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.
git clone --depth 1 https://github.com/fatihkan/badiWrote 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/commands/fatihkan/badi/lighthouse)<a href="https://agentmods.dev/commands/fatihkan/badi/lighthouse"><img src="https://agentmods.dev/badge/commands/fatihkan/badi/lighthouse.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00369 |
| Opus 5 | $0.00000 | $0.00185 |
| Sonnet 5 | $0.00000 | $0.00074 |
| Haiku 4.5 | $0.00000 | $0.00037 |
Grade A, and why
lighthouse 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 today.
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.
What it actually says
Lighthouse audit command. Performance, Accessibility, Best Practices, SEO scores and Core Web Vitals via the Google PageSpeed Insights API.
Required Tools
- Bash (badi lighthouse command invocation)
Procedure
Step 1: Get the URL
Take a full URL from the user. Mind the http/https prefix. Ask if invoked without an argument.
Step 2: Strategy Selection
Mobile or desktop? Mobile is usually the default since Google does mobile-first indexing.
badi lighthouse [url] # Mobile (default)
badi lighthouse [url] --desktop # Desktop
Step 3: Interpret the Result
Scores in 4 categories:
- Performance - speed metrics
- Accessibility - axe-core based
- Best Practices - HTTPS, console errors
- SEO - meta tags, crawlability
Core Web Vitals:
- FCP < 1.8s (good), < 3.0s (fair)
- LCP < 2.5s (good), < 4.0s (fair)
- TBT < 200ms (good), < 600ms (fair)
- CLS < 0.1 (good), < 0.25 (fair)
Step 4: Improvement Suggestions
For categories under 90, give the user concrete suggestions:
- Low Performance: "Image optimization, code splitting, caching"
- Low A11y: "Get detail with
/a11y-audit [url]" - Low SEO: "Detailed report via
badi seo audit [url]"
Example
/lighthouse https://example.com
/lighthouse https://example.com --desktop
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.
- today First seen · 46 lines · 0 tokens per session scan A 1cfe1870322b
lighthouse is a command published in the GitHub repository fatihkan/badi (7 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 369 tokens. 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 2026-09-06.
Other commands, from other repositories
audit-agents-skills
Audit quality of agents, skills, and commands in a Claude Code project.
check-cache-bugs
Audit Claude Code setup for cache bugs (CC#40524) — sentinel, --resume/--continue, attribution header + ArkNill B3/B4/B5.
land-and-deploy
Merge PR, wait for CI, verify deploy, run canary — the complete landing pipeline.
qa
Systematic QA testing of a web application — diff-aware, tiered, with fix-and-verify loop.
review-pr
Perform a comprehensive code review of a pull request.
git-worktree-clean
Clean up stale git worktrees with merged branch detection and disk usage report.