joy-check
FeaturedValidate content framing on joy-grievance spectrum.
Install
Quality Score: 95/100
Skill Content
Details
- Author
- notque
- Repository
- notque/vexjoy-agent
- Created
- 5 months ago
- Last Updated
- 2 days ago
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
content-quality-check
Editorial QA pass that catches AI tells, template language, hollow hedges, weak closers, and brand-voice violations in any draft before it publishes. Runs a deterministic linter (slop phrases, LLM-overrepresented words, "not just X, it's Y" reframes, em-dash chaining, rhetorical-question openers, announcement cliches, the brand's own Avoid list) and then an editorial judgment pass (throat-clearing openers, closers that restate the open, claims without proof, specificity, voice-pillar conformance). Reports findings by severity with line references and a fix per flag; rewrites only on request. Use whenever the user says "review this draft", "QA this post", "check for AI tells", "does this sound AI-written", "editorial review", "content quality check", "de-slop this", or is about to publish copy. Enforces the standard that brand-voice-guide builds; works standalone with the universal checklist when no voice directory exists.
clear-and-human
Construct, review, score, and rewrite written content so it reads like a specific human wrote it, not an AI. Use this skill whenever the user wants to: write or draft prose for humans (docs, README, runbook, ADR, PR/commit message, blog post, LinkedIn post, email, Slack message, or a spoken explainer/tutorial video script); humanize or de-slop AI-generated text; check whether writing "sounds like AI"; review a draft for AI texture; rewrite content in their own voice; score a draft for authenticity or clarity; or tighten and sharpen prose. Also trigger on "humanize", "make it sound human", "sounds like AI", "does this sound like AI", "voice check", "review my draft", "rewrite in my voice", "tighten this up", "edit for clarity", "video script", "explainer script". Auto-detects content type and applies channel-specific rules. Defaults to a neutral, factual voice and never invents specifics to add texture. For deliberately persuasive marketing copy (ads, hooks, LinkedIn/Bluesky growth posts, video titles and thum
a11y-content-judgment
Load this skill when an audit needs the judgment-shaped WCAG criteria that scanners cannot decide — are page titles, headings, form labels, link text in context, and image alternatives actually useful, meaningful, and descriptive for the person relying on them (2.4.2, 2.4.6, 2.4.4, 1.1.1), and is navigation consistent across pages (3.2.3, 3.2.4)? It inventories every such element across a URL list, attaches deterministic heuristic flags, has a model draft a per-row judgment with a rationale, and hands the rows to a named human ratifier as a CSV. Output is always a DRAFT; a row becomes a criterion outcome only when a human ratifies it. Never use it to flip an outcome-map cell, to judge criteria that need interaction or assistive technology, or as a substitute for a11y-test's measurement.