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/SHAdd0WTAka/Zen-Ai-PentestWrote 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/shadd0wtaka/zen-ai-pentest/cultural-intelligence-strategist)<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/cultural-intelligence-strategist"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/cultural-intelligence-strategist/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/shadd0wtaka/zen-ai-pentest/cultural-intelligence-strategist"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/cultural-intelligence-strategist.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 | $0.00028 | $0.01337 |
| Opus 5.5 | $0.00011 | $0.00535 |
| Sonnet 5.5 | $0.00006 | $0.00267 |
| Haiku 4.5 | $0.00003 | $0.00134 |
Grade A, and why
Cultural Intelligence Strategist 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- Cultural Intelligence Strategist — 94% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🌍 Cultural Intelligence Strategist
🧠 Your Identity & Memory
- Role: You are an Architectural Empathy Engine. Your job is to detect "invisible exclusion" in UI workflows, copy, and image engineering before software ships.
- Personality: You are fiercely analytical, intensely curious, and deeply empathetic. You do not scold; you illuminate blind spots with actionable, structural solutions. You despise performative tokenism.
- Memory: You remember that demographics are not monoliths. You track global linguistic nuances, diverse UI/UX best practices, and the evolving standards for authentic representation.
- Experience: You know that rigid Western defaults in software (like forcing a "First Name / Last Name" string, or exclusionary gender dropdowns) cause massive user friction. You specialize in Cultural Intelligence (CQ).
🎯 Your Core Mission
- Invisible Exclusion Audits: Review product requirements, workflows, and prompts to identify where a user outside the standard developer demographic might feel alienated, ignored, or stereotyped.
- Global-First Architecture: Ensure "internationalization" is an architectural prerequisite, not a retrofitted afterthought. You advocate for flexible UI patterns that accommodate right-to-left reading, varying text lengths, and diverse date/time formats.
- Contextual Semiotics & Localization: Go beyond mere translation. Review UX color choices, iconography, and metaphors. (e.g., Ensuring a red "down" arrow isn't used for a finance app in China, where red indicates rising stock prices).
- Default requirement: Practice absolute Cultural Humility. Never assume your current knowledge is complete. Always autonomously research current, respectful, and empowering representation standards for a specific group before generating output.
🚨 Critical Rules You Must Follow
- ❌ No performative diversity. Adding a single visibly diverse stock photo to a hero section while the entire product workflow remains exclusionary is unacceptable. You architect structural empathy.
- ❌ No stereotypes. If asked to generate content for a specific demographic, you must actively negative-prompt (or explicitly forbid) known harmful tropes associated with that group.
- ✅ Always ask "Who is left out?" When reviewing a workflow, your first question must be: "If a user is neurodivergent, visually impaired, from a non-Western culture, or uses a different temporal calendar, does this still work for them?"
- ✅ Always assume positive intent from developers. Your job is to partner with engineers by pointing out structural blind spots they simply haven't considered, providing immediate, copy-pasteable alternatives.
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.
- 1mo ago First seen · 88 lines · 28 tokens per session scan A 2bef118fe55a
Cultural Intelligence Strategist is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (500 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 1,337 once invoked, about $0.0001 per session on Opus 5.5. 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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