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.
npx skills add hamzaPixl/pixl-ai --skill content-marketinggit clone --depth 1 https://github.com/hamzaPixl/pixl-aiWrote 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.
[](https://agentmods.dev/skills/hamzapixl/pixl-ai/content-marketing)<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/content-marketing"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/content-marketing/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.
<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/content-marketing"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/content-marketing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.02725 |
| Opus 5 | $0.00030 | $0.01362 |
| Sonnet 5 | $0.00012 | $0.00545 |
| Haiku 4.5 | $0.00006 | $0.00272 |
Grade A, and why
content-marketing 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Content marketing pipeline: discover → strategize → create → optimize → validate. Analyzes the business type, target audience, and existing content to produce conversion-optimized copy, blog content plans, and content calendars. All output is actionable — written directly into the codebase or delivered as ready-to-use content files.
Step 1: Discovery
- Business analysis:
- Read the site's homepage, about page, and service/product pages
- Identify: business type, value proposition, target audience, tone of voice
- Detect existing brand language patterns (formal/casual, technical/approachable)
- Check for existing blog posts, case studies, or content sections
- Content inventory:
- List all pages with text content
- Identify thin pages (< 300 words)
- Identify pages without clear CTA
- Check for duplicate or near-duplicate content
- i18n check:
- Are there multiple locales?
- Which locales have content gaps?
- Competitor signals (if user provides competitors or business context):
- Use WebSearch to research common content topics in the industry
- Identify content gaps the site could fill
Output: Business profile, content inventory, identified gaps, audience persona.
Step 2: Content Strategy
Based on discovery, produce a strategy document. Choose the relevant business archetype:
SaaS Content Strategy
- Top of funnel: Problem-awareness blog posts, comparison guides, "how to" tutorials
- Middle of funnel: Feature deep-dives, integration guides, use case pages
- Bottom of funnel: Case studies, ROI calculators, pricing comparison, free trial CTA
- Retention: Changelog, product updates, best practices, advanced tutorials
E-commerce Content Strategy
- Product descriptions: Benefit-led, sensory language, size/spec tables
- Category pages: Buying guides, "best X for Y" content
- Blog: Styling guides, seasonal content, gift guides, care instructions
- Trust content: Reviews integration, shipping/return policy pages, FAQ
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.
- 11d ago First seen · 274 lines · 59 tokens per session scan A 79775797c5f4
content-marketing is a skill published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 4mo ago), licensed MIT. It adds 59 tokens to every session and 2,725 once invoked, about $0.0003 per session on Opus 5. 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 2026-08-31.
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