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 charlieviettq/awesome-agent-skill --skill algo-seo-technicalgit clone --depth 1 https://github.com/charlieviettq/awesome-agent-skillWrote 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/charlieviettq/awesome-agent-skill/algo-seo-technical)<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-seo-technical"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-seo-technical/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/charlieviettq/awesome-agent-skill/algo-seo-technical"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-seo-technical.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 | $0.00084 | $0.01062 |
| Opus 5 | $0.00042 | $0.00531 |
| Sonnet 5 | $0.00017 | $0.00212 |
| Haiku 4.5 | $0.00008 | $0.00106 |
Grade A, and why
"algo-seo-technical" 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 9d 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.
This is a copy
92% identical to algo-seo-technical — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Core Web Vitals Optimization
Overview
Core Web Vitals are Google's page experience metrics: LCP (loading), INP (interactivity), and CLS (visual stability). Measured on real user data (CrUX). Pass thresholds: LCP < 2.5s, INP < 200ms, CLS < 0.1.
When to Use
Trigger conditions:
- Diagnosing why a site fails Core Web Vitals assessment
- Optimizing page load performance for SEO
- Reducing layout shift or improving interactivity
When NOT to use:
- When the issue is content relevance, not speed (use content SEO)
- When analyzing link authority (use PageRank / backlink analysis)
Algorithm
IRON LAW: CrUX Field Data Is the Source of Truth
Lab scores (Lighthouse) that pass can still FAIL in the field.
Google ranks based on REAL USER data (75th percentile):
- LCP < 2.5s (Good), 2.5-4.0s (Needs Improvement), > 4.0s (Poor)
- INP < 200ms (Good), 200-500ms (Needs Improvement), > 500ms (Poor)
- CLS < 0.1 (Good), 0.1-0.25 (Needs Improvement), > 0.25 (Poor)
Phase 1: Input Validation
Collect field data from CrUX API or Search Console. Run Lighthouse for lab baseline. Identify which metrics fail. Gate: Have both field and lab data; failing metrics identified.
Phase 2: Core Algorithm
LCP fixes: 1. Optimize largest element (hero image/text). 2. Preload critical resources. 3. Reduce server response time (TTFB). 4. Eliminate render-blocking resources.
INP fixes: 1. Break long tasks (> 50ms) into smaller chunks. 2. Reduce JavaScript execution time. 3. Use requestIdleCallback for non-critical work. 4. Minimize main thread blocking.
CLS fixes: 1. Set explicit dimensions on images/videos. 2. Reserve space for ads/embeds. 3. Avoid inserting content above existing content. 4. Use CSS contain for dynamic elements.
Phase 3: Verification
Re-run Lighthouse, deploy, then monitor CrUX for 28-day rolling average improvement. Gate: Lab scores pass; await field data confirmation (28-day cycle).
Phase 4: Output
Return audit results with specific fix recommendations prioritized by impact.
What ships with it
3 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.
- 9d ago First seen · 87 lines · 84 tokens per session scan A 1b0298d5fcf4
"algo-seo-technical" is a skill published in the GitHub repository charlieviettq/awesome-agent-skill (25 stars, last pushed 1mo ago), licensed MIT. It adds 84 tokens to every session and 1,062 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to algo-seo-technical, differing in 8 lines, and is treated as a copy.
Other skills, from other repositories
design-loop
Autonomous multi-page site builder using a baton-passing loop. Each iteration reads a task from .design/next-prompt.md, generates a page in HTML/Tailwind, integrates it into the site, verifies visually, then writes the next task to keep the loop alive. Use whenever the user asks to build an entire site autonomously…
color-palette
Generate complete, accessible colour palettes from a single brand hex. Produces 11-shade scale (50-950), semantic tokens, dark mode variants, Tailwind v4 CSS output, WCAG contrast checks. Use whenever the user supplies a brand hex and asks for a palette, mentions setting up a design system, wants Tailwind theme…
tailwind-theme-builder
Set up Tailwind v4 + shadcn/ui themed UI with dark mode. Install deps, configure CSS variables via @theme inline, wire dark mode toggle, verify. Use whenever the user mentions Tailwind v4, setting up Tailwind theming, shadcn/ui colours, dark mode, or troubleshooting colours not working, tw-animate-css errors, @theme…
design-review
Review a web app or page for visual design quality — layout, typography, spacing, colour, hierarchy, consistency, interaction patterns, and responsive behaviour. Not a UX audit (that checks usability) — this checks whether it looks professional and polished. Produces a design findings report with screenshots.…
design-system
Extract a complete design system from an existing website or screenshot into a DESIGN.md file. Analyses colours, typography, component styles, spacing, and atmosphere through browser automation and HTML inspection. Produces a semantic design system document optimised for consistent page generation. Triggers: 'extract…
responsiveness-check
Test website responsiveness across viewport widths using browser automation. Resizes a single session through breakpoints, screenshots each width, and detects layout transitions (column changes, nav switches, overflow). Produces comparison reports showing exactly where layouts break. Trigger with 'responsiveness…