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 rules/duckduckgo/apple-browsers/abn-experiment-frameworkgit clone --depth 1 https://github.com/duckduckgo/apple-browsersWhat 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 | $0.00000 | $0.03627 |
| Opus 5 | $0.00000 | $0.01813 |
| Sonnet 5 | $0.00000 | $0.00725 |
| Haiku 4.5 | $0.00000 | $0.00363 |
Grade A, and why
abn-experiment-framework 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 today.
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 — 602 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A/B/N Experiment Framework
Overview
The DuckDuckGo browser includes a comprehensive A/B/N experiment framework that enables data-driven feature testing across iOS and macOS platforms. This framework allows you to safely experiment with new ideas while maintaining control groups and measuring impact.
Reference: Video of knowledge sharing session: ✓ A/B/N Experiment Framework
What is A/B/N Testing?
An A/B/N test is a method of experimenting with multiple variants of a feature (A, B, ... N) to determine which performs better. It's like traditional A/B testing but scaled up to support more than two groups.
Use Cases
You can use this framework to explore:
- UI/UX variations: Whether blue buttons outperform green buttons
- Content experiments: If showing pictures of cats 🐱 or dogs 🐶 boosts user retention
- Feature comparisons: Different implementations of the same functionality
- Performance optimization: Testing various algorithms or approaches
When to Use A/B/N Testing
✅ Use for:
- Comparing user behavior between two or more feature variants
- Validating hypotheses before rolling out changes to all users
- Safely experimenting with new ideas while maintaining control groups
- Measurable, impactful decisions with clear success metrics
❌ Don't use for:
- Simple bug fixes or obvious improvements
- Changes without measurable impact
- Features that can't be easily reversed
⚠️ Note: Not every change needs a test—reserve it for measurable, impactful decisions. This is typically decided in collaboration with ODRIs and Data Science.
Framework Architecture
Remote Configuration System
A/B/N experiments are supported via remote configuration on both macOS and iOS:
- Sub-features are used for experiments
- Parent features group related experiments
- Cohorts define the different variants
- Weights control user distribution
- Targets allow locale-based segmentation
Configuration Setup
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.
- today First seen · 602 lines · 0 tokens per session scan A b838c3b03fba
abn-experiment-framework is a cursor rule published in the GitHub repository duckduckgo/apple-browsers (252 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 3,627 tokens. 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 2026-09-01.
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