Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sivang/sivan-claude-plugins --skill site-auditgit clone --depth 1 https://github.com/sivang/sivan-claude-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sivang/sivan-claude-plugins/site-audit)<a href="https://agentmods.dev/skills/sivang/sivan-claude-plugins/site-audit"><img src="https://agentmods.dev/badge/skills/sivang/sivan-claude-plugins/site-audit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sivang/sivan-claude-plugins/site-audit"><img src="https://agentmods.dev/badge/skills/sivang/sivan-claude-plugins/site-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.02676 |
| Opus 5.5 | $0.00019 | $0.01070 |
| Sonnet 5.5 | $0.00009 | $0.00535 |
| Haiku 4.5 | $0.00005 | $0.00268 |
Grade A, and why
site-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Site Audit
Role: Thorough website quality auditor.
Objective: Crawl the provided URL and all reachable same-domain pages using Chrome browser navigation, checking for broken links, spelling/grammar errors, console errors, and visual issues. Produce a structured report of all findings.
Input
The user provides a target URL as an argument to /site-audit. Example: /site-audit https://example.com
If no URL is provided, ask the user for one. Validate that the input is a valid URL (starts with http:// or https://).
Execution
Phase 1: URL Validation & Browser Setup
- Extract the URL from the user's command
- Validate it starts with http:// or https://
- Set up Chrome browser tab:
- Call
tabs_context_mcpto get existing tab group (withcreateIfEmpty: true) - Call
tabs_create_mcpto create one dedicated tab for the entire audit - Store the returned tab ID for all subsequent operations
- Call
- Navigate to the seed URL to verify it loads
- Confirm the target domain with the user
Phase 2: Chrome-Based Crawl
After URL validation, begin the breadth-first crawl using Chrome navigation.
Initialization:
- Parse the seed URL to extract protocol, domain (hostname), and path
- Initialize crawl state:
queue: List containing only the seed URL (normalized)visited: Empty set for tracking crawled URLspage_count: 0max_pages: 20 (crawl limit — keeps audit focused)broken_links: Empty list for recording dead links with source infoseed_hostname: Extracted hostname from seed URL (for same-domain checks)link_sources: Map of {target_url: source_page} for dead link trackingbroken_links_count: 0spelling_issues_count: 0
- Create
.audit-data/directory and initialize JSONL files:mkdir -p .audit-data touch .audit-data/findings-broken-links.jsonl touch .audit-data/findings-spelling.jsonl - Reference @references/URL_RULES.md for URL normalization rules
- Reference @references/CHECKS.md for content analysis and broken link detection rules
- Display initialization summary to user:
- Seed URL (normalized)
- Domain to crawl
- Max pages limit
- Chrome tab ID being used
- Findings will be written to
.audit-data/directory
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 257 lines · 47 tokens per session scan A 2441e3828494
site-audit is a skill published in the GitHub repository sivang/sivan-claude-plugins (1 stars, last pushed 9mo ago), licensed MIT. It adds 47 tokens to every session and 2,676 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
qa
Browser-based QA verification. Launches a real browser, navigates the app, clicks buttons, fills forms, and tests user flows. Works as a standalone skill or as a phase end condition in campaigns. Requires Playwright (optional dependency, graceful skip if not installed).
postmortem
Auto-generates a structured postmortem from a completed campaign. Reads the campaign file, telemetry logs, and feature ledger. Produces a documented analysis of what broke, what the safety systems caught, and what patterns emerged. Can also be invoked manually for any incident.
systematic-debugging
4-phase root cause analysis: observe, hypothesize, verify, fix. Enforces investigation before any code changes. Emergency stop after 2 failed fixes. Prevents shotgun debugging and fix cascades.
audit-project
Run an iterative multi-agent code audit until critical and high findings are resolved. Use when the user says "audit my code", "find all the bugs", "deep code audit", "iterative review", or "review until clean".
optimize
Use when asked to optimize code, make a path faster, make this as fast as possible, reduce allocations, repair a regression, profile a target, grill every inefficiency, or run a subsystem or repo-wide performance campaign against a measured floor; when a performance requirement, slowness report, Core Web Vitals miss…
debug
Hypothesis-driven debugging. Use when a test fails, a crash or exception occurs, output is wrong, or an intermittent flake has no obvious cause.