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rule-optimize

Testing & Quality
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Workflow for modifying and benchmarking detection rules

QUICK START

How to use this skill

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  1. Open your project in Codex.
  2. Copy the prompt below and paste it into your agent.
  3. Review the proposed files and risks before you approve installation.
Prompt to paste
I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/performance/rule-optimize-ahrav-gossip-rs/SKILL.md

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First, summarize what it does, its dependencies, license status if identifiable, and any risks. Show the exact files you propose to add under .agents/skills/rule-optimize/. Do not write files or run scripts until I approve.

After I approve, install the complete skill folder, including required referenced files, into that project location. Verify it is discoverable, then tell me its actual invocation name and how to use it. Do not claim it is installed until you have verified it.

Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

Rule Optimization Workflow

Use after modifying rules in default_rules.yaml (loaded by src/rules/).

Checklist

  1. Run cargo test to verify no regressions
  2. Build release: RUSTFLAGS="-C target-cpu=native" cargo build --release
  3. Benchmark against test repos: 
    ./target/release/scanner-rs ../linux ../gitleaks ../tigerbeetle ../trufflehog
  4. Compare throughput/findings against baseline
  5. Document anchor/keyword choice if non-obvious (add inline comment)

Pattern Guidelines

When adding or modifying rules:

Anchors

  • Prefer structured prefixes (sgp_, hvs., AKIA) over service name keywords
  • Avoid generic patterns like [a-fA-F0-9]{40} that match git SHAs
  • Add inline comments explaining non-obvious anchor/keyword choices

Performance

  • Test rule isolation: cargo bench --bench rule_isolation -- <rule_id>
  • Check for backtracking: avoid .* followed by greedy quantifiers
  • Prefer character classes over alternation when possible

Validation

  • Ensure validators don't make network calls in hot paths
  • Use entropy checks for high-entropy secrets
  • Add checksum validation where applicable (AWS keys, etc.)

Baseline Comparison

Before making changes, capture baseline:

# Run 3x and record median throughput
for i in 1 2 3; do
  ./target/release/scanner-rs ../linux 2>&1 | tail -1
done

After changes, compare:

# Calculate % change
# Acceptable: <2% regression
# Investigate: 2-5% regression
# Block: >5% regression without justification

Related Skills

  • bench-compare - Criterion benchmark comparison
  • perf-regression - Full performance regression workflow
  • test-strategy - Choose testing approach for rule changes