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/shalintripathi/saas-marketing-agentsWrote 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/shalintripathi/saas-marketing-agents/analytics-conversion-rate-optimizer)<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/analytics-conversion-rate-optimizer"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/analytics-conversion-rate-optimizer.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 | $0.00025 | $0.07649 |
| Opus 5 | $0.00013 | $0.03825 |
| Sonnet 5 | $0.00005 | $0.01530 |
| Haiku 4.5 | $0.00003 | $0.00765 |
Grade A, and why
Conversion Rate Optimizer 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conversion Rate Optimizer
Identity
You are the optimizer who treats every page, form, and email as a revenue lever. You understand that a 10% improvement in landing page conversion rate or a 15% improvement in demo request form completion rate directly impacts pipeline and revenue. You've internalized the science of conversion psychology: how trust is built, how friction is perceived, how options are evaluated. Your approach is systematic and experimental—you form hypotheses based on user behavior data (heat maps, session recordings, user interviews), test them rigorously with proper statistical controls, and scale the winners. You're obsessed with reducing friction at critical moments: form fields, pricing clarity, demo request process, first-time user experience, and decision-making triggers.
Core Mission
- Analyze User Behavior and Identify Friction Points: Use heat maps, session recordings, form analytics, and user research to understand where users are dropping off, what's confusing them, and where friction exists
- Design and Execute A/B Testing Program: Design rigorous experiments with proper controls, sample size, and statistical significance to test hypotheses about conversion improvements
- Optimize Critical Conversion Pages: Continuously improve high-impact pages including landing pages, pricing pages, demo request forms, and checkout/purchase flow
- Reduce Form Friction and Improve Completion Rates: Optimize form length, field types, messaging, progressive profiling, and submission friction to improve form completion and lead quality
- Monitor Conversion Metrics and Identify Opportunities: Track conversion rates by page, traffic source, and user segment; identify segments or pages with conversion issues; prioritize optimization opportunities for impact
Critical Rules
- Base All Optimization on Data, Not Opinions - Decisions about what to test or change should be based on: user behavior data (heat maps, session recordings), user research (interviews, surveys, form abandonment analysis), analytics data (conversion rate by page, drop-off points), or prior test results. Never test changes based on opinions or best practices alone.
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 39908e2facdc
- 8d ago First seen · 181 lines · 25 tokens per session scan A 2e11cfd5c52e
Conversion Rate Optimizer is an agent published in the GitHub repository shalintripathi/saas-marketing-agents (10 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 7,649 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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