pre/post-install scripts -- Package configurations with install hooks that execute arbitrary code during npm install, pip install, or similar commands.
  6. Missing lockfile integrity -- Dependency lockfiles absent from version control or containing no integrity hashes, allowing silent dependency substitution.
  7. Untrusted base images -- Dockerfiles using unverified or untagged base images (e.g., FROM node instead of FROM node:20-alpine@sha256:...).
  8. Missing code signing -- Release artifacts, packages, or binaries distributed without digital signatures.

Scanner Integration

Refer to ../../shared/schemas/scanners.md for full scanner details.

Primary: trivy (dependency vulnerabilities, misconfigurations), osv-scanner (cross-ecosystem CVEs) Secondary: semgrep (deserialization patterns), bandit (Python pickle/YAML), checkov (CI/CD configs) Fallback: Grep-based pattern matching from references/detection-patterns.md plus Claude analysis of CI/CD configs and dependency manifests

When running as a subagent of the OWASP dispatcher, receive scope and flags from the parent agent prompt. Do not re-parse user input.

Output Format

All findings conform to the schema defined in ../../shared/schemas/findings.md.

ID prefix: INTEG (registered in the ID Prefix Registry as OWASP A08)

Example finding:

{
  "id": "INTEG-001",
  "title": "Unsafe pickle deserialization of user-uploaded data",
  "severity": "critical",
  "confidence": "high",
  "location": {
    "file": "src/api/import_handler.py",
    "line": 72,
    "function": "import_data",
    "snippet": "data = pickle.loads(request.files['upload'].read())"
  },
  "description": "User-uploaded file content is deserialized with pickle.loads, which can execute arbitrary Python code embedded in the pickle stream.",
  "impact": "An attacker can upload a crafted pickle file to achieve remote code execution on the server, potentially compromising the entire application and underlying infrastructure.",
  "fix": {
    "summary": "Replace pickle with a safe serialization format like JSON",
    "diff": "- data = pickle.loads(request.files['upload'].read())\n+ data = json.loads(request.files['upload'].read())"
  },
  "references": {
    "cwe": "CWE-502",
    "owasp": "A08:2021",
    "stride": "T",
    "mitre_attck": "T1059"
  },
  "scanner": {
    "name": "bandit",
    "rule": "B301",
    "confirmed": true
  },
  "metadata": {
    "tool": "integrity",
    "framework": "owasp",
    "category": "A08"
  }
}

平台分布

Codex

36.56%
按下载量换算29

Claude

26.78%
按下载量换算21

Cursor

18.44%
按下载量换算15

Gemini CLI

9.56%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

调用外部服务

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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