Which tools does this skill interact with?

It integrates with Rust's cargo toolchain, including cargo test, cargo bench, and custom release builds optimized for native CPU architectures.

What are anchors in the context of this skill?

Anchors refer to structured prefixes like 'sgp_' or 'AKIA' that help the scanner quickly identify potential matches without scanning every character in a file.

What kind of rules does this skill help optimize?

It is specifically designed for secret detection rules used to identify API keys, credentials, and sensitive tokens within large source code repositories.

Does this skill help with regex backtracking?

Yes, it provides specific pattern guidelines to avoid greedy quantifiers and common pitfalls that lead to slow scanning performance.

How does it handle performance regressions?

The skill provides a workflow to calculate the percentage change in throughput, categorizing regressions under 2% as acceptable and blocking those over 5% without justification.

Secret Detection Rule Optimizer

Name: Secret Detection Rule Optimizer
Author: ahrav

byahrav

•

Security & Testing

Standardizes the modification and performance benchmarking of secret detection rules to ensure high-speed, accurate scanning.

This skill provides a rigorous workflow for developers maintaining pattern-matching engines and secret scanners. It guides the user through modifying detection rules, performing release-build benchmarks against massive repositories, and verifying that performance regressions stay within strict thresholds. By enforcing regex best practices—such as utilizing structured anchors, avoiding backtracking, and preferring character classes over alternation—this skill ensures that detection logic remains both performant and reliable during security audits.

Key Features

01Validation protocols for high-entropy secrets and checksums

022 GitHub stars

03Regression tracking with automated median throughput comparison

04Comprehensive benchmarking workflow against real-world datasets

05Rule isolation testing via Criterion benchmarks

06Regex optimization guidelines for anchors and character classes

Use Cases

01Identifying and fixing catastrophic backtracking in complex pattern matching

02Benchmarking scanner throughput after adding new regex rules for API keys

03Optimizing sensitive data detection patterns to prevent performance bottlenecks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ahrav/scratch-scanner-rs rule-optimize

For use in Claude.ai and ChatGPT

Download Skill