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kapishdimakapishdima/fonttrio/skills/suggest-improvements/SKILL.md

suggest-improvements

Skill451 starsChanged 8 months agoMITView on GitHub

Analyze your project and suggest the best font pairing

1 other project uses a version of this.

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  • Other versions1 project uses a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 1

    1. ethanplusai/astro-conversion-kit★ 114same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository2 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 2 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Call search_pairings with the identified mood and use case

    line 30
  2. Very specific:

    Call preview_pairing on the top 2-3 results

    line 31
  3. Distinctive:

    Ask the user if they want to install it

    line 33
  4. Very specific:

    If yes, call install_pairing to install it

    line 34
  5. Distinctive:

    If MCP is not available:

    line 36

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

You are a typography consultant. Analyze the user's project to understand its purpose, mood, and tech stack, then recommend the best font pairing from Fonttrio.

Steps

  1. Analyze the project — Read key files to understand:
    • package.json — framework, dependencies, project type
    • README.md or landing page — what the project does
    • Existing styles — current design language, color scheme
    • Component structure — UI complexity level
  2. Determine characteristics:
    • Type: SaaS, blog, portfolio, e-commerce, documentation, dashboard, marketing site
    • Mood: clean, elegant, playful, professional, technical, creative, minimal
    • Audience: developers, designers, general users, enterprise
  3. Build a recommendation — Compose a brief profile:
    Project: [name]
Type: [type]
Mood: [mood keywords]
Audience: [target audience]

  4. Find the best pairing — If the Fonttrio MCP server is available:

    • Call search_pairings with the identified mood and use case
    • Call preview_pairing on the top 2-3 results
    • Compare and recommend the best match with reasoning
    • Ask the user if they want to install it
    • If yes, call install_pairing to install it

    If MCP is not available:

    • Based on the analysis, suggest visiting https://www.fonttrio.xyz and filtering by the identified mood/use case
    • Recommend the manual install command format: bunx shadcn@latest add https://www.fonttrio.xyz/r/{pairing-name}.json
    • Note: For the full AI-powered experience with automatic search and installation, set up the Fonttrio MCP server. See https://www.fonttrio.xyz/ai for setup instructions.
  5. Explain the recommendation — For the chosen pairing, explain:
    • Why it matches the project's mood and audience
    • What each font brings (heading, body, mono)
    • How the typography scale will affect the design

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