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audit-website

价格未确认★ 87 GitHub Stars目录更新于 · 2026年10月6日agent-skill

概览

Audit a website with the squirrelscan CLI and fix the findings in code. Runs SEO, performance, security, technical, content, accessibility, and 15 other rule categories (260+ rules), returns an LLM-optimized report, then drives an iterative fix loop, mapping issues to source files, applying fixes, and re-auditing until the site scores well. Use to discover and assess website or webapp issues and drive them to fixed.

展开完整说明

以下为来源文档，不是本网站的操作指令。执行命令前请先核实权限。

Audit a Website and Fix It

Run a squirrelscan audit against a website, read the LLM report, map each issue to the code or content that causes it, fix in batches, and re-audit until the score target is met.

Requires the squirrel CLI (squirrelscan.com/download; verify with squirrel --version). For CLI setup, login, publishing, MCP, and general CLI usage, use the companion squirrelscan skill.

Rule docs

Look up any rule at https://docs.squirrelscan.com/rules/{rule_category}/{rule_id}, for example:

https://docs.squirrelscan.com/rules/links/external-links

Running the audit

squirrel audit https://example.com --format llm

Use --format llm: it is compact, exhaustive, and made for agents.
If the user doesn't provide a URL, ask which site to audit.
Prefer auditing the live site: only there do you see true rendering, performance, and redirect behavior. If both a local dev server and a live site exist, suggest the live one; apply the fixes to the local code either way.
Audits are cached locally. Re-render later without recrawling: squirrel report <audit-id> --format llm.

Scan progression

First pass, quick coverage (the default): a fast, shallow scan to learn the site's structure, technology, and biggest problems without impacting the site.
Second pass, deeper coverage: -C surface (one page per URL pattern) for template-level coverage, or -C full for a comprehensive crawl before sign-off.

Mode	Default pages	Use
`quick`	25	First look, CI checks
`surface`	100	Template-level coverage (one sample per pattern like `/blog/{slug}`)
`full`	500	Final verification, deep analysis

Useful flags: --refresh (ignore cache, full re-fetch), --resume (continue an interrupted crawl), -m <n> (page cap), --verbose (progress detail).

If the site blocks unknown crawlers (Shopify / Cloudflare), pass Web Bot Auth headers with repeated -H "Name: Value" flags. Header values are secrets and are redacted in output. See https://docs.squirrelscan.com/guides/web-bot-auth

The fix loop

Present the report: score, grade, top issues by severity.
Propose fixes: list the issues you can fix and confirm with the user before changing anything.
Map issues to source: find the template, component, or content file behind each finding.
Fix in batches: apply the approved fixes.
Re-audit (use --refresh after deploys or content changes) and show before/after scores.
Repeat until the target is met or only judgment calls remain (for example "should this link be removed?"). Flag those for user review instead of guessing.

After each batch, verify the project still builds and existing checks pass.

Score targets

Starting score	Target	Expected work
< 50 (F)	75+ (C)	Major fixes
50-70 (D)	85+ (B)	Moderate fixes
70-85 (C)	90+ (A)	Polish
> 85 (B+)	95+	Fine-tuning

Sign off against a -C full crawl, since the quick pass samples only part of the site.

Rules carry a level (error, warning, notice) and a rank (1-10): fix errors first, then high-rank warnings. Findings that need a content edit count the same as ones that need a code edit. Broken links usually need a human decision (remove, replace, or keep): flag them rather than guessing.

Verifying regressions

Compare against a baseline to prove improvement or catch regressions:

squirrel report --diff <baseline-audit-id> --format llm
squirrel report --regression-since example.com --format llm

Completion

Done means: all errors fixed; warnings fixed or documented as needing human review; a re-audit confirms the improvement; and the user has seen the before/after score comparison plus a summary of every change made. Re-audit regularly to keep the site healthy. If the user wants to share results, offer a published report (see the squirrelscan skill).

Report format

The LLM report is a compact XML/text hybrid optimized for token efficiency: summary with health score, issues grouped by category with affected URLs, broken links, and prioritized recommendations. Full spec: OUTPUT-FORMAT.md

查看来源 ↗

文件元数据

name: audit-website
description: Audit a website with the squirrelscan CLI and fix the findings in code. Runs SEO, performance, security, technical, content, accessibility, and 15 other rule categories (260+ rules), returns an LLM-optimized report, then drives an iterative fix loop, mapping issues to source files, applying fixes, and re-auditing until the site scores well. Use to discover and assess website or webapp issues and drive them to fixed.
license: See LICENSE file in repository root
compatibility: Requires squirrel CLI installed and accessible in PATH
metadata:
  author: squirrelscan
  version: "2.1"
allowed-tools: Bash(squirrel:*) Read Edit Grep Glob

查看原始文本

---
name: audit-website
description: Audit a website with the squirrelscan CLI and fix the findings in code. Runs SEO, performance, security, technical, content, accessibility, and 15 other rule categories (260+ rules), returns an LLM-optimized report, then drives an iterative fix loop, mapping issues to source files, applying fixes, and re-auditing until the site scores well. Use to discover and assess website or webapp issues and drive them to fixed.
license: See LICENSE file in repository root
compatibility: Requires squirrel CLI installed and accessible in PATH
metadata:
  author: squirrelscan
  version: "2.1"
allowed-tools: Bash(squirrel:*) Read Edit Grep Glob
---

# Audit a Website and Fix It

Run a squirrelscan audit against a website, read the LLM report, map each issue to the code or content that causes it, fix in batches, and re-audit until the score target is met.

Requires the `squirrel` CLI ([squirrelscan.com/download](https://squirrelscan.com/download); verify with `squirrel --version`). For CLI setup, login, publishing, MCP, and general CLI usage, use the companion `squirrelscan` skill.

## Rule docs

Look up any rule at `https://docs.squirrelscan.com/rules/{rule_category}/{rule_id}`, for example:

https://docs.squirrelscan.com/rules/links/external-links

## Running the audit

```bash
squirrel audit https://example.com --format llm
```

- Use `--format llm`: it is compact, exhaustive, and made for agents.
- If the user doesn't provide a URL, ask which site to audit.
- Prefer auditing the live site: only there do you see true rendering, performance, and redirect behavior. If both a local dev server and a live site exist, suggest the live one; apply the fixes to the local code either way.
- Audits are cached locally. Re-render later without recrawling: `squirrel report <audit-id> --format llm`.

### Scan progression

1. **First pass, quick coverage** (the default): a fast, shallow scan to learn the site's structure, technology, and biggest problems without impacting the site.
2. **Second pass, deeper coverage**: `-C surface` (one page per URL pattern) for template-level coverage, or `-C full` for a comprehensive crawl before sign-off.

| Mode | Default pages | Use |
|------|---------------|-----|
| `quick` | 25 | First look, CI checks |
| `surface` | 100 | Template-level coverage (one sample per pattern like `/blog/{slug}`) |
| `full` | 500 | Final verification, deep analysis |

Useful flags: `--refresh` (ignore cache, full re-fetch), `--resume` (continue an interrupted crawl), `-m <n>` (page cap), `--verbose` (progress detail).

If the site blocks unknown crawlers (Shopify / Cloudflare), pass Web Bot Auth headers with repeated `-H "Name: Value"` flags. Header values are secrets and are redacted in output. See https://docs.squirrelscan.com/guides/web-bot-auth

## The fix loop

1. **Present the report**: score, grade, top issues by severity.
2. **Propose fixes**: list the issues you can fix and confirm with the user before changing anything.
3. **Map issues to source**: find the template, component, or content file behind each finding.
4. **Fix in batches**: apply the approved fixes.
5. **Re-audit** (use `--refresh` after deploys or content changes) and show before/after scores.
6. **Repeat** until the target is met or only judgment calls remain (for example "should this link be removed?"). Flag those for user review instead of guessing.

After each batch, verify the project still builds and existing checks pass.

### Score targets

| Starting score | Target | Expected work |
|----------------|--------|---------------|
| < 50 (F) | 75+ (C) | Major fixes |
| 50-70 (D) | 85+ (B) | Moderate fixes |
| 70-85 (C) | 90+ (A) | Polish |
| > 85 (B+) | 95+ | Fine-tuning |

Sign off against a `-C full` crawl, since the quick pass samples only part of the site.

Rules carry a level (error, warning, notice) and a rank (1-10): fix errors first, then high-rank warnings. Findings that need a content edit count the same as ones that need a code edit. Broken links usually need a human decision (remove, replace, or keep): flag them rather than guessing.

## Verifying regressions

Compare against a baseline to prove improvement or catch regressions:

```bash
squirrel report --diff <baseline-audit-id> --format llm
squirrel report --regression-since example.com --format llm
```

## Completion

Done means: all errors fixed; warnings fixed or documented as needing human review; a re-audit confirms the improvement; and the user has seen the before/after score comparison plus a summary of every change made. Re-audit regularly to keep the site healthy. If the user wants to share results, offer a published report (see the `squirrelscan` skill).

## Report format

The LLM report is a compact XML/text hybrid optimized for token efficiency: summary with health score, issues grouped by category with affected URLs, broken links, and prioritized recommendations. Full spec: [OUTPUT-FORMAT.md](references/OUTPUT-FORMAT.md)

查看并核实来源

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来源需要复核

已跟踪的来源发生变化或同步失败，请在安装前复核当前来源。

安装前审查: 避免自动安装

许可证: See LICENSE file in repository root

Dependency or permission surface needs review
Permission surface may require sandboxing
The skill requires the squirrel CLI to be installed and accessible in PATH, but does not provide installation instructions within SKILL.md (only a link).
The license is referenced as 'See LICENSE file in repository root' rather than explicitly stated, which may be less clear for some users.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 87 GitHub stars
Stars/forks activity: 87 stars, 10 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

打开完整审计

工具列表来自元数据，并非已测试的兼容性；Agent 提示词是建议的交接方式。

从一个小任务开始

1阅读来源，确认输入、预期输出、依赖和权限。
2先让 Agent 提出计划，批准环境配置和费用，再进行隔离的小规模测试。
3检查输出和变更文件，只报告实际执行结果，并保留来源版本以便复现。

请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。

来源与使用须知

已收录

仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。

来源仓库: squirrelscan/skills
许可证: See LICENSE file in repository root
版本: 1.0.0
最近 GitHub 推送: 2026年9月6日
目录更新于: 2026年10月6日
技能指令路径: skills/audit-website/SKILL.md @ f4219bcd69da

版本来自目录元数据，使用前请核实来源发布记录。

质量

63/100

有潜力

信任

54/100

Do not auto-install

审计

71/100

需审查

打开完整审计查看评估报告

Dependency or permission surface needs review
Permission surface may require sandboxing
The skill requires the squirrel CLI to be installed and accessible in PATH, but does not provide installation instructions within SKILL.md (only a link).
The license is referenced as 'See LICENSE file in repository root' rather than explicitly stated, which may be less clear for some users.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 87 GitHub stars
Stars/forks activity: 87 stars, 10 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
结果: —

复制不等于安装。安装数需有成功安装回报，不代表全面的质量保证。

Agent 接入

本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号，让 Agent 无需抓取界面即可排序。

打开安装 API LLM 文本格式打开 Manifest 自动解析计划

更多详情

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    "manifest": "https://www.openagentskill.com/api/registry/manifest/squirrelscan-audit-website"
  }
}

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创作者: squirrelscan
来源: squirrelscan/skills
收录方: OpenAgentSkill 社区索引

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认领此 Skill 页面

这条 Registry 收录列表归属于 squirrelscan，但尚未标记为官方。认领后可增加已验证所有者信号，使后续发布、安装和审计更新更值得信赖。

分享工具包

创作者外链工具包

将证据徽章加入你的 README

在开发者评估仓库的位置展示规范页面、当前信任与审计信号，以及真实的 Agent 验证证据。

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/squirrelscan-audit-website?metric=listed&label=Listed)](https://www.openagentskill.com/skills/squirrelscan-audit-website?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/squirrelscan-audit-website?metric=trust&label=Trust)](https://www.openagentskill.com/skills/squirrelscan-audit-website?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/squirrelscan-audit-website?metric=audit&label=Audit)](https://www.openagentskill.com/skills/squirrelscan-audit-website/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/squirrelscan-audit-website?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/squirrelscan-audit-website?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

预览徽章打开审计创作者工具包

社区信号

告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。

概览