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 seaworld008/Commonly-used-high-value-skills --skill content-creatorgit clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-skillsWrote 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/seaworld008/commonly-used-high-value-skills/content-creator)<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/content-creator"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/content-creator/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/seaworld008/commonly-used-high-value-skills/content-creator"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/content-creator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00025 | $0.01772 |
| Opus 5 | $0.00013 | $0.00886 |
| Sonnet 5 | $0.00005 | $0.00354 |
| Haiku 4.5 | $0.00003 | $0.00177 |
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 4d 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 — 312 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.
Table of Contents
Keywords
content creation, blog posts, SEO, brand voice, social media, content calendar, marketing content, content strategy, content marketing, brand consistency, content optimization, social media marketing, content planning, blog writing, content frameworks, brand guidelines, social media strategy
Quick Start
Brand Voice Development
- Run
scripts/brand_voice_analyzer.pyon existing content to establish baseline - Review
references/brand_guidelines.mdto select voice attributes - Apply chosen voice consistently across all content
Blog Content Creation
- Choose template from
references/content_frameworks.md - Research keywords for topic
- Write content following template structure
- Run
scripts/seo_optimizer.py [file] [primary-keyword]to optimize - Apply recommendations before publishing
Social Media Content
- Review platform best practices in
references/social_media_optimization.md - Use appropriate template from
references/content_frameworks.md - Optimize based on platform-specific guidelines
- Schedule using
assets/content_calendar_template.md
Core Workflows
Workflow 1: Establish Brand Voice (First Time Setup)
For new brands or clients:
Step 1: Analyze Existing Content (if available)
python scripts/brand_voice_analyzer.py existing_content.txt
Step 2: Define Voice Attributes
- Review brand personality archetypes in
references/brand_guidelines.md - Select primary and secondary archetypes
- Choose 3-5 tone attributes
- Document in brand guidelines
Step 3: Create Voice Sample
- Write 3 sample pieces in chosen voice
- Test consistency using analyzer
- Refine based on results
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/content_calendar_template.md 1.6 KB
- examples/brand_voice_analysis_example.md 4.9 KB
- examples/seo_optimization_example.md 7.1 KB
- references/analytics_guide.md 8.6 KB
- references/brand_guidelines.md 6.7 KB
- references/content_frameworks.md 11 KB
- references/social_media_optimization.md 9.8 KB
- scripts/brand_voice_analyzer.py 6.5 KB runs code
- scripts/seo_optimizer.py 15 KB runs code
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.
- 4d ago Changed · -49 tokens per session ec4fb8915d3d
- 12d ago First seen · 312 lines · 74 tokens per session scan A ae030934dcee
content-creator is a skill published in the GitHub repository seaworld008/Commonly-used-high-value-skills (70 stars, last pushed 4d ago), licensed MIT. It adds 25 tokens to every session and 1,772 once invoked, about $0.0001 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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