Template Enforcer logo

Template Enforcer

Organization
Amazon-Quick
template-enforcer

Apply a brand guide or style template to any document, presentation, or generated output, enforcing colors, fonts, tone of voice, logo placement, and formatting rules. Use when the user says 'apply brand guide', 'enforce template', 'match this style', 'make it consistent with our brand', 'apply our formatting', 'style this document', or any request to align a document with a visual/brand standard.

Overview

PublisherAmazon-Quick
RepositoryAmazon-Quick-official-catalog
Skill nametemplate-enforcer
Stars
50
Forks
4
Bundled files
1
LicenseMIT-0
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.

  • 1 bundled files

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

  • Open source

    Published by Amazon-Quick on GitHub. Read the source before you install it.

Installation

Install the Template Enforcer 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/Amazon-Quick/Amazon-Quick-official-catalog/tree/main/skills/design/template-enforcer
  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/Amazon-Quick/Amazon-Quick-official-catalog.git /tmp/Amazon-Quick-official-catalog
mkdir -p .claude/skills
cp -r /tmp/Amazon-Quick-official-catalog/skills/design/template-enforcer .claude/skills/template-enforcer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Template Enforcer 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 Template Enforcer 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 Template Enforcer 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.

Overview

Reads a brand guide or style reference, extracts design tokens (colors, fonts, spacing, tone rules, logo usage), then applies those constraints to a target document. Reports compliance violations, makes corrections according to the specified strictness level, and produces a styled output alongside a compliance report.

Workflow

<Definition - Brand Profile> A structured extraction from a brand guide containing:

  • colors: primary, secondary, accent, background, text_primary, text_secondary
  • typography: heading_font, body_font, heading_sizes (h1/h2/h3), body_size, line_height
  • tone: voice style, encouraged patterns (dos), prohibited patterns (donts), terminology preferences
  • logo: placement, minimum_size, clear_space
  • formatting: margins, paragraph_spacing, bullet_style, table_style, header_footer rules

Not all fields will be present in every brand guide. The profile contains only what was explicitly found. </Definition - Brand Profile>

<Definition - Compliance Score> Percentage of audited dimensions that pass. Calculated as: (passing_categories / total_auditable_categories) * 100. Categories: colors, typography, tone, formatting, logo, terminology. </Definition - Compliance Score>

<Workflow - Enforce Template description="End-to-end brand enforcement: parse guide, audit, correct, output." tools=[file_read, file_read_pdf, file_read_docx, file_read_pptx, run_python, file_write, open_in_session_tab] triggers=["User asks to apply brand guide", "enforce template", "match this style", "make it consistent with our brand"]

  1. [Decide] Is {{brand_guide}} a file path or a saved profile name?

    • File path: proceed to step 2.
    • Profile name: check artifacts/brand-profiles/{{brand_guide}}-profile.yaml. If found, load it and skip to step 4. If not found, ask user for the file path. Validate: One path is chosen. If fails: Ask user to clarify whether they are referencing a saved profile or providing a new file.
  2. [Agent] Parse the brand guide file using the appropriate reader (file_read_pdf for PDF, file_read_docx for DOCX, file_read for other formats). Extract all design token information into a structured brand profile per <Definition - Brand Profile>. Validate: At least one category (colors, typography, or tone) successfully extracted with concrete values. If fails: Report which categories could not be extracted and ask user to point to specific pages/sections containing the brand rules. Offer to proceed with partial rules.

  3. [Ask user] Present extracted brand profile summary. Confirm it looks correct before proceeding. Validate: User confirms or provides corrections. If fails: Adjust profile per user feedback and re-present.

  4. [Agent] Load the source document ({{source_document}}) using the appropriate reader. Preserve full structure (headings, paragraphs, tables, images, metadata). Validate: Document loads successfully and contains parseable content. If fails: Report the format issue. Ask user for an alternative format or path.

  5. [Agent] Audit the source document against the brand profile. Check each applicable dimension:

    • Color compliance: Are colors consistent with the palette? Flag off-brand colors with their locations.
    • Typography compliance: Correct fonts, sizes, and hierarchy?
    • Tone compliance: Does language match voice guidelines? Flag jargon violations or banned terminology.
    • Formatting compliance: Margins, spacing, bullet styles correct?
    • Logo compliance: Proper placement and sizing? (if applicable and detectable)
    • Terminology compliance: Preferred terms used? Banned terms present?

    Produce a compliance report table:

    CategoryStatusIssues FoundSeverity

    Calculate overall compliance score per <Definition - Compliance Score>. Validate: At least one category assessed. Report table generated. If fails: Proceed with best-effort assessment on available categories.

  6. [Decide] What is the strictness level?

    • "advisory": Save compliance report to artifacts/compliance-report-[name].md. Present to user. Skip to step 9.
    • "moderate" or "strict": Proceed to step 7. Validate: Strictness is one of the three valid values. If fails: Default to "moderate".
  7. [Agent] Apply corrections using run_python:

    • Swap off-brand colors to nearest brand-approved color.
    • Replace fonts with brand typography.
    • Adjust heading hierarchy to match brand sizes.
    • Fix spacing, margins, bullet styles.
    • Replace banned terminology with preferred alternatives.
    • (strict only) Rewrite flagged tone violations to match brand voice.
    • (strict only) Insert/reposition logo if template requires it. Validate: Corrections applied without corrupting document structure. Re-audit shows improved compliance score. If fails: Report which items could not be auto-corrected. Present them for manual review.
  8. [Agent] Generate styled output file in {{output_format}} format:

    • "same": Match the input file format.
    • "docx": Apply styles via python-pptx/openpyxl, set fonts, colors, paragraph formatting.
    • "html": Generate with inline styles matching brand tokens.
    • "pptx": Apply slide master colors, fonts, logo placement.
    • "md": Apply tone corrections and structure formatting. Save to: artifacts/styled-[original-name].[ext] Validate: Output file created, non-empty, and valid format. If fails: Fall back to markdown output with compliance notes inline.
  9. [Agent] Save compliance report to artifacts/compliance-report-[original-name].md. Open styled output (if created) and compliance report in session tabs. Present summary:

    • Compliance improved: [X]% to [Y]%
    • [N] corrections applied
    • [M] items flagged for manual review
    • Output saved: artifacts/styled-[filename].[ext] Validate: User can view the output. If fails: Provide file path and inline summary.
  10. [Ask user] "I've extracted your brand profile. Want me to save it so you can reference it by name next time without re-uploading the guide?"

    • Yes: Save to artifacts/brand-profiles/[brand-name]-profile.yaml
    • No: Done. Validate: If yes, profile file saved and readable. If fails: Provide extracted profile as inline YAML for user to save manually.

</Workflow - Enforce Template>

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 Template Enforcer AI skill do?

Apply a brand guide or style template to any document, presentation, or generated output, enforcing colors, fonts, tone of voice, logo placement, and formatting rules. Use when the user says 'apply brand guide', 'enforce template', 'match this style', 'make it consistent with our brand', 'apply our formatting', 'style this document', or any request to align a document with a visual/brand standard.

Why use Template Enforcer on TypingMind?

Because you install it once and use it with any model. Template Enforcer 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 Template Enforcer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Amazon-Quick/Amazon-Quick-official-catalog/tree/main/skills/design/template-enforcer. 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 Template Enforcer?

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 Template Enforcer?

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

Is the Template Enforcer AI skill free?

Yes. It is published on GitHub by Amazon-Quick under the MIT-0 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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