market-copy

market-copy is a skill for Claude Code, Codex from zubair-trabzada/ai-marketing-claude. It costs 0 tokens per session (2,983 once invoked), scanned A, original, MIT.

A copywriting tool for reviewing website text and creating alternative wording. It examines headings, paragraphs, buttons, navigation, metadata, testimonials, and other page content based on the type of page and business.

In plain words
What is it for?
Use it to analyze a website page, score its copy, identify its page type, and create an optimization report with replacement examples.
Why use it?
It helps identify unclear or weak website wording and shows specific before-and-after suggestions. It also provides a structured review instead of relying on general editing advice.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to analyze a website page, score its copy, identify its page type, and create an optimization report with replacement examples.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zubair-trabzada/ai-marketing-claude/market-copy
About the project

AI Marketing Suite for Claude Code is a collection of marketing skills and parallel agents that analyze websites and produce copy, email sequences, campaigns, content calendars, competitor research, and reports. Entrepreneurs, agencies, and solo operators use it to run marketing workflows from Claude Code, and the catalogue lists the suite's skills and agents.

zubair-trabzada/ai-marketing-claude · 2,639 stars · on GitHub · skool.com

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zubair-trabzada/ai-marketing-claude --skill market-copy
Clone the repo
git clone --depth 1 https://github.com/zubair-trabzada/ai-marketing-claude

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for market-copy

README.md
[![agentmods](https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-copy/github.svg)](https://agentmods.dev/skills/zubair-trabzada/ai-marketing-claude/market-copy)
Your own site
<a href="https://agentmods.dev/skills/zubair-trabzada/ai-marketing-claude/market-copy"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-copy/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for market-copy

Your own site · 80×15
<a href="https://agentmods.dev/skills/zubair-trabzada/ai-marketing-claude/market-copy"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-copy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,983 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.02983
Opus 5 $0.00000 $0.01491
Sonnet 5 $0.00000 $0.00597
Haiku 4.5 $0.00000 $0.00298

Measured 13d ago against content hash e047acc21d5b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

market-copy scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/market-copy/SKILL.md · 337 lines

How it starts

The opening of the file, as written. The whole thing — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Copywriting Analysis & Generation

You are the copywriting engine for /market copy <url>. You analyze existing website copy, score it, and generate optimized alternatives with specific before/after examples. Every recommendation is grounded in proven copywriting frameworks and tailored to the detected business type.

When This Skill Is Invoked

The user runs /market copy <url>. Fetch the target page(s), analyze the existing copy, score it, and produce both terminal output and a detailed COPY-SUGGESTIONS.md file.


Phase 1: Copy Discovery

1.1 Fetch and Parse

Use WebFetch to retrieve the target URL. Extract:

  • Primary headline (H1)
  • Subheadline / supporting headline
  • Hero section copy
  • All section headlines (H2, H3)
  • Body copy paragraphs
  • CTA button text (every instance)
  • Navigation labels
  • Footer copy
  • Meta title and meta description
  • Social proof elements (testimonials, stats, logos)

1.2 Detect Page Type

Identify what kind of page this is, because each type has different copy priorities:

Page Type Primary Goal Copy Priority
Homepage Communicate value prop, route visitors Headline clarity, navigation clarity, CTA hierarchy
Landing Page Single conversion action Headline-CTA alignment, objection handling, urgency
Pricing Page Drive plan selection Plan naming, feature framing, anchoring, FAQ
About Page Build trust and connection Story, mission, team credibility, values
Product Page Demonstrate value of specific product Feature-to-benefit translation, social proof, specifications
Feature Page Explain a specific capability Problem-solution framing, use cases, comparison
Blog Post Educate and capture leads Headline hook, intro engagement, CTA placement
Contact/Demo Page Capture lead information Form headline, friction reduction, trust signals

1.3 Voice and Tone Analysis

Before generating new copy, analyze the existing voice:

Read the full file on GitHub · 337 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 337 lines · 0 tokens per session scan A e047acc21d5b

Subscribe to this mod's changes

market-copy is a skill published in the GitHub repository zubair-trabzada/ai-marketing-claude (2,639 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,983 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

content-pillar-atomizer

Take 1 blog post or article and generate 15-30 platform-native micro-content pieces. Not reformatting — re-contextualizing for each platform's culture. Triggers on: "atomize this content", "repurpose my blog post", "turn this into social posts", "content atomizer", "pillar content", "one to many content", "repurpose…

Affitor/affiliate-skills · 136 tokens

marketing-os

A complete marketing department in one skill. Website and landing-page audits with weighted 0-100 scores, copywriting with panel scoring and AI-slop removal, an 18-tactic ad hook engine, GEO/AEO for getting cited by ChatGPT/Perplexity/AI Overviews, paid-ads creative diagnosis and production briefs, email sequences…

Yuzzyuk/marketing-os · 237 tokens

competitor-research-playbook

Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth flywheel? This gives you the complete SOP — from Wayback Machine snapshots to X/Twitter propagation analysis to growth flywheel scoring. Built from 150+ AI…

Gingiris-1031/gingiris-skills · 598 tokens

gr-competitor-research

Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth flywheel? This gives you the complete SOP — from Wayback Machine snapshots to X/Twitter propagation analysis to growth flywheel scoring. Built from 150+ AI…

Gingiris-1031/gingiris-skills · 582 tokens

content-pillar-atomizer

Take 1 blog post or article and generate 15-30 platform-native micro-content pieces. Not reformatting — re-contextualizing for each platform's culture. Triggers on: "atomize this content", "repurpose my blog post", "turn this into social posts", "content atomizer", "pillar content", "one to many content", "repurpose…

Gingg7260/affiliate-skills · 136 tokens

market-ads

Platform-native ad copy for Meta (Facebook/Instagram), Google Search, LinkedIn, TikTok, and YouTube with character-limit compliance, audience targeting notes, and creative briefs. Invoke whenever the user says "ad copy", "Facebook ads", "Google Ads", "LinkedIn ads", "TikTok ads", or runs /market ads . Respects…

rediumvex/ai-marketing-claude · 81 tokens