scratch-scanner-rs

Write-then-verify documentation pipeline. Use when a user asks to improve comments or docs, explain algorithms or design choices, write or upgrade docstrings, or raise documentation quality for a codebase (especially Rust crates). Writes docs, then automatically verifies every claim against code reality using a fresh agent to eliminate confirmation bias.

Use when you have code review findings, PR comments, or review reports that need to be systematically addressed — especially when there are multiple findings across different files and severities

Use when creating any beads task — auto-researches the codebase, links related tasks, and produces a rich self-contained description from a structured template. Accepts minimal intent and outputs a complete task ready for agent implementation.

Use when you have code review findings, PR comments, or review reports that need to be systematically addressed — especially when there are multiple findings across different files and severities

Use when a task needs an implementation plan that is iteratively created and stress-tested through review-and-revise cycles before implementation begins — catches blind spots, incorrect codebase assumptions, unnecessary complexity, and performance pitfalls while changes are still cheap

Use when a markdown plan file exists and needs validation before implementation — catches design flaws, logic holes, footguns, unnecessary complexity, and performance concerns while changes are still cheap

Use when a task needs an implementation plan that is iteratively created and stress-tested through review-and-revise cycles before implementation begins — catches blind spots, incorrect codebase assumptions, unnecessary complexity, and performance pitfalls while changes are still cheap

Consolidate verbose test suites by replacing repetitive unit tests with property-based tests, parameterized tests (rstest), or fuzz tests. Less code to maintain, same or better coverage.

Write-then-verify documentation pipeline — a doc-rigor agent writes/improves docs, then a separate fresh doc-verify agent checks accuracy against code reality with zero confirmation bias

Verify documentation accuracy against code reality and external claims — runs as a fresh agent after /doc-rigor to prevent confirmation bias

Run Jepsen-style cluster tests using Maelstrom (lightweight) or full Jepsen (heavyweight) — validates correctness of the deployed gossip-rs system with real network behavior, complementing in-process DST

Simulation-testability code review — enforces DST-compatible patterns in coordination, gossip, and pipeline code based on FoundationDB, TigerBeetle, sled, and Firezone evidence

Run deterministic simulation tests with progressive difficulty levels (sunny/stormy/radioactive) inspired by TigerBeetle VOPR — orchestrates seed management, workload selection, and invariant verification

Scaffold simulation-testable modules with sans-IO pattern, proptest state machine tests, and fault injection points — prevents retrofitting costs by making code DST-ready from the start

SIMD vectorization for Rust — detects ISA features, identifies vectorizable patterns, generates platform-specific intrinsics (ARM NEON/SVE, x86 SSE/AVX/AVX-512), validates correctness and performance. Uses tiered research with baked-in references and /deep-research fallback.

Comprehensive review of unsafe code — audits safety invariants, demands benchmark+ASM proof of performance benefit, and verifies Miri/Kani/fuzz/property test coverage for every unsafe block

Verify documentation accuracy against code reality and external claims — runs as a fresh agent after /doc-rigor to prevent confirmation bias

Comprehensive 6-phase research funnel — 8-10 parallel survey agents sweep wide, a synthesizer compiles evidence, deep-dive and adversarial agents run in parallel to elaborate and challenge findings, a final synthesizer reconciles everything, and an integrator maps verified findings to a concrete codebase plan with full traceability

Distributed systems design and implementation auditor — enforces evidence-backed coordination decisions, citation requirements, invariant tracking, and correctness verification against academic literature, battle-tested systems, and the project's locked architectural decisions

Run Jepsen-style cluster tests using Maelstrom (lightweight) or full Jepsen (heavyweight) — validates correctness of the deployed gossip-rs system with real network behavior, complementing in-process DST

Simulation-testability code review — enforces DST-compatible patterns in coordination, gossip, and pipeline code based on FoundationDB, TigerBeetle, sled, and Firezone evidence

Run deterministic simulation tests with progressive difficulty levels (sunny/stormy/radioactive) inspired by TigerBeetle VOPR — orchestrates seed management, workload selection, and invariant verification

Scaffold simulation-testable modules with sans-IO pattern, proptest state machine tests, and fault injection points — prevents retrofitting costs by making code DST-ready from the start

Assess and recommend the appropriate testing strategy for Rust code - unit tests, parameterized tests (rstest), property-based tests, fuzz tests, Kani model checking, or simulation testing

SIMD vectorization for Rust — detects ISA features, identifies vectorizable patterns, generates platform-specific intrinsics (ARM NEON/SVE, x86 SSE/AVX/AVX-512), validates correctness and performance. Uses tiered research with baked-in references and /deep-research fallback.

Comprehensive review of unsafe code — audits safety invariants, demands benchmark+ASM proof of performance benefit, and verifies Miri/Kani/fuzz/property test coverage for every unsafe block

ASM-guided deep performance optimization. Collects assembly, audits codegen quality, applies targeted transforms, validates with benchmarks. Uses cargo-show-asm + Criterion as ground truth.

ASM-guided deep performance optimization. Collects assembly, audits codegen quality, applies targeted transforms, validates with benchmarks. Uses cargo-show-asm + Criterion as ground truth.

Respond to PR review comments by verifying bug reports with failing tests before fixing code — never blindly trust a reviewer

Use when the user wants a minimal source-only archive for upload or checkpoint. Creates a tar.gz with just src/ and tests/ directories.

Run Criterion benchmarks with baseline comparison for performance optimization work

Deep research before design — 3-5 parallel research agents survey papers, production systems, failure modes, and prior art, then a synthesizer compiles evidence, and an integrator maps findings to a concrete codebase plan with citations

Run a parallel diverge-then-converge design tournament — 3-5 independent agents explore a problem, then 2 ranking agents evaluate and stack-rank the results with confidence scores

Review Rust interfaces for ease of correct use and resistance to misuse, applying "make interfaces easy to use correctly and hard to use incorrectly"

Deep Linux perf profiling — PMU counters, topdown analysis, flamegraphs, and annotated hotspot drill-down on ARM/Graviton

Performance regression testing workflow for hot path changes

Analyze Rust code for performance issues, allocation hot spots, and optimization opportunities

Parallel specialist code review — 6 focused agents (correctness, design, performance, safety, docs, complexity) diverge independently, then a single ranker merges findings into an importance-ranked report with confidence scores

Workflow for modifying and benchmarking detection rules

Run cargo-fuzz targets with proper nightly toolchain and options