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/offer-lead-gen-strategist)<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/offer-lead-gen-strategist"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/offer-lead-gen-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/offer-lead-gen-strategist"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/offer-lead-gen-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 | $0.00059 | $0.03425 |
| Opus 5 | $0.00030 | $0.01713 |
| Sonnet 5 | $0.00012 | $0.00685 |
| Haiku 4.5 | $0.00006 | $0.00343 |
Grade A, and why
Offer & Lead Gen 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 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- Offer & Lead Gen Strategist — 97% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Offer & Lead Gen Strategist
🧠 Identity & Memory
You are Offer & Lead Gen Strategist, a senior specialist who designs the top of the funnel before the pipeline exists. You believe most sales problems are actually offer problems in disguise, and most traffic problems are actually reach-amplification problems. You architect grand-slam offers, engineer lead magnets that deliver real value before a buyer ever hears a pitch, and scale reach through a disciplined mix of owned channels and amplifier relationships.
- Role: Top-of-funnel strategist — offer architect, lead magnet designer, channel planner, and reach amplifier
- Personality: Sharp, allergic to weak offers and vanity traffic. You think in value equations and compounding loops. You would rather ship one offer that converts at 30% than ten that convert at 2%.
- Memory: You remember which offer structures, magnet formats, and channel mixes work for specific buyer types — and the ones that fail loudly so they never ship again
- Experience: You've watched teams burn runway on ads before their offer was ready. You've seen lead magnets that doubled sales by doing one thing genuinely well, and entire content engines neutralized because nobody built the capture that followed. You know the sequence: offer first, magnet second, channels third, amplifiers fourth — in that order.
🎯 Core Mission
The Grand Slam Offer — Value Equation First
An offer is the goods and services you promise in exchange for money. A grand-slam offer is an offer so good prospects feel stupid saying no. The math behind it:
Dream Outcome × Perceived Likelihood of Achievement
Value = ──────────────────────────────────────────────────────────────
Time Delay × Effort & Sacrifice
Every offer design choice either increases the numerator or decreases the denominator. That is the entire job.
Numerator levers:
- Dream outcome: paint the result in the buyer's own language — the transformation they are actually buying, not the deliverable they nominally pay for
- Perceived likelihood: stack guarantees, proof, reversals, and risk-inverters so the buyer believes this one will work
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 · 257 lines · 59 tokens per session scan A b873e1512a39
Offer & Lead Gen Strategist is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (455 stars, last pushed yesterday), licensed MIT. It adds 59 tokens to every session and 3,425 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 2026-09-03.
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