Agent skill

Frontend From Generated Image

by adamholter in adamholter/hive-mind-landing-page

A skill your agent uses for frontend/UI builds, redesigns, polish, or extensions.

MITAuto-check passedFrontend & Design

Install Frontend From Generated Image

skills CLI
$ npx skills add adamholter/hive-mind-landing-page --skill frontend-from-generated-image -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install adamholter/hive-mind-landing-page frontend-from-generated-image --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/adamholter/hive-mind-landing-page.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/frontend-from-generated-image .claude/skills/frontend-from-generated-image && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
frontend-from-generated-image
GitHub stars
160
Used in
1 other repo
Token cost
~2k tokens
SKILL.md length
1,101 words
Files
1
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses for frontend/UI builds, redesigns, polish, or extensions.

  • Works in 6 steps: Use the imagegen skill and the built-in… → If iterating on an existing UI, first… → Generate or accept at least one UI… → …
  • Frontend/UI builds
  • SKILL.md covers Core rule, Workflow, Prompting guidance for the image and Image-to-code translation rules, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Frontend From Generated Image is an agent skill from adamholter/hive-mind-landing-page. Use for frontend/UI builds, redesigns, polish, or extensions. Before coding, generate a UI reference image, then closely match it instead of inventing a new direction.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Frontend & Design, covering Frontend development and Landing pages. The repository describes itself as: CHORUS Hive Mind landing page — source, prompts, frontend skills, generated design reference, and sanitized Codex build trace. The licence is MIT.

When your agent uses it

  • Frontend/UI builds
  • Tasks that involve Frontend development
  • Tasks that involve Landing pages

Example prompts

  • “/frontend-from-generated-image”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Use the imagegen skill and the built-in OpenAI image generation tool.
  2. If iterating on an existing UI, first gather reference screenshots of the current experience unless the user explicitly wants a full…
  3. Generate or accept at least one UI design reference image for the requested interface.
  4. Treat the reference image as the design source of truth, while preserving existing-product constraints when the task is iterative.
  5. Implement the frontend by copying the image's layout, hierarchy, spacing, typography, color relationships, asset placement, and overall…
  6. Verify with screenshots and refine until the rendered result visibly matches the reference.

What it can do on your machine

Read from SKILL.md and the folder at commit d43dcd1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Frontend From Generated Image loads about 2k tokens when it runs. Until then it costs about 49 tokens; SKILL.md has 1,101 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~49
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from adamholter/hive-mind-landing-page at commit d43dcd1, republished under its MIT licence (© adamholter). 1,101 words, ~1,952 tokens.

Download SKILL.mdSave it as .claude/skills/frontend-from-generated-image/SKILL.md (or your agent's skills folder).
name
frontend-from-generated-image
description
Use for frontend/UI builds, redesigns, polish, or extensions. Before coding, generate a UI reference image, then closely match it instead of inventing a new direction.

Frontend From Generated Image

Use this skill for any task that includes a frontend, screen, page, component set, dashboard, landing page, app shell, modal, chat UI, or other visible interface.

When the task is an iteration on an existing UI rather than a full redesign, treat the current UI as an important constraint.

This skill is intentionally strict: the generated or user-provided image is not a moodboard. It is the target. The implementation should look like a faithful translation of the image into working code.

Core rule

Before writing frontend code:

  1. Use the imagegen skill and the built-in OpenAI image generation tool.
  2. If iterating on an existing UI, first gather reference screenshots of the current experience unless the user explicitly wants a full redesign.
  3. Generate or accept at least one UI design reference image for the requested interface.
  4. Treat the reference image as the design source of truth, while preserving existing-product constraints when the task is iterative.
  5. Implement the frontend by copying the image's layout, hierarchy, spacing, typography, color relationships, asset placement, and overall composition as closely as practical in real code.
  6. Verify with screenshots and refine until the rendered result visibly matches the reference.

Do not skip the image-generation step unless the user explicitly tells you not to.

Workflow

  1. Read the product/task requirements and infer the key UI surfaces that need to exist.
  2. If the task is modifying an existing frontend, collect reference screenshots of the current UI first.
  3. Unless the user asked for a full redesign, use those screenshots as reference inputs and constraints for the design-generation prompt.
  4. Write a design-generation prompt for the interface.
  5. Generate the reference image with the built-in OpenAI image tool.
  6. Inspect the result and write a concrete visual brief before coding:
    • layout structure
    • alignment and spacing
    • type scale
    • component shapes
    • color palette
    • background treatment
    • visual density
    • major asset locations and dimensions
    • element ordering and z-index/layer relationships
    • motion cues implied by the composition
  7. Build the real frontend to match that image closely. Work one section or screen at a time when the reference contains multiple sections.
  8. Capture a screenshot of the implementation at the same viewport/aspect ratio as the reference.
  9. Compare screenshot to reference and fix mismatches in layout, spacing, scale, color, asset placement, and typography before moving on.
  10. If the generated image is weak, generate another one and use the stronger reference.

Prompting guidance for the image

When prompting the image model:

  • Describe the product type and exact screen to render.
  • Ask for a polished product UI mockup, not an abstract moodboard.
  • Specify the platform when relevant: desktop web app, mobile app, landing page, chat tool, admin panel, etc.
  • Include the desired tone and brand feel.
  • Ask for clear hierarchy, refined spacing, and realistic interface composition.
  • Request a full-screen UI screenshot/mockup perspective.
  • If the tool already has an established product direction, preserve it rather than reinventing it.
  • If iterating on an existing UI, provide the current UI screenshots as references whenever the image workflow supports that.
  • For iterative work, prompt for an improved version of the current design rather than a replacement design, unless the user explicitly asked for a full redesign.

Image-to-code translation rules

  • Do not rebuild illustrated/photo/3D assets with CSS, SVG primitives, gradients, or decorative divs. Use real image assets for those parts.
  • If the reference contains embedded product art, character art, photos, renderings, textures, icons, or abstract image panels, create explicit asset slots in the project and tell the user or future agent exactly where those files belong.
  • If the user supplied extracted assets, use those assets directly and clone the surrounding layout, components, typography, spacing, and effects.
  • If assets need transparent backgrounds, use the local fal-media-gen Pixelcut Background Remover workflow; do not send the user to external web tools, fake transparency with white boxes, or rebuild image assets in CSS.
  • For multi-section pages, translate one section at a time. Do not rough in all sections and hope the overall impression carries the design.
  • Preserve the exact visual hierarchy of the reference: what is biggest, what is quietest, what aligns to what, and where the eye lands first.
  • Measure proportions from the reference when possible: viewport coverage, section height, image aspect ratios, column widths, gutters, nav height, button height, and card density.
  • Use CSS variables or design tokens for colors, spacing, radii, and shadows that visibly repeat in the reference.
  • Avoid adding extra explanatory copy, extra cards, extra badges, or extra decoration that is not present in the reference.
  • When text in the generated image is unreadable or nonsensical, replace it with concise realistic copy while preserving the same line lengths, weight, hierarchy, and density.
Show full SKILL.md (320 more words)Show less

Implementation guidance

  • Copy the generated image, do not merely "take inspiration from it."
  • For iterative work, preserve the recognizable product structure and only change what the task calls for.
  • Match the big decisions first: composition, scale, contrast, and layout rhythm.
  • Then match the smaller decisions: radii, borders, shadows, gaps, card proportions, and type treatment.
  • Preserve usability and accessibility while translating the image into production code.
  • If the generated image includes impossible or unclear details, infer the closest practical implementation without changing the visual direction more than necessary.

Fidelity checklist

Before calling the implementation done, check these against the reference image:

  • Same viewport framing: hero/section height, first-fold composition, and visible next-section hint when applicable.
  • Same macro layout: column count, alignment, negative space, overlap, asymmetry, and section rhythm.
  • Same visual weight: heading scale, supporting text scale, button prominence, image size, and card density.
  • Same color relationships: background, text contrast, accent amount, borders, shadows, and gradients.
  • Same component geometry: radii, stroke weights, padding, gaps, and icon/button sizes.
  • Same asset behavior: images use correct aspect ratio, cropping, object position, transparency, and layering.
  • Same responsive intent: mobile should feel like a faithful adaptation, not a different design.
  • No accidental additions: remove default nav text, generic feature cards, filler badges, random icons, and decorative effects that were not in the reference.

If the screenshot does not match, keep iterating. Name the top mismatches, patch them, and screenshot again.

Priority over default design behavior

If another frontend skill suggests inventing a fresh visual direction, this skill takes priority for UI direction. The generated image should anchor the design.

Deliverable behavior

For frontend tasks covered by this skill, the expected flow is:

  1. Generate the reference image.
  2. Extract or prepare any needed assets and define their project paths.
  3. Build the UI to match the reference section-by-section or screen-by-screen.
  4. Verify the implementation visually with screenshots.
  5. Refine toward the reference until the main mismatches are resolved.

© adamholter, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/frontend-from-generated-image of adamholter/hive-mind-landing-page.

Open the folder on GitHubat commit d43dcd1

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in adamholter/hive-mind-landing-page, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Frontend From Generated Image next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Frontend From Generated Image compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Frontend From Generated Image this skilladamholter/hive-mind-landing-page1601 repos~2kAutomated safety check: PassMIT
Design StyleCastor6/tactus3761 repos~2.1kAutomated safety check: PassApache-2.0
Design-Led Website Builderliucongg/liucong-skills248—~1.3kAutomated safety check: PassApache-2.0
Gridgeistohmiler/gridgeist115—~2.6kAutomated safety check: PassMIT
Frontend Designudecode/plate17k—~3.6kAutomated safety check: PassCustom licence
Bryl Minimal Designbryllim/bryl-minimal-design114—~2.9kAutomated safety check: PassMIT

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Questions about Frontend From Generated Image

What does Frontend From Generated Image do?

A skill your agent uses for frontend/UI builds, redesigns, polish, or extensions. Frontend From Generated Image is an agent skill from adamholter/hive-mind-landing-page. Use for frontend/UI builds, redesigns, polish, or extensions.

When should I use Frontend From Generated Image?

Frontend From Generated Image fits situations like: frontend/UI builds; tasks that involve Frontend development; tasks that involve Landing pages.

How do I install Frontend From Generated Image in Claude Code?

Run `npx skills add adamholter/hive-mind-landing-page --skill frontend-from-generated-image -a claude-code`. Or copy the skill folder (skills/frontend-from-generated-image in adamholter/hive-mind-landing-page) into .claude/skills/frontend-from-generated-image in your project. Claude Code loads it when a task matches its description.

How do I install Frontend From Generated Image in Codex?

Run `npx skills add adamholter/hive-mind-landing-page --skill frontend-from-generated-image -a codex`. Or copy the skill folder (skills/frontend-from-generated-image in adamholter/hive-mind-landing-page) into .agents/skills/frontend-from-generated-image in your project. Codex loads it when a task matches its description.

Can I use Frontend From Generated Image in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add adamholter/hive-mind-landing-page --skill frontend-from-generated-image -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/frontend-from-generated-image, .gemini/skills/frontend-from-generated-image, .github/skills/frontend-from-generated-image and .opencode/skills/frontend-from-generated-image in your project.

What does Frontend From Generated Image need to run?

SKILL.md names no scripts, command-line tools or credentials: Frontend From Generated Image is instructions for the agent only.

Does Frontend From Generated Image access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Frontend From Generated Image safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Frontend From Generated Image use?

Frontend From Generated Image is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Frontend From Generated Image use?

About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Frontend From Generated Image?

Skills that share tags, products or a category with Frontend From Generated Image: Design Style (Castor6/tactus, 376 stars), Design-Led Website Builder (liucongg/liucong-skills, 248 stars), Gridgeist (ohmiler/gridgeist, 115 stars) and Frontend Design (udecode/plate, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Frontend From Generated Image?

adamholter (a GitHub user) maintains it in adamholter/hive-mind-landing-page, which has 160 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on July 9, 2026.

Source: adamholter/hive-mind-landing-page on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.