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Seo Performance

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AgriciDaniel
seo-performance

Performance specialist for full audits. Measures CWV (LCP/INP/CLS), Lighthouse score signals, and emits deterministic report artifacts.

Overview

PublisherAgriciDaniel
Repositorycodex-seo
Skill nameseo-performance
Stars
804
Forks
112
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Seo Performance AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/AgriciDaniel/codex-seo/tree/main/skills/seo-performance
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AgriciDaniel/codex-seo.git /tmp/codex-seo
mkdir -p .claude/skills
cp -r /tmp/codex-seo/skills/seo-performance .claude/skills/seo-performance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Seo Performance in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Seo Performance on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Seo Performance is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Performance Specialist

Use this for the performance sub-track in full audits.

Shared Data Cache

Step 0 -- Check shared data cache:

Before gathering, check .seo-cache/ for cached data from other skills. Reference: ../seo/references/shared-data-cache.md for schemas and dependency map.

This specialist does not require upstream cache inputs before running fresh performance checks.

  • If found: no prerequisite cache is needed; continue with current measurements
  • If missing: proceed normally and gather fresh performance data
  • If the user says "refresh" or "re-run": ignore cache entirely

Inputs

  • URL
  • Timeout
  • Optional PageSpeed API key (PAGESPEED_API_KEY)

Execution Path

Prefer running scripts/analyze_performance.py for deterministic performance analysis in API/headless environments. The script uses PageSpeed data when available and otherwise falls back to labeled heuristics so the pipeline still completes without a human in the loop.

Outputs

  • PERFORMANCE-AUDIT-REPORT.md
  • SUMMARY.json

Core checks

  • Prefer real-user CWV data from PageSpeed Insights / CrUX when available
  • If real-user data is unavailable, fall back to Lighthouse lab data and label it clearly as lab data
  • Lighthouse performance score (mobile + desktop if available)
  • LCP and CLS measurements
  • INP only when the data source actually provides it; do not fabricate or infer INP from TBT
  • TBT may be reported as a lab proxy when INP is unavailable
  • Fallback guidance when API data is unavailable, quota-blocked, or unauthenticated

Priority Rules

  • High: Performance score < 70 or LCP > 2500ms or INP > 200ms or CLS > 0.1
  • Medium: Performance score 70-79
  • Low: Data-source limitations

Write to shared data cache

After completing all work, write results to .seo-cache/.

bash
mkdir -p .seo-cache/pages/{url-slug}

Write .seo-cache/pages/{url-slug}/performance.json using the schema in ../seo/references/shared-data-cache.md. At minimum, match the documented cache keys: core_web_vitals and issues. Add extra helpful fields only if they do not replace or rename the documented keys.

Add .seo-cache/ to .gitignore if not already present:

bash
grep -qxF '.seo-cache/' .gitignore 2>/dev/null || echo '.seo-cache/' >> .gitignore

Premium Deliverable

If the user requests a 'client report' or 'premium deliverable', automatically read ../seo-audit/assets/report-template.html and ../seo/references/premium-report-standard.md. Use that report standard as the default brief. Generate the HTML as an internal intermediate artifact, then produce the PDF as the public deliverable. Mention only the PDF in your final response unless the user explicitly asks for the HTML file.

Frequently asked questions

What does the Seo Performance AI skill do?

Performance specialist for full audits. Measures CWV (LCP/INP/CLS), Lighthouse score signals, and emits deterministic report artifacts.

Why use Seo Performance on TypingMind?

Because you install it once and use it with any model. Seo Performance is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Seo Performance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgriciDaniel/codex-seo/tree/main/skills/seo-performance. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Seo Performance?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Seo Performance?

As many as you like. As long as a model supports skills, you can use Seo Performance with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Seo Performance AI skill free?

It is published on GitHub by AgriciDaniel. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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