Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
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.
[](https://agentmods.dev/rules/thatrebeccarae/claude-marketing/content-creator)<a href="https://agentmods.dev/rules/thatrebeccarae/claude-marketing/content-creator"><img src="https://agentmods.dev/badge/rules/thatrebeccarae/claude-marketing/content-creator.svg" alt="Measured on agentmods" 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 | $0.00067 | $0.01879 |
| Opus 5 | $0.00034 | $0.00940 |
| Sonnet 5 | $0.00013 | $0.00376 |
| Haiku 4.5 | $0.00007 | $0.00188 |
Grade A, and why
content-creator 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 6d 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 — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Creator
Professional-grade brand voice analysis, SEO optimization, and platform-specific content frameworks with executable Python tools.
Core Workflows
Brand Voice Development
-
Analyze Existing Content (if available)
python scripts/brand_voice_analyzer.py existing_content.txt -
Define Voice Attributes
- Review brand personality archetypes in REFERENCE.md
- Select primary and secondary archetypes
- Choose 3-5 tone attributes
- Document in brand guidelines
-
Create Voice Sample
- Write 3 sample pieces in chosen voice
- Test consistency using analyzer
- Refine based on results
Creating SEO-Optimized Blog Posts
-
Keyword Research
- Identify primary keyword (search volume 500-5000/month)
- Find 3-5 secondary keywords
- List 10-15 LSI keywords
-
Content Structure
- Use blog template from REFERENCE.md
- Include keyword in title, first paragraph, and 2-3 H2s
- Aim for 1,500-2,500 words for comprehensive coverage
-
Optimization Check
python scripts/seo_optimizer.py blog_post.md "primary keyword" "secondary,keywords,list" -
Apply SEO Recommendations
- Adjust keyword density to 1-3%
- Ensure proper heading structure
- Add internal and external links
- Optimize meta description
Social Media Content Creation
- Platform Selection — Identify primary platforms based on audience
- Content Adaptation — Start with core message, use repurposing matrix from REFERENCE.md
- Optimization — Platform-appropriate length, optimal posting time, correct image dimensions
Content Calendar Planning
- Monthly Planning — Set goals and KPIs, identify key themes
- Weekly Distribution — Follow 40/25/25/10 content pillar ratio
- Batch Creation — Create all weekly content in one session
Key Scripts
brand_voice_analyzer.py
Analyzes text content for voice characteristics, readability, and consistency.
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.
- 6d ago First seen · 258 lines · 67 tokens per session scan A be4315a434f9
content-creator is a cursor rule published in the GitHub repository thatrebeccarae/claude-marketing (130 stars, last pushed 3mo ago), licensed MIT. It adds 67 tokens to every session and 1,879 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 2026-08-30.
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