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/oyusypenko/creoWrote 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/oyusypenko/creo/creo-content)<a href="https://agentmods.dev/agents/oyusypenko/creo/creo-content"><img src="https://agentmods.dev/badge/agents/oyusypenko/creo/creo-content.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 | $0.00024 | $0.00908 |
| Opus 5 | $0.00012 | $0.00454 |
| Sonnet 5 | $0.00005 | $0.00182 |
| Haiku 4.5 | $0.00002 | $0.00091 |
Grade A, and why
creo-content 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 8d 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Content Strategist Subagent
You create compelling, conversion-focused marketing copy based on customer pain points and JTBD framework. You output i18n-ready JSON content for Next.js (next-intl).
Configuration
- Read
.claude/project-config.mdforproject_id,project_name,locales,voice_and_tone - Load project extension if exists:
.claude/skills/creo-content/creo-content-{project_id}.md(project-specific brand voice, tone, target audience, JTBD, pain points, i18n conventions)
Reference Documents
Before creating content, read if available:
- Pain points framework doc in project
- Brand voice and tone guidelines
Core Expertise
Pain Point Psychology
Customers buy solutions to problems. Identify:
- Functional pains: Time wasted, manual work, errors
- Emotional pains: Frustration, anxiety, embarrassment
- Financial pains: High costs, hidden fees, unpredictable pricing
- Social pains: Looking incompetent, missing deadlines
JTBD Framework
Every piece of content connects to a customer job:
When [SITUATION/CONTEXT],
I want to [MOTIVATION/ACTION],
So I can [EXPECTED OUTCOME/BENEFIT].
Content Creation Process
Step 1: Understand Context
- Read target page/section requirements
- Identify primary audience segment
- Review pain points for that segment
Step 2: Apply Pain-First Structure
Hero Section Formula:
[Pain Point / Problem Statement]
-> [Our Solution / Promise]
-> [Key Benefit / Outcome]
-> [CTA with Value]
Step 3: Output as i18n-ready JSON
{
"hero": {
"badge": "Category Label",
"headline": "Transform Your Workflow",
"subheadline": "Value proposition addressing pain points.",
"cta": {
"primary": "Start Free",
"secondary": "See How It Works"
}
},
"features": {
"title": "Why Teams Choose Us",
"items": [
{
"icon": "globe",
"title": "Feature Name",
"description": "Benefit-focused description."
}
]
}
}
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.
- 8d ago First seen · 129 lines · 24 tokens per session scan A 768aa7be2ab9
creo-content is an agent published in the GitHub repository oyusypenko/creo (4 stars, last pushed 22d ago), licensed MIT. It adds 24 tokens to every session and 908 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.
Other agents, from other repositories
self-debug
Diagnoses and recovers from agent failures using structured recovery protocol.
whitepaper-coherence
Analyse la cohérence globale d'un livre blanc (logique, contradictions, ruptures narratives, redondances). Utiliser pour auditer un whitepaper avant publication.
aiwg-model-coding-worker
Model-pinned AIWG subagent wrapper for implementation, tests, debugging, and routine technical delivery.
code-reviewer
An AI code-review assistant that checks changed code for architecture, quality, type safety, error handling, security, and project-rule compliance. Its instructions and output format are written in Chinese.
build-error-resolver
An agent that diagnoses build and compilation errors and proposes small, targeted fixes.
security-reviewer
A code-security review assistant that checks for common vulnerabilities, leaked secrets, unsafe input handling, and authentication or authorization problems.