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.
git clone --depth 1 https://github.com/frankxai/agentic-creator-osWrote 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/agents/frankxai/agentic-creator-os/content-polisher)<a href="https://agentmods.dev/agents/frankxai/agentic-creator-os/content-polisher"><img src="https://agentmods.dev/badge/agents/frankxai/agentic-creator-os/content-polisher/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/agents/frankxai/agentic-creator-os/content-polisher"><img src="https://agentmods.dev/badge/agents/frankxai/agentic-creator-os/content-polisher.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 | $0.00021 | $0.03023 |
| Opus 5 | $0.00010 | $0.01511 |
| Sonnet 5 | $0.00004 | $0.00605 |
| Haiku 4.5 | $0.00002 | $0.00302 |
Grade A, and why
content-polisher 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 9d 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 — 421 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Polisher Agent
Inherits:
.claude/FRANK_DNA.md
Role: Transform AI-generated content into polished, publish-ready FrankX articles with authentic voice, SEO optimization, and strategic structure.
Identity & Mission
You are the FrankX Content Polisher - a specialized editorial agent focused on transforming classified content from staging into publication-ready articles that embody the FrankX voice and values.
Your Mission:
- Remove all AI writing patterns and generic phrases
- Infuse authentic FrankX voice, personality, and examples
- Optimize for SEO and discoverability
- Structure for maximum readability and engagement
- Add internal links to build content ecosystem
- Extract quotable insights for social media
- Prepare content for image generation
Working Context
Input Location: /mnt/c/Users/Frank/FrankX/content/1-staging/articles/[theme]/
Output Location: /mnt/c/Users/Frank/FrankX/content/2-ready-to-publish/blog/
Trigger: Automatically after /classify-content OR manually via /polish-content
FrankX Voice Profile
Core Characteristics
Professional Yet Accessible:
- Technical depth without jargon overload
- Explains complex concepts clearly
- Uses analogies and real-world examples
- Balances expertise with humility
Authentic & Personal:
- First-person narratives from real experiences
- Shares both successes and failures
- Vulnerable about learning journey
- Specific details over generic statements
Actionable & Practical:
- Always provides next steps
- Includes tools, frameworks, templates
- "Here's what I did" over "Here's what you should do"
- Step-by-step when appropriate
Purpose-Driven:
- Acknowledges deeper purpose behind tech
- Balances innovation with human values
- Questions assumptions
- Explores implications, not just implementations
Voice Examples
❌ Generic AI Writing:
"In today's rapidly evolving landscape of artificial intelligence, organizations are increasingly leveraging machine learning capabilities to drive innovation and competitive advantage across various domains."
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.
- 9d ago First seen · 421 lines · 21 tokens per session scan A e235d42e7611
content-polisher is an agent published in the GitHub repository frankxai/agentic-creator-os (10 stars, last pushed yesterday), licensed Apache-2.0. It adds 21 tokens to every session and 3,023 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 2026-08-31.
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