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    🎨 Brand Consistency Linter

    🎨 Brand Consistency Linter

    by JustHandled Labs

    Hold your bios, footers, and profiles to one brand spec. Flags brand-name spelling and casing that does not match your canonical form, off-spec taglines, links that are not on your official list, leftover placeholders (Lorem, TODO, "your tagline here"), and handles that differ from one surface to the next. You define the spec once and it enforces it everywhere.

    Updated Jun 2026
    Security scanned
    Cursor

    $12

    Β· or 60 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Audit GitHub bios and READMEs for outdated product taglines
    • Detect forgotten placeholders or "TODO" links in public documentation
    • terminal, file_read automation included
    • Ready for Cursor
    • Instant install

    Sample input

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

    Sample output

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    • [Med] Rule link-check: Outdated Twitter URL in footer.txt:2.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

    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 surfacesβ€”like GitHub bios, website footers, and profile READMEsβ€”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    • Identifies inconsistent taglines, outdated brand names, and broken link patterns.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.

    Use Cases

    • Audit GitHub bios and READMEs for outdated product taglines
    • Detect forgotten placeholders or "TODO" links in public documentation
    • Ensure consistent social media links across all footer files
    • Validate brand naming conventions in technical documentation

    Reviews

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    Security Scanned

    Passed automated security review

    Permissions

    Terminal / Shell
    Read Files

    Allowed Hosts

    example.com

    File Scopes

    brand-consistency-linter/**
    **/*.md
    **/*.txt
    references/brand-spec.json (your spec)

    Loads your canonical name, taglines, official links, handle, and placeholder list from an editable references/brand-spec.json. Reads no environment variables and rewrites nothing.

    Tags

    brand-management
    linting
    documentation
    compliance
    marketing-ops

    Works with any agent that can read text files and run a local Python script (Claude Code, Cursor, Codex CLI, and other SKILL.md-compatible agents). Standard library only, no install step. No network calls.

    Creator

    JustHandled Labs

    JustHandled Labs creates focused agent skills and workflow packs for Claude, Codex, Cursor, and AI-assisted builders. Each tool is designed around a real repeatable task: cleaner commits, better PRs, stronger handoffs, safer repo hygiene, clearer documentation, and less copy-paste chaos. The goal is not generic AI productivity. The goal is specific workflows that are easier to run, review, and repeat. Maintained by H.J. Westerfield, with a background in communications, editing, project coordination, customer support, and practical AI systems. JustHandled Labs builds tools for people who want useful automation without theatrical complexity.

    Frequently Asked Questions

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