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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

    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    • [Med] Rule link-check: Outdated Twitter URL in footer.txt:2.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.
    README.md

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

    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    • Identifies inconsistent taglines, outdated brand names, and broken link patterns.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 use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    What's inside

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