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Wp Acf And Content Modeling

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jorgerosal
wp-acf-and-content-modeling

WordPress ACF and content modeling review. Use when reviewing Advanced Custom Fields usage, field group architecture, CPT and taxonomy design, options pages, repeaters, flexible content, block-bound field groups, meta storage patterns, or when user mentions "ACF", "field groups", "flexible content", "repeater", "custom post type design", "taxonomy design", "content model", "relationship fields", "ACF JSON", "options page", or "meta query performance". Detects schema drift, weak content modeling, brittle field naming, and performance issues in meta-heavy WordPress builds.

Overview

Publisherjorgerosal
Repositorywordpress-skills
Skill namewp-acf-and-content-modeling
Stars
113
Forks
13
Bundled files
3
LicenseMIT
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Wp Acf And Content Modeling 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/jorgerosal/wordpress-skills/tree/main/claude-skills/wp-acf-and-content-modeling
  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/jorgerosal/wordpress-skills.git /tmp/wordpress-skills
mkdir -p .claude/skills
cp -r /tmp/wordpress-skills/claude-skills/wp-acf-and-content-modeling .claude/skills/wp-acf-and-content-modeling
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wp Acf And Content Modeling 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 Acf And Content Modeling 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 Acf And Content Modeling 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.

WordPress ACF and Content Modeling Skill

Overview

Systematic review skill for WordPress projects that rely on Advanced Custom Fields and custom content architecture. Core principle: a healthy WordPress content model is durable, query-aware, editor-friendly, and predictable to migrate. Review focuses on CPT and taxonomy design, field-group boundaries, naming consistency, storage strategy, ACF JSON synchronization, and the long-term cost of meta-heavy patterns. Report findings grouped by file or subsystem with severity labels (CRITICAL, WARNING, INFO), line references where possible, and concrete remediation guidance.

When to Use

Use when:

  • Auditing a plugin or theme that registers custom post types, taxonomies, or ACF field groups
  • Reviewing acf_add_local_field_group() or field group JSON exports
  • Checking whether repeaters / flexible content are the right fit for the content problem
  • Evaluating options pages, relationship fields, clone fields, or block field groups
  • Investigating slow admin screens or expensive meta_query usage in content-heavy builds
  • Planning a new content model for an editorial site, directory, landing-page builder, or headless setup
  • Reviewing ACF JSON sync, field key drift, or environment-to-environment portability

Don't use for:

  • Generic plugin architecture without meaningful ACF/content-model work (use wp-plugin-development)
  • Pure REST route design (use wp-rest-api-development)
  • Gutenberg block implementation details unrelated to field modeling (use wp-block-development)
  • Performance audits not tied to content schema or metadata access (use wp-performance-review)
  • WooCommerce domain modeling (use wp-woocommerce-dev unless the issue is truly generic ACF modeling)

Review Workflow

Follow this seven-step workflow.

  1. Identify the model boundary

    • What is the real domain: articles, locations, staff, products, events, landing pages, settings, or reusable content fragments?
    • Determine whether the model is single-site, multisite, or headless-facing.
    • Inventory CPTs, taxonomies, options pages, and field groups before evaluating implementation quality.
  2. Check core content entities first

    • Validate each CPT has a clear purpose and does not merely duplicate posts/pages without a reason.
    • Check whether taxonomies model classification and relationships better than extra text/meta fields.
    • Flag overloaded post types used as catch-alls for unrelated content.
  3. Review field-group architecture

    • Inspect location rules, naming conventions, instructions, conditional logic, defaults, and required flags.
    • Check whether field groups are split by editorial task instead of becoming giant monoliths.
    • Verify repeaters and flexible content are used intentionally, not as a substitute for missing entity design.
  4. Scan for CRITICAL patterns

    • Field names or data shapes changed without a migration path.
    • Environment-specific field keys relied on directly in code.
    • Content that should be relational or taxonomic stored as plain text blobs.
    • Massive meta_query dependence for core archive/search behavior with no mitigation.
    • Flexible-content or repeater structures used where separate entities are clearly required.
    • Options-page values treated as request-specific content without cache or invalidation awareness.
  5. Check WARNING patterns

    • Ambiguous field names (title, image, link) with no domain prefix or context.
    • Duplicate field groups or cloned definitions drifting across environments.
    • Relationship/post object fields with no return-format consistency.
    • Fields exposed to editors with weak instructions, no defaults, or unclear conditional logic.
    • ACF JSON enabled inconsistently or committed unreliably.
    • Repeater-heavy landing pages likely to become impossible to query, reuse, or migrate.
  6. Note INFO improvements

    • Taxonomies could improve filtering, SEO, or editorial consistency.
    • An options page could replace duplicated per-page settings.
    • A custom table may be justified for high-volume structured data.
    • Shared components may benefit from clone fields or a reusable block strategy.
    • Field instructions, tabs, and groups could reduce editor error rates.
  7. Report with context-aware severity

    • Enterprise/editorial site: prioritize governance, migration safety, query behavior, and authoring ergonomics.
    • Marketing/landing-page builder: prioritize maintainability and editorial constraints over abstract purity.
    • Headless site: prioritize schema stability, API exposure shape, and relationship modeling.
    • Add cross-skill notes when findings should be followed by wp-rest-api-development, wp-performance-review, or wp-block-development.

Model-Level Checks

Content Type Design (ACF-01)

CRITICAL

  • Multiple unrelated business concepts forced into one CPT with flags like type, layout, or kind doing all the work
  • A CPT exists only to simulate grouped fields that belong on an existing content type
  • Important relational content stored in serialized arrays or long text fields instead of structured entities

WARNING

  • CPT labels, supports, or archive behavior do not match editorial intent
  • Post types rely on custom fields for primary titles or slugs when core title/slug should carry that job
  • Content discoverability depends entirely on custom sorting/meta instead of taxonomy or date semantics

INFO

  • A taxonomy may be better than another boolean/select field
  • A small reusable post type may simplify repeated section content or shared landing-page fragments

Taxonomy Design (ACF-02)

CRITICAL

  • Taxonomy-worthy classification modeled as free-text fields, causing duplicate spellings and broken filters
  • Relationship semantics forced into repeated text/select fields instead of terms or relationship fields

WARNING

  • Taxonomies are too broad, mixing audience, topic, location, and workflow state in one structure
  • A hierarchical taxonomy is used where flat tagging would be simpler, or vice versa
  • Term metadata is added for core entity content that likely deserves its own entity instead

INFO

  • Taxonomies can often replace fragile editor-entered labels and improve queryability

Field Naming and Schema Stability (ACF-03)

CRITICAL

  • Code depends on field keys like field_123abc instead of stable field names when not required
  • Field names renamed with no migration or backward-compatibility handling
  • Two unrelated fields share nearly identical names across contexts, leading to template confusion

WARNING

  • Names are too generic (title, cta, copy, image) and lose meaning outside one template
  • Prefixing is inconsistent across domains (hero_, event_, team_ mixed unpredictably)
  • Return formats vary silently between field groups for the same conceptual field

INFO

  • Prefix related fields by domain or component to improve grepability and future migrations

Repeater and Flexible Content Usage (ACF-04)

CRITICAL

  • Flexible content is used as a full site-builder without governance, creating untestable content permutations
  • Repeaters hold data that needs independent URLs, reuse, ownership, or filtering
  • Huge nested repeaters are queried or transformed as if they were relational tables

WARNING

  • Repeater rows have no min/max limits or editor guidance
  • Flexible content layouts overlap heavily and indicate missing design-system discipline
  • Deep nesting makes migrations, previews, and template maintenance brittle

INFO

  • Consider dedicated entities, synced patterns, or block-based composition for reusable structures

Relationship Fields and Return Formats (ACF-05)

CRITICAL

  • Relationship/post-object fields used without a stable expected return format in code
  • Bidirectional relationships are assumed but never maintained consistently

WARNING

  • Templates call get_field() repeatedly inside loops when values could be normalized once
  • Relationship field queries are not constrained, making editorial selection noisy and error-prone
  • IDs vs objects vs arrays are mixed casually across code paths

INFO

  • Normalize field access through view-model helpers or DTO-like mappers when templates become repetitive

Options Pages and Global Settings (ACF-06)

CRITICAL

  • Frequently changing request-level content is stored globally and expected to vary per page/user/context
  • Critical runtime configuration is edited through ACF options with no validation or deployment discipline

WARNING

  • Sitewide content is duplicated across pages instead of centralized in options/global entities
  • Options pages mix marketing copy, integration secrets, and editorial settings in one screen
  • Code assumes options always exist and never handles empty defaults

INFO

  • Split options pages by responsibility and add defaults/instructions for resilience

ACF JSON and Environment Sync (ACF-07)

CRITICAL

  • Field-group changes exist only in the database with no committed JSON or export path
  • Team workflow routinely overwrites field definitions because sync direction is unclear

WARNING

  • acf-json is committed inconsistently or partially
  • Field groups are edited in production without a promotion path
  • Local JSON path configuration differs between environments without documentation

INFO

  • Keep acf-json under version control and treat DB-only edits as temporary until exported

Meta Query and Storage Performance (ACF-08)

CRITICAL

  • Primary archive/search behavior depends on multiple unindexed meta_query clauses at scale
  • Repeater/flexible content values are mined through LIKE queries for business-critical views
  • Numeric/date filtering uses string comparison semantics or inconsistent storage formats

WARNING

  • Content modeling encourages many joins against postmeta for every request
  • Derived/aggregated values are recalculated from nested ACF data on each page load
  • Query behavior assumes ACF fields are cheap just because the admin UI is convenient

INFO

  • Promote high-volume query keys into taxonomies, dedicated lookup tables, or precomputed indexes when needed

Review Heuristics

Good ACF signs

  • Field groups align with clear editorial tasks or components
  • CPTs and taxonomies reflect real business entities
  • Names are stable, descriptive, and domain-prefixed
  • ACF JSON is committed and environment sync is intentional
  • Relationship fields and return formats are normalized in code
  • Meta usage supports the scale and query patterns of the site

Common anti-patterns

  • “Everything is a page with flexible content forever”
  • “Everything is post meta even when it should be taxonomy or a dedicated entity”
  • “Editors can build anything” without constraints or safe defaults
  • “We query repeater internals directly”
  • “We changed field names and hoped templates would keep working”

Output Format

Use this structure:

text
# ACF / Content Modeling Review

## Summary
- Scope: plugin/theme/app reviewed
- Modeling maturity: strong / mixed / fragile
- Primary risks: 2-5 bullets

## Critical Findings
- [ACF-XX] Title — file:line or subsystem
  Why it matters
  Recommended fix

## Warning Findings
- [ACF-XX] Title — file:line or subsystem
  Why it matters
  Recommended fix

## Info / Improvement Opportunities
- [ACF-XX] Title — file:line or subsystem
  Suggested improvement

## Modeling Notes
- Entity design observations
- Taxonomy vs meta observations
- Query/storage implications

## Cross-Skill Follow-Up
- Run `/wp-perf-review` if query behavior is the main risk
- Run `/wp-rest-review` if schema exposure or API contracts need review
- Run `/wp-block-review` if field groups power custom blocks heavily

Reference Files

Load these only as needed:

  • references/content-modeling-guide.md
  • references/acf-json-and-field-group-guide.md
  • references/meta-query-and-performance.md

Final Reminder

This skill should not reward ACF usage merely because it works in the admin. Prefer models that stay understandable after the site doubles in content, editors, and integrations.

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 Acf And Content Modeling AI skill do?

WordPress ACF and content modeling review. Use when reviewing Advanced Custom Fields usage, field group architecture, CPT and taxonomy design, options pages, repeaters, flexible content, block-bound field groups, meta storage patterns, or when user mentions "ACF", "field groups", "flexible content", "repeater", "custom post type design", "taxonomy design", "content model", "relationship fields", "ACF JSON", "options page", or "meta query performance". Detects schema drift, weak content modeling, brittle field naming, and performance issues in meta-heavy WordPress builds.

Why use Wp Acf And Content Modeling on TypingMind?

Because you install it once and use it with any model. Wp Acf And Content Modeling 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 Acf And Content Modeling in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jorgerosal/wordpress-skills/tree/main/claude-skills/wp-acf-and-content-modeling. 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 Acf And Content Modeling?

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 Acf And Content Modeling?

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

Is the Wp Acf And Content Modeling AI skill free?

Yes. It is published on GitHub by jorgerosal under the MIT license. 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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