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/thatrebeccarae/claude-marketingWrote 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/rules/thatrebeccarae/claude-marketing/braze)<a href="https://agentmods.dev/rules/thatrebeccarae/claude-marketing/braze"><img src="https://agentmods.dev/badge/rules/thatrebeccarae/claude-marketing/braze.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 | $0.00053 | $0.03590 |
| Opus 5 | $0.00026 | $0.01795 |
| Sonnet 5 | $0.00011 | $0.00718 |
| Haiku 4.5 | $0.00005 | $0.00359 |
Grade A, and why
braze 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 — 409 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Braze Customer Engagement Platform
Expert-level guidance for Braze — auditing, building, and optimizing Canvases, campaigns, segments, data architecture, and cross-channel messaging.
Core Capabilities
Canvas Auditing & Design
- Audit existing Canvases for logic errors, timing issues, and missed opportunities
- Design multi-step, multi-channel Canvases (email, push, SMS, in-app, Content Cards, webhook)
- Implement Canvas Flow features: Action Paths, Audience Paths, Experiment Paths, Decision Splits
- Review entry schedules, exception events, re-eligibility, and rate limiting
Segmentation & Targeting
- Build segments using Braze's filter system (user attributes, custom events, purchase behavior, engagement)
- Design segment extensions for complex queries (event property filters, nested AND/OR logic)
- Implement predictive audiences (Predictive Churn, Predictive Purchases)
- Connected Audience sync from external CDPs (Segment, mParticle, Amplitude)
Campaign Strategy
- Plan cross-channel campaigns: email, push, SMS, in-app messages, Content Cards, webhooks
- A/B and multivariate testing with Intelligent Selection
- Personalization with Liquid templating, Connected Content, and Catalogs
- Frequency capping and Intelligent Timing optimization
Data Architecture
- Design custom event and attribute schemas
- Implement Currents data export (to Snowflake, BigQuery, S3, Mixpanel)
- Plan data migration from other platforms (Klaviyo, Iterable, Salesforce MC)
- API integration patterns (REST API, SDK implementation)
Deliverability & Compliance
- Email: SPF, DKIM, DMARC, IP warming schedules
- Push: Token management, provisional authorization, opt-in strategies
- SMS: Short code vs long code, compliance (TCPA, CTIA), opt-in management
- GDPR/CCPA data handling and consent management
Key Benchmarks
| Metric | Good | Great | Warning |
|---|---|---|---|
| Email Open Rate | 20-25% | 30%+ | <15% |
| Email Click Rate | 2-3% | 4%+ | <1.5% |
| Push Open Rate (iOS) | 3-5% | 7%+ | <2% |
| Push Open Rate (Android) | 5-8% | 12%+ | <3% |
| In-App Click Rate | 15-20% | 25%+ | <10% |
| Content Card Click Rate | 10-15% | 20%+ | <5% |
| SMS Click Rate | 8-12% | 15%+ | <5% |
| Unsubscribe Rate (email) | <0.3% | <0.1% | >0.5% |
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 · 409 lines · 53 tokens per session scan A 013fed5e5abb
braze is a cursor rule published in the GitHub repository thatrebeccarae/claude-marketing (132 stars, last pushed 3mo ago), licensed MIT. It adds 53 tokens to every session and 3,590 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 2026-08-30.
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