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Agent Skill · 研究检索

code-audit-readonly(代码审核只读)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

code-audit-readonly 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,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 62,001。

总安装 343周安装 14GitHub Stars 公开资料未说明下载 111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:code-audit-readonly(代码审核只读)
来源仓库:https://github.com/jpkovas/code-audit-readonly
仓库路径:skills/code-audit-readonly
安装命令:
npx skills add https://github.com/jpkovas/code-audit-readonly --skill code-audit-readonly
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/jpkovas/code-audit-readonly --skill code-audit-readonly

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。

以只读模式执行完整技术仓库审核,输出至 improvements.md。禁止修改源码或配置文件,仅允许创建审计记录文件。适用于生产环境前的安全合规检查,避免意外变更。执行前无需确认,但需确保具备足够读取权限。code-audit-readonly 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/code-audit-readonly

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/jpkovas/code-audit-readonly --skill code-audit…;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

    它需要接触敏感数据,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

code-audit-readonly 怎么安装?

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

code-audit-readonly 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。

code-audit-readonly 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

code-audit-readonly 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。

code-audit-readonly 用的人多吗?

公开数据是累计安装 343 次,近一周安装 14 次,下载 111 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。

code-audit-readonly 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
code-audit-readonly

代码审核只读 · 本页

343—接触敏感数据未明确未通过

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

Code Audit Readonly

Run a full technical repository audit in read-only mode and record everything in improvements.md.

Mandatory rules

  1. Operate in read-only mode for the audited project.
  2. Do not edit source code, configs, or tests in the audited project.
  3. Do not run automatic refactors, formatters that write to disk, or destructive commands.
  4. Allow only the creation/update of improvements.md as the final audit output.
  5. Do not ask for confirmation to proceed with the audit; execute the plan end to end.
  6. Record every validated finding; do not impose arbitrary limits.
  7. If multiple locations share the same issue pattern, still register every location with explicit file and line references.
  8. This audit is intentionally slow: prioritize depth, evidence quality, and completeness over speed.
  9. Do not optimize for fast turnaround if that reduces analysis coverage or confidence.
  10. Never reproduce secrets or raw credential material in improvements.md, tool output, or final responses.
  11. For secret-related findings, record only the file path, line range, secret class, and sanitized context needed to explain the risk.
  12. Do not quote full offending lines when they contain tokens, keys, passwords, cookies, connection strings, private keys, or other sensitive values.

Sensitive data handling

Apply these rules whenever the audit touches credentials, secrets, or other sensitive material:

  1. Treat any suspected secret as high-risk content that must stay redacted.
  2. Confirm the issue via read-only inspection, but never echo the literal value back to the user.
  3. Describe the finding with neutral placeholders such as <redacted-api-key> or <redacted-private-key> only when a placeholder is necessary.
  4. Prefer descriptions like hardcoded API credential in config bootstrap over copying the surrounding source line.
  5. If a log, error, or telemetry path leaks sensitive data, describe the leaked data class and exposure path without reproducing payload contents.
  6. Keep traceability through file paths and line ranges, not through verbatim secret material.

Mandatory analysis scope

  1. Correctness and logic

1. Detect obvious and subtle bugs. 2. Check for race conditions, inconsistent states, and incorrect async/concurrency usage. 3. Evaluate error/exception handling, nullability, typing, and unsafe conversions. 4. Cover edge flows and extreme scenarios.

  1. Performance

1. Find unnecessary allocations, expensive loops, N+1 patterns, excessive I/O, and repeated work. 2. Check for caching opportunities and inappropriate data structures. 3. Correlate bottlenecks across modules.

  1. Duplication and maintainability

1. Detect literal duplication and logical duplication. 2. Identify long functions, mixed responsibilities, and excessive coupling. 3. Flag confusing internal APIs, ambiguous names, and outdated comments.

  1. Security (mandatory, thorough)

1. Hardcoded secrets (tokens, keys, passwords, sensitive endpoints), reported with redacted descriptions only. 2. Injection vectors (SQL/NoSQL/command/template). 3. XSS, CSRF, SSRF, open redirect, path traversal. 4. Insecure uploads (insufficient type/size/validation checks). 5. Authentication/authorization issues (bypass, missing checks, privilege escalation). 6. Insufficient validation/sanitization. 7. Weak cryptography and inadequate hashing. 8. Insecure configurations (overly broad CORS, missing headers, debug in production). 9. Vulnerable dependencies and problematic versions. 10. Sensitive data leakage in logs, errors, and telemetry.

  1. Observability and reliability

1. Validate log quality without exposing secrets. 2. Verify metrics/tracing where applicable. 3. Evaluate consistency and actionability of error messages.

  1. Tests and quality

1. Identify coverage gaps in critical areas. 2. Detect brittle tests and missing integration coverage. 3. Map untested edge cases.

Execution method

  1. Map the repository tree and list all relevant files:

1. Application code, internal libraries, configs, scripts, CI, Docker, IaC, migrations, and tests.

  1. Initialize improvements.md with:

1. A short system summary inferred from the structure. 2. A "Progress Tracking" section with all relevant files marked as pending. 3. Severity and category conventions.

  1. Review each file sequentially and deterministically:

1. Read the entire file. 2. Record specific findings and correlate with related imports/calls/contracts. 3. Update progress tracking. 4. Explicitly record: File fully reviewed: <path/to/file>. 5. Before moving to the next file, run a quick self-check for missed edge cases, security vectors, and cross-file impacts.

  1. Run read-only auxiliary checks when useful:

1. Static analysis, linter, and typecheck in read-only mode. 2. Run tests without writing to disk. 3. Dependency/CVE audit.

  1. Close improvements.md with:

1. A complete finding inventory (all findings captured during the audit). 2. A prioritized backlog that references finding IDs and contains no artificial cap. 3. A detailed phased remediation plan (see "Detailed planning requirements"). 4. A brief completeness checkpoint describing what was verified to ensure no relevant area was rushed or skipped.

Progress tracking

Apply these rules to keep progress tracking clear and stable:

  1. Build a canonical file list once:

1. Normalize paths (./ removed, no trailing slash, consistent case as seen on disk). 2. Sort the list before writing "Progress Tracking".

  1. Keep exactly one progress row per canonical file path.
  2. Update progress in-place:

1. Change the existing row status (pending -> in_progress -> reviewed). 2. Never append a second row for the same file.

  1. Write File fully reviewed: <path/to/file> exactly once per file.
  2. If a file is revisited, add notes under the same file entry; do not create a new checklist row or a second File fully reviewed line.
  3. Before finishing, validate:

1. Number of reviewed rows == number of unique relevant files. 2. "Progress Tracking" appears exactly once in the report. 3. Every finding location appears in at least one reviewed file entry.

Example report structure

Use this high-level structure to keep the report consistent and to ensure a single "Progress Tracking" section:

# improvements.md

## 1. System summary
- Inferred architecture and main modules.
- Main risk surfaces.

## 2. Conventions
- Categories and severity scale used in the audit.
- Finding ID convention (`A001`, `A002`, ...).

## 3. Progress Tracking
- [ ] path/to/file-a.ext
- [ ] path/to/file-b.ext
- [ ] path/to/file-c.ext

## 4. Complete finding inventory
### A001
Category: ...
Severity: ...
Location: ...
Problem: ...
Impact: ...
Suggestion: ...
Correlation notes: ...
Security (if applicable): ...

### A002
...

## 5. Prioritized backlog (all findings)
- Priority 1: A00X, A00Y...
- Priority 2: A00Z...

## 6. Detailed phased remediation plan
### Phase 1
- Objective
- Findings included
- Dependencies
- Validation gates
- Exit criteria

### Phase 2
...

### Phase 3
...

Categories and severity

Use only these categories:

  • Bug
  • Performance
  • Security
  • Duplication
  • Code Quality
  • Architecture
  • Maintainability
  • Observability
  • Tests
  • Dependencies

Use only these severity levels:

  • Critical
  • High
  • Medium
  • Low

Mandatory format for each finding

Use unique sequential IDs (A001, A002,...).

A0XX
Category: <...>
Severity: <Critical|High|Medium|Low>
Location: <file>:<start line>-<end line>
Problem: <objective description>
Impact: <real or potential impact>
Suggestion: <high-level fix, without editing code>
Correlation notes: <related files/flows>
Security (if applicable): <plausible abuse scenario + mitigation>

For secret-related findings, keep the same structure but never include the raw secret value or paste the full source line. Use file and line references plus sanitized descriptions only.

Detailed planning requirements

The planning phase in improvements.md must be explicit and implementation-oriented. Use this structure:

  1. Planning assumptions and constraints:

1. Confirm read-only audit boundaries. 2. List unknowns that may affect remediation sequencing.

  1. Prioritized backlog (complete):

1. Include all findings (A001...A0XX) with: 1. Priority order. 2. Estimated effort (S, M, L) with a short rationale. 3. Primary risk type (Correctness, Security, Performance, Reliability, Maintainability).

  1. Phase plan with objective and controls:

1. For each phase, include: 1. Objective. 2. Findings included (explicit ID list). 3. Dependencies and ordering constraints. 4. Validation gates (tests/checks/evidence expected after fixes). 5. Exit criteria (what must be true to close the phase).

  1. Sequencing rules:

1. Resolve Critical and exploitable High security/correctness findings first. 2. Schedule performance and maintainability work after risk containment unless blocking. 3. Call out parallelizable workstreams and non-parallelizable bottlenecks.

  1. Delivery roadmap:

1. Provide a suggested execution order by batch/wave. 2. For each batch, list expected risk reduction and verification focus.

Traceability requirements

  1. Make every finding traceable to file and line/section.
  2. Avoid generic recommendations without evidence.
  3. Register all validated findings found during the audit, including low-severity and repeated-location findings.
  4. Explicitly record uncertainties when evidence is partial.
  5. For sensitive findings, preserve traceability with file and line references while keeping all credential material redacted.

Completion criteria

Finish only when:

  1. All relevant files are marked as reviewed in Progress Tracking.
  2. Each reviewed file has the line File fully reviewed:....
  3. improvements.md contains the complete finding inventory, a prioritized backlog, and a detailed phased plan.
  4. The audited project remains intact, with only improvements.md as the audit output artifact.

平台分布

Codex

36.36%
按下载量换算40

Claude

26.51%
按下载量换算29

Cursor

18.59%
按下载量换算21

Gemini CLI

9.58%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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