Wp Performance logo

Wp Performance

OrganizationPopular
WordPress
wp-performance

Use when investigating or improving WordPress performance (backend-only agent): profiling and measurement (WP-CLI profile/doctor, Server-Timing, Query Monitor via REST headers), database/query optimization, autoloaded options, object caching, cron, HTTP API calls, and safe verification.

Overview

PublisherWordPress
Repositoryagent-skills
Skill namewp-performance
Stars
2.1K
Forks
318
Bundled files
11
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.

  • 11 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Wp 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.
  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/WordPress/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/wp-performance .claude/skills/wp-performance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wp 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 Wp 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 Wp 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.

WP Performance (backend-only)

When to use

Use this skill when:

  • a WordPress site/page/endpoint is slow (frontend TTFB, admin, REST, WP-Cron)
  • you need a profiling plan and tooling recommendations (WP-CLI profile/doctor, Query Monitor, Xdebug/XHProf, APMs)
  • you’re optimizing DB queries, autoloaded options, object caching, cron tasks, or remote HTTP calls

This skill assumes the agent cannot use a browser UI. Prefer WP-CLI, logs, and HTTP requests.

Inputs required

  • Environment and safety: dev/staging/prod, any restrictions (no writes, no plugin installs).
  • How to target the install:
    • WP root --path=<path>
    • (multisite/site targeting) --url=<url>
  • The performance symptom and scope:
    • which URL/REST route/admin screen
    • when it happens (always vs sporadic; logged-in vs logged-out)

Procedure

0) Guardrails: measure first, avoid risky ops

  1. Confirm whether you may run write operations (plugin installs, config changes, cache flush).
  2. Pick a reproducible target (URL or REST route) and capture a baseline:
    • TTFB/time with curl if possible
    • WP-CLI profiling if available

Read:

  • references/measurement.md

1) Generate a backend-only performance report (deterministic)

Run:

  • node skills/wp-performance/scripts/perf_inspect.mjs --path=<path> [--url=<url>]

This detects:

  • WP-CLI availability and core version
  • whether wp doctor / wp profile are available
  • autoloaded options size (if possible)
  • object-cache drop-in presence

2) Fast wins: run diagnostics before deep profiling

If you have WP-CLI access, prefer:

  • wp doctor check

It catches common production foot-guns (autoload bloat, SAVEQUERIES/WP_DEBUG, plugin counts, updates).

Read:

  • references/wp-cli-doctor.md

3) Deep profiling (no browser required)

Preferred order:

  1. wp profile stage to see where time goes (bootstrap/main_query/template).
  2. wp profile hook (optionally with --url=) to find slow hooks/callbacks.
  3. wp profile eval for targeted code paths.

Read:

  • references/wp-cli-profile.md

4) Query Monitor (backend-only usage)

Query Monitor is normally UI-driven, but it can be used headlessly via REST API response headers and _envelope responses:

  • Authenticate (nonce or Application Password).
  • Request REST responses and inspect headers (x-qm-*) and/or the qm property when using ?_envelope.

Read:

  • references/query-monitor-headless.md

5) Fix by category (choose the dominant bottleneck)

Use the profile output to pick one primary bottleneck category:

  • DB queries → reduce query count, fix N+1 patterns, improve indexes, avoid expensive meta queries.
    • references/database.md
  • Autoloaded options → identify the biggest autoloaded options and stop autoloading large blobs.
    • references/autoload-options.md
  • Object cache misses → introduce caching or fix cache key/group usage; add persistent object cache where appropriate.
    • references/object-cache.md
  • Remote HTTP calls → add timeouts, caching, batching; avoid calling remote APIs on every request.
    • references/http-api.md
  • Cron → reduce due-now spikes, de-duplicate events, move heavy tasks out of request paths.
    • references/cron.md

6) Verify (repeat the same measurement)

  • Re-run the same wp profile / wp doctor / REST request.
  • Confirm the performance delta and that behavior is unchanged.
  • If the fix is risky, ship behind a feature flag or staged rollout when possible.

WordPress 6.9 performance improvements

Be aware of these 6.9 changes when profiling:

On-demand CSS for classic themes:

  • Classic themes now get on-demand CSS loading (previously only block themes had this).
  • Reduces CSS payload by 30-65% by only loading styles for blocks actually used on the page.
  • If you're profiling a classic theme, this should already be helping.

Block themes with no render-blocking resources:

  • Block themes that don't define custom stylesheets (like Twenty Twenty-Three/Four) can now load with zero render-blocking CSS.
  • Styles come from global styles (theme.json) and separate block styles, all inlined.
  • This significantly improves LCP (Largest Contentful Paint).

Inline CSS limit increased:

  • The threshold for inlining small stylesheets has been raised, reducing render-blocking resources.

Reference: https://make.wordpress.org/core/2025/11/18/wordpress-6-9-frontend-performance-field-guide/

Verification

  • Baseline vs after numbers are captured (same environment, same URL/route).
  • wp doctor check is clean (or improved) when applicable.
  • No new PHP errors or warnings in logs.
  • No cache flush is required for correctness (cache flush should be last resort).

Failure modes / debugging

  • “No change” after code changes:
    • you measured a different URL/site (--url mismatch), caches masked results, or opcode cache is stale
  • Profiling data is noisy:
    • eliminate background tasks, test with warmed caches, run multiple samples
  • SAVEQUERIES/Query Monitor causes overhead:
    • don’t run in production unless explicitly approved

Escalation

  • If this is production and you don’t have explicit approval, do not:
    • install plugins, enable SAVEQUERIES, run load tests, or flush caches during traffic
  • If you need system-level profiling (APM, PHP profiler extensions), coordinate with ops/hosting.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Wp Performance AI skill do?

Use when investigating or improving WordPress performance (backend-only agent): profiling and measurement (WP-CLI profile/doctor, Server-Timing, Query Monitor via REST headers), database/query optimization, autoloaded options, object caching, cron, HTTP API calls, and safe verification.

Why use Wp Performance on TypingMind?

Because you install it once and use it with any model. Wp 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 Wp Performance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/WordPress/agent-skills/tree/trunk/skills/wp-performance. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Wp 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 Wp Performance?

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

Is the Wp Performance AI skill free?

It is published on GitHub by WordPress. 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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