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    🎨 Brand Consistency Linter

    1

    It eliminates the "drift" that happens when taglines are updated or social links change, but old documentation isn't refreshed.

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    🎨 Brand Consistency Linter

    🎨 Brand Consistency Linter

    Example session with this skill installed

    Audit my project's README.md and footer.txt files against our brand spec to ensure consistency.

    • Read your context and instructions
    • Compiled the brand consistency linter
    • Generated the UI component

    Brand Audit Results

    Scope: README.md, footer.txt
    Findings:

    • [High] Rule v1-tagline: Inconsistent tagline in README.md:12. Found "Fastest AI tool", expected "The World's Pro-Grade AI Orchestrator".
    • [Med] Rule link-check: Outdated Twitter URL in footer.txt:2.
      Remediation: Update tagline using snippet SNIP-04.

    brand-consistency-linter.tsx

    TSX · React component

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Audit GitHub bios and READMEs for outdated product taglinesDetect forgotten placeholders or "TODO" links in public documentationEnsure consistent social media links across all footer filesValidate brand naming conventions in technical documentation

    About this skill

    Automated Brand Compliance for Developers

    The Brand Consistency Linter is a specialized audit tool designed to ensure your project's public-facing surfaces—like GitHub bios, website footers, and profile READMEs—perfectly align with your official brand guidelines. It eliminates the "drift" that happens when taglines are updated or social links change, but old documentation isn't refreshed.

    What it does

    • Scans local Markdown and text files against a centralized brand-spec.json.
    • Identifies inconsistent taglines, outdated brand names, and broken link patterns.
    • Detects forgotten "INSERT LINK HERE" or "BRAND_NAME" placeholders.
    • Provides structured findings including severity levels, line numbers, and rule IDs.

    Why use this skill?

    Unlike a general LLM prompt which might hallucinate or miss subtle inconsistencies, this skill uses a deterministic Python-based scanner backed by a formal specification. It acts as a linting layer for your brand identity, ensuring 100% adherence to your source of truth without the risk of an AI "improving" your copy in unauthorized ways. It provides actionable remediation snippets instead of just vague advice.

    Output details

    You receive a comprehensive audit report detailing the inspected scope, the specific rules applied, a categorized list of violations, and recommended copy fixes based on your approved remediation library.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

    Skills folder by agent

    Click the path to copy it. Create the folder if it does not exist yet.

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    Fresh listing

    Recently published to Agensi

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    Trust & safety

    Security scanned

    Verified clean 3 months ago

    • Passed all security checks, Safe to install

    Listed3 months ago

    Frequently Asked Questions