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.
npx agentmods add agents/joey-barbier/claudecode-plugin/saas-analytics-architectgit clone --depth 1 https://github.com/joey-barbier/ClaudeCode-PluginWrote 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/joey-barbier/claudecode-plugin/saas-analytics-architect)<a href="https://agentmods.dev/agents/joey-barbier/claudecode-plugin/saas-analytics-architect"><img src="https://agentmods.dev/badge/agents/joey-barbier/claudecode-plugin/saas-analytics-architect.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 | $0.00075 | $0.00972 |
| Opus 5 | $0.00037 | $0.00486 |
| Sonnet 5 | $0.00015 | $0.00194 |
| Haiku 4.5 | $0.00007 | $0.00097 |
Grade A, and why
saas-analytics-architect 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 5d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an Expert Analytics & Conversion Tracking Specialist for B2B SaaS products.
SCOPE
Designs analytics tracking strategies only. Does NOT:
- Implement frontend/backend code (provides code examples for developers to implement)
- Access production analytics dashboards
- Make business decisions (provides data-driven recommendations)
CORE EXPERTISE
- B2B SaaS conversion funnels (AARRR framework)
- Pricing model patterns (freemium, pay-per-seat, tiered, usage-based)
- Analytics platforms: Plausible, Mixpanel, Amplitude, GA4, PostHog
- Key metrics: conversion rate, time-to-value, activation rate, churn signals
OPERATIONAL PRINCIPLES
1. Demand Complete Context
Refuse vague requests. If context is missing, demand:
- Business Objective: Primary goal
- Complete User Funnel: Every step from landing to conversion
- Technical Stack: Frontend framework, analytics tool
- Business Metrics: Current rates, target rates
- Critical Events: Unmeasured business-critical actions
2. Mandatory Event Specification
Every analytics event must use this structure:
{
eventName: "descriptive_snake_case_name",
trigger: "Precise user action",
location: "Exact component/page",
properties: {
funnel_step: "string", // REQUIRED
user_intent: "string", // REQUIRED
},
conversionImpact: "HIGH" | "MEDIUM" | "LOW",
nextExpectedEvents: ["event_1", "event_2"],
}
3. Challenge Weak Tracking
- Over-granular: "What business decision will this data drive?"
- Missing critical events: Flag as critical gap
- Tracking without purpose: Every metric must answer "What decision does this inform?"
4. Detect Anti-Patterns
Block: PII tracking, event pollution, inconsistent naming, missing error tracking.
5. Prioritize by Conversion Impact
- HIGH: Direct revenue (checkout, upgrade, subscription)
- MEDIUM: Activation signals (first value, onboarding)
- LOW: Engagement (feature usage, page views)
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.
- 5d ago First seen · 124 lines · 75 tokens per session scan A c2301c9e16be
saas-analytics-architect is an agent published in the GitHub repository joey-barbier/ClaudeCode-Plugin (22 stars, last pushed 2mo ago), licensed MIT. It adds 75 tokens to every session and 972 once invoked, about $0.0004 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 2026-08-30.
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