Installing Taste Skill Claude SKILL.md Files in AI Coding Agents
This skill teaches you how to set up and configure Taste Skill SKILL.md instruction files inside AI coding agents like Cursor, Claude Code, Codex, Gemini CLI, and v0 so that every frontend generation follows design-quality rules instead of producing generic, sloppy UI.
Place SKILL.md files in the agent-specific instruction directory for your tool. For Claude Code, add them to your project's .claude/ folder or reference them in CLAUDE.md. For Cursor, place them in .cursor/rules/. For Codex, reference them in your AGENTS.md. Each agent reads these files as persistent system instructions that shape every generation toward stronger design quality.
Outcome: Your AI coding agent will read Taste Skill design rules on every prompt, producing UI with intentional typography, spacing, layout density, and motion instead of the generic defaults that make AI-generated frontends look identical.
Prerequisites
- A working AI coding agent (Cursor, Claude Code, Codex, Gemini CLI, or v0)
- A frontend project repository with at least one UI component or page
- Basic comfort with file system operations (creating folders, copying files)
- Familiarity with markdown file format
Overview
Every AI coding agent has a mechanism for persistent instructions: files that the agent reads before it processes your prompt, shaping its behavior across every generation. The Taste Skill Frontend Design Framework is built entirely around this mechanism. It packages design-quality rules into portable SKILL.md files that you drop into the right directory, and from that point forward, your agent treats those rules as constraints on every piece of frontend code it writes. Without this installation step, none of the framework's benefits activate. Your agent will keep producing the same padded, generic, same-font-everywhere UI that every other agent produces.
The installation process is different for each agent because each tool has its own convention for where persistent instructions live. Claude Code reads from .claude/ and CLAUDE.md. Cursor reads from .cursor/rules/. OpenAI Codex reads from AGENTS.md. Gemini CLI reads from GEMINI.md. v0 reads from project-level instructions or pasted context. The skill here is not just knowing these paths, but understanding how each agent prioritizes, merges, and applies instruction files so that your taste rules actually take effect and do not get silently ignored or overridden by conflicting instructions.
The concrete artifact you produce is a configured project where running any frontend prompt through your agent yields output shaped by Taste Skill rules. You will know installation succeeded when you can prompt your agent to build a simple component (a card, a settings page, a pricing table) and the result shows tighter spacing, deliberate type hierarchy, and visual density that looks like a human designer reviewed it. If the output still looks like a generic Tailwind template with py-8 padding on everything, something in your installation needs adjustment.
This skill is the entry point for the entire framework. Once installed, you can layer in sibling skills like enforcing typography and spacing standards, configuring layout and visual density constraints, and adding motion and interaction taste rules. But none of those matter if the files are not in the right place and being read by your agent.
How It Works
AI coding agents operate on a layered instruction model. At the bottom layer is the model's training data, which includes millions of UI examples. On top of that sits the system prompt, which the agent provider controls. On top of that sit your persistent project instructions, which is where SKILL.md files live. Finally, on top of everything is your per-prompt instruction, the actual thing you type. Each layer can override or refine the layers below it, but persistent project instructions have a special property: they apply to every prompt without you needing to repeat them. This is what makes them so powerful for design quality. You are not relying on yourself to remember to say "use tighter spacing" every time. The agent remembers for you.
The reason taste skill claude instruction files work is that they exploit a known weakness in LLM-generated UI. Without constraints, models default to the most statistically common patterns in their training data. For frontend code, that means Bootstrap-like padding, system font stacks or generic sans-serif, 16px body text with no type scale, equal spacing everywhere, and no visual hierarchy beyond font-weight bold. These defaults are not wrong, they are just average. SKILL.md files replace that average with specific, opinionated rules: a modular type scale, a spacing system tied to a base unit, density targets for different component types, and motion constraints that prevent gratuitous animation.
The Taste Skill Frontend Design Framework organizes these rules into separate SKILL.md files by domain (typography, spacing, layout, motion, review). Each file is self-contained. You can install all of them for comprehensive coverage or start with just one. The agent reads them as a set of hard constraints, similar to how a linter config constrains code style. The key mental model is: SKILL.md files are not suggestions. They are rules the agent must follow unless your prompt explicitly overrides them.
Different agents handle file discovery differently, and this is where installation gets specific. Some agents (Claude Code) walk the directory tree upward from the current file and merge every instruction file they find. Others (Cursor) read only from a specific folder. Some (v0) have no file system at all and require pasting instructions. Understanding your agent's discovery mechanism is essential because a SKILL.md file in the wrong directory is the same as no file at all. The agent will not tell you it missed a file. It will simply generate UI without those constraints, and you might not notice the difference until you compare output side by side.
One subtlety worth understanding: instruction files can conflict. If you have a SKILL.md that says "use 4px base spacing unit" and another project-level instruction that says "use Tailwind defaults," the agent will try to reconcile them, often by following whichever instruction appeared last or seemed more specific. This is why installation includes a verification step. You need to confirm that your taste rules are actually winning the priority contest inside your agent's instruction stack.
Step-by-Step
Step 1: Identify your AI coding agent and its instruction file convention
Before you touch any files, confirm exactly which agent you are using and look up its instruction file convention. claude/
directory. cursor/rules/as individual rule files in markdown format. md` files in subdirectories for scoped instructions.md` in the project root. v0 from Vercel does not use a file system for instructions but accepts instructions pasted into the project context panel. Write down your agent, its instruction path, and whether it supports multiple instruction files or only one. This determines everything about how you structure the installation.
Tip: If you use multiple agents on the same project (for example, Claude Code for backend and Cursor for frontend), you will need to install the files in both locations. The files themselves are identical. Only the directory path changes.
Step 2: Obtain the Taste Skill SKILL.md files
md files from the Taste Skill repository or documentation. The framework distributes files by domain: typography, spacing, layout-density, motion, and review. Each file is a standalone markdown document containing rules, constraints, and examples that the agent can parse. Download or copy the files you want to install.
If you are starting fresh, begin with the typography and spacing file, because those two domains have the highest impact on perceived design quality. You can add layout-density, motion, and review files later. Store the downloaded files in a temporary location while you prepare the target directories.
Tip: Read through each SKILL.md file before installing it. You may want to customize thresholds, like base spacing unit or type scale ratio, to match an existing design system. Making these edits before installation saves you from having the agent generate output you immediately need to override.
Step 3: Create the instruction directory if it does not exist
In your project repository, create the directory that your agent expects. md
at the root. cursor/rules/if that directory tree does not exist. md` at the project root.md` at the root. If the directory already exists and contains other instruction files, open those files and read them. You need to check for conflicts: any existing instruction that specifies spacing, typography, font sizes, or padding values might conflict with the Taste Skill rules. Note any conflicts you find, because you will resolve them in the next step.
Tip: Add the instruction directory to your version control. These files are project configuration, not personal preferences. Every developer on the team should get the same taste rules when they pull the repo.
Step 4: Install the SKILL.md files into the correct location
md files into the directory you identified. md
under a clear heading like## Design Quality Rules. cursor/rules/with descriptive names. Cursor treats each file as an independent rule, so separation by domain works well.md
under clearly marked sections. mdas a single document, so use markdown headings to separate domains. md` with section headings. For v0, you will paste the content into the project instructions panel in the v0 interface during your next session.Tip: Name your files with a consistent convention like `taste-typography.md`, `taste-spacing.md`, `taste-layout.md`. This makes it obvious which rules come from Taste Skill versus other instruction sources, and makes removal or updates straightforward.
Step 5: Resolve conflicts with existing instructions
If you found conflicting instructions in Step 3, resolve them now. " These generic instructions will fight with Taste Skill's specific spacing and typography rules. The resolution is usually to remove the generic instruction and let the Taste Skill rules be the authority on spacing, type, and layout. md files to reference your tokens instead of the framework defaults.
" The goal is a single, non-contradictory set of design instructions. If two instructions disagree, the agent will pick one unpredictably.
Tip: A quick way to detect conflicts is to search all instruction files for keywords like 'padding', 'margin', 'font-size', 'spacing', 'gap', and 'border-radius'. Any existing rule mentioning these terms is a potential conflict with Taste Skill.
Step 6: Verify the agent is reading the files
Open your agent and start a new conversation or session in the project directory. " A properly configured agent will reference the taste rules you installed. If the agent responds with generic information or says it has no specific design rules, the files are not being read. Check the file path, file extension, and directory name.
md`), or the file is outside the project root that the agent is scoped to. Fix the issue and test again until the agent can describe the rules back to you.
Tip: Claude Code has a helpful diagnostic: run `/config` or ask "What files are in my project instructions?" to see exactly which instruction files were loaded. Other agents are less transparent, so the "summarize the rules" test is your best verification method.
Step 7: Run a smoke test with a simple UI component
Prompt your agent to generate a simple, self-contained UI component. A good test is a user profile card or a pricing table, because these components expose typography hierarchy, spacing decisions, padding, and visual density all at once. Do not include any design instructions in your prompt. Just say "Build a user profile card component" and let the agent work from the installed rules alone.
Examine the output. Check for specific signals: Is there a visible type scale (heading noticeably larger than body, with a clear step between sizes)? Is the padding tighter than the typical generous defaults? Are spacing values consistent and based on a grid?
Is there any gratuitous animation? md files. If you see no meaningful difference, the rules are either not being read or are being overridden by something else in the instruction stack.
Tip: Save the output of this smoke test. It becomes your baseline for measuring improvement as you add more SKILL.md files or tune the existing ones. Screenshot the rendered component or save the generated code in a test file.
Step 8: Commit and document the installation for your team
Add the instruction files and directories to version control. Write a brief note in your project README or contributing guide explaining that the project uses Taste Skill instruction files for AI-assisted frontend development. Include the file locations, the purpose of each file, and instructions for any teammate who needs to update the rules. This documentation matters because a teammate who does not understand the files might delete them, move them, or add conflicting instructions.
cursor/rules/ to enforce design quality when using AI coding agents. Do not modify these files without reviewing the Taste Skill documentation" is sufficient. If your team uses multiple agents, document which directories map to which agents.
Tip: Consider adding a pre-commit hook or CI check that verifies the SKILL.md files still exist and have not been accidentally deleted. A simple check like "does .cursor/rules/taste-typography.md exist" catches accidental removal before it hits production.
Examples
Example: Solo developer installing taste skill claude files in Cursor for a Next.js SaaS dashboard
A solo developer is building a SaaS analytics dashboard in Next.js. They use Cursor as their primary coding agent. The dashboard has about 15 page-level components, and the AI-generated UI looks flat and generic with inconsistent spacing. They have 20 minutes to install taste rules and want to see immediate improvement.
cursor/rules/ in the project root. md files from the Taste Skill repository: typography, spacing, and layout-density. cursor/rules/. " They remove the spacing-related line from that file to avoid conflict.
" Cursor responds with a summary of the three taste files. " The output uses a clear type scale (24px heading, 14px labels, 32px metric values), 12px internal padding instead of the usual 24px, and a tight 8px gap between the metric items. The card looks noticeably denser and more intentional than previous output.
Example: Engineering team installing taste rules in Claude Code for a B2B component library
A four-person frontend team maintains a shared React component library used across three B2B products. They use Claude Code for rapid component scaffolding. The team lead wants all developers to produce components with consistent design quality when using the agent. The existing design system has custom spacing tokens defined in a CSS custom properties file.
claude/directory in the component library repository root. md files but customize the spacing file before installing. The original file specifies a 4px base unit, but the team's design system uses a 6px base unit with tokens named--space-1through--space-10`. css.
--space-2 (12px) for tight component padding. --space-3 (18px) for standard component padding. md. md at the project root that says: "This is a shared component library.
claude/ before generating any component code. " They open Claude Code, run a verification prompt, and Claude accurately summarizes all five rule files plus the token reference. They generate a test DataTable component. The output uses the team's spacing tokens, applies a type scale consistent with the existing components, and omits entrance animations on table rows (per the motion rules).
They commit everything, open a PR, and add installation verification to the team's onboarding checklist.
Example: Designer-developer hybrid using v0 for rapid prototyping with taste constraints
A product designer who writes frontend code uses v0 by Vercel to quickly prototype landing page sections. They want v0's output to match their portfolio's visual standard, which emphasizes tight spacing, a 1.2 type scale, and no decorative shadows. v0 does not have a file system, so installation requires a different approach.
The designer opens their v0 project and navigates to the project-level instructions panel (not the per-prompt chat). md files, typography and spacing, directly into this panel, separated by markdown headings. They add a third custom section: "Do not use box-shadow for decorative purposes. Use border (1px solid) for card boundaries.
" They save the project instructions. " The output uses a clear type hierarchy (48px headline, 20px subhead, 16px bullets), tight vertical spacing (16px between headline and subhead, 24px before the bullets), and no shadow on the button. The feature bullets use 8px gap between icon and text. The designer compares this to a v0 generation from a project without instructions: that version used 64px of vertical padding, a drop shadow on the button, and identical font sizes for subhead and bullets.
The taste-constrained version looks significantly more polished. Because v0 does not support file-based instructions across sessions, the designer saves the instruction text in a local markdown file for easy re-pasting when starting new v0 projects.
Example: Open-source maintainer configuring Codex and Gemini CLI on the same monorepo
An open-source maintainer runs a design system monorepo with packages for React, Vue, and Svelte components. Contributors use a mix of Codex and Gemini CLI. The maintainer wants taste rules to apply regardless of which agent a contributor uses. The monorepo uses pnpm workspaces with packages in a `packages/` directory.
md file at the root for Gemini CLI users. md files (typography, spacing, layout-density) under clearly marked markdown headings. md inside packages/react/ that adds React-specific rules: "Use CSS custom properties for all spacing and typography values. Do not use inline style objects for spacing.
md` files with framework-specific rules. The maintainer tests both agents. " The output uses the global taste rules for spacing and typography plus the React-specific token rules. " The output follows the global taste rules (tight padding, type scale, no decorative shadows).
Best Practices
Install one SKILL.md file at a time and verify its effect before adding the next. If you drop five files in at once and the output looks wrong, you cannot tell which file is causing the problem. Start with typography, verify it works, then add spacing, then layout density. This incremental approach takes slightly longer but produces a reliable, debuggable configuration.
Keep SKILL.md files under version control and treat them as project configuration, not personal dotfiles. When one developer has taste rules installed and another does not, the same prompt produces different output, which creates inconsistency in the codebase. Committing the files to the repo ensures every team member and every CI pipeline gets the same design constraints.
Review and update SKILL.md files quarterly, or whenever your design system changes. Stale rules that reference old spacing tokens or deprecated component patterns will cause the agent to generate code that does not match your current system. Set a calendar reminder or tie the review to your design system's release cycle.
Use explicit, specific rules rather than aspirational language. "Use a 1.25 type scale ratio with 16px base" is a rule the agent can follow. "Make the typography feel premium" is a vibe the agent will interpret unpredictably. Every rule in a SKILL.md file should be testable: you should be able to look at the generated code and say definitively whether the rule was followed or not.
Test your installation against at least three different component types (a form, a card, and a data table) before considering it complete. Different component types stress different rules. A card tests spacing and hierarchy. A form tests label alignment and input density.
A data table tests information density and column spacing. If the rules work for all three, they will work for most components.
When using agents that support scoped instructions (like Codex's directory-level AGENTS.md), place general taste rules at the project root and component-specific overrides in subdirectories. For example, your root AGENTS.md contains global typography and spacing rules, while a
/components/dashboard/AGENTS.mdadds density rules specific to dashboard widgets. This mirrors how design systems scope tokens by context.Do not duplicate rules across multiple instruction files. md specify font sizes, the agent receives conflicting signals. Each domain file should own its domain exclusively. Typography owns type scale, font family, and line height.
Spacing owns margin, padding, and gap. If a rule touches two domains, put it in whichever domain is primary and reference the other.
Common Mistakes
Placing SKILL.md files in the wrong directory or using the wrong file name convention
Correction
This is the most common installation failure and it is completely silent. The agent does not throw an error when it cannot find instruction files. It simply operates without them. The telltale sign is output that looks identical to what the agent produces in any project without custom instructions: generous padding, no type scale, default border-radius values.
Fix it by verifying the exact directory path your agent expects. md. cursor/rules/. Spell them exactly, including the leading dot and correct casing.
Installing all SKILL.md files but leaving conflicting instructions from a previous setup
Correction
This surfaces as inconsistent output: sometimes the agent follows taste rules, sometimes it does not, and sometimes it produces a confusing hybrid. The root cause is that the agent is trying to reconcile two contradictory instructions, like a SKILL.md saying "4px base spacing" and an older instruction saying "use Tailwind's default spacing scale." Search all instruction files in the project for spacing, typography, and layout keywords. Remove or update any rule that conflicts with the Taste Skill files. After cleanup, run the smoke test again to confirm consistent output.
Pasting SKILL.md content into a per-prompt message instead of a persistent instruction file
Correction
md content into their chat prompt because they are unsure about file-based installation. This works for a single generation but fails on the next prompt because per-prompt context does not persist. The agent forgets the rules as soon as the conversation moves on. You will notice this when the first component looks good but subsequent components in the same session revert to generic defaults.
The fix is always file-based installation for agents that support it. For v0, which does not have a file system, paste the content into the project-level instructions panel (not the chat input), which persists across prompts within that project.
Writing SKILL.md rules in vague, aspirational language instead of specific constraints
Correction
Rules like "create beautiful, well-designed interfaces" or "follow good design principles" give the agent no actionable constraint. The output will look exactly the same as without the rule, because the agent already attempts to produce "good" output by default. md files are installed and being read (the agent can summarize them), but the output shows no improvement. Replace every aspirational rule with a specific, measurable constraint.
Instead of "use good spacing," write "use a 4px base spacing unit. Component internal padding should be 12px or 16px. Section spacing should be 24px or 32px.
Not verifying installation with a smoke test
Correction
Many developers install the files, see them in the directory, and assume they are working. But file presence does not guarantee file reading. The agent might be scoped to a different directory, the file might have a parsing error that causes it to be silently skipped, or another instruction file might be overriding the taste rules. Always run the two-part verification: first, ask the agent to describe its loaded rules.
Second, generate a test component and inspect the output for specific signals of the taste rules (type scale, spacing values, density). Skipping this step means you might develop for days or weeks without the rules actually being applied.
Installing taste rules only on one developer's machine in a team project
Correction
md files are not committed to version control, only the developer who installed them gets design-quality output. Other team members, and any CI/CD pipeline using AI agents, produce generic output. Over time, the codebase accumulates a mix of taste-constrained and unconstrained components, creating visual inconsistency. The fix is straightforward: commit the instruction files and their directories to the repository.
Add a note to your README explaining the files. Treat them the same way you treat ESLint configs or Prettier settings, as shared project configuration that every contributor inherits.
Other Skills in This Method
Enforcing Typography and Spacing Standards in AI-Generated UI
Teaches how to write and apply SKILL.md rules that govern font sizing, line height, letter spacing, whitespace, and visual density to eliminate generic-looking layouts.
Adding Motion and Interaction Taste Rules
How to specify animation timing, easing curves, hover states, and transition guidelines in SKILL.md files so AI-generated interfaces feel polished and intentional.
Writing Anti-Slop Design Review Rules
How to author SKILL.md checklist rules that catch common AI-generated UI anti-patterns such as oversized padding, default border-radius, and bland color choices before code ships.
Configuring Layout and Visual Density Constraints for AI Agents
Teaches how to define grid, container, and density rules inside skill files so AI agents produce tighter, more intentional page compositions instead of loosely spaced defaults.
Auditing AI-Generated Frontends for Design Quality
A structured review workflow for evaluating AI-produced React and Next.js interfaces against Taste Skill criteria covering hierarchy, contrast, alignment, and component consistency.
Authoring Portable SKILL.md Files for Design Systems
Teaches how to create reusable, framework-agnostic SKILL.md instruction files that encode your team's design-system tokens, component conventions, and aesthetic judgment for any AI agent.
Frequently Asked Questions
How do I install taste skill claude files if my agent is not on the supported list?
Most AI coding agents follow one of two patterns: file-based instructions (a specific markdown file in a specific directory) or pasted system instructions (a text field in the UI). md content there. If it supports only per-prompt context, paste the rules at the start of each session. md files is agent-agnostic. Only the installation location changes.
How long should installing SKILL.md files take for a new project?
For a single agent with no existing instruction files and no design system customization, installation takes about 10-15 minutes: create the directory, copy the files, verify the agent reads them, run one smoke test. If you have existing instruction files that might conflict, add 10-15 minutes for conflict resolution. If you need to customize the SKILL.md rules to match an existing design system's tokens, add 15-30 minutes depending on how many token values you need to map. Total range: 10 minutes for the simplest case, 60 minutes for a complex setup with multiple agents and a custom design system.
Should I install SKILL.md files before or after setting up my design system tokens?
Install after your design tokens exist, even if they are preliminary. md files reference spacing values, type scales, and color constraints. md files to reference your tokens instead of the framework defaults. Installing taste rules that say "use 4px base unit" when your design system uses an 8px base unit creates conflicting output. If you do not have a design system yet, the Taste Skill defaults are a reasonable starting point and can be updated later.
Can I use the same SKILL.md files across multiple projects?
Yes, if the projects share the same design system or if you are using the framework's default values without customization. md files are plain markdown with no project-specific references by default. Copy them into each project's instruction directory. md file and maintain project-specific forks with customized token references. md files and use symlinks or a script to distribute them to project directories.
Why does my agent's output still look generic after installing taste skill files?
There are four common causes. First, the files are in the wrong directory and the agent is not reading them. Verify by asking the agent to summarize its rules. Second, existing instructions are overriding the taste rules. Search all instruction files for conflicting spacing or typography directives. Third, the rules are too vague. If you wrote "use good spacing" instead of "use 12px component padding," the agent has nothing specific to follow. Fourth, your prompt is overriding the rules. If your prompt says "make it spacious and airy," that contradicts tight-spacing taste rules. md files control design decisions.
How do I update SKILL.md files when the Taste Skill framework releases new versions?
Download the updated files from the framework repository and compare them against your installed versions. If you customized the files with project-specific tokens, do not overwrite your versions directly. Instead, diff the new version against your current version to identify new rules, changed thresholds, or removed rules. Apply the changes you want while preserving your customizations. If you did not customize the files, you can replace them directly. After updating, always re-run the verification and smoke test steps to confirm the agent reads the new rules correctly and the output matches your expectations.
Do SKILL.md files slow down my AI coding agent's response time?
Not in any way you would notice. md files are typically 500-2000 words each. Even installing all five files adds roughly 5000-8000 tokens to the agent's context, which is a small fraction of the 100K-200K token context windows that modern agents support. The agent processes these tokens in milliseconds. The output quality improvement far outweighs any theoretical latency increase. md files are not the cause. Look at conversation history length instead.