Testing & Debugging for Claude Code

Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.

Comprehensive quality control for flow cytometry and CyTOF data. Covers flow rate stability, signal drift, margin events, dead cell exclusion, and batch QC. Use when assessing acquisition quality or identifying problematic samples before analysis.

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Quality control and normalization for metabolomics data. Covers QC-based correction, batch effect removal, and data transformation methods. Use when correcting technical variation in metabolomics data before statistical analysis.

Detect sample contamination and cross-species reads using FastQ Screen. Screen reads against multiple reference genomes to identify bacterial, viral, adapter, or sample swap contamination. Use when suspecting cross-contamination or working with samples prone to microbial contamination.

All-in-one read preprocessing with fastp including adapter trimming, quality filtering, deduplication, base correction, and HTML report generation. Use when preprocessing Illumina data and wanting a single fast tool instead of separate Cutadapt, Trimmomatic, and FastQC steps.

Filter reads by quality scores, length, and N content using Trimmomatic and fastp. Apply sliding window trimming, remove low-quality bases from read ends, and discard reads below thresholds. Use when reads have poor quality tails or require minimum quality for downstream analysis.

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Spatial and temporal convergence analysis with Richardson extrapolation and Grid Convergence Index (GCI) for solution verification

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Select and configure linear solvers for systems Ax=b in dense and sparse problems. Use when choosing direct vs iterative methods, diagnosing convergence issues, estimating conditioning, selecting preconditioners, or debugging stagnation in GMRES/CG/BiCGSTAB.

Analyze and enforce numerical stability for time-dependent PDE simulations. Use when selecting time steps, choosing explicit/implicit schemes, diagnosing numerical blow-up, checking CFL/Fourier criteria, von Neumann analysis, matrix conditioning, or detecting stiffness in advection/diffusion/reaction problems.

> Validate material sample annotations and data structures against ontology constraints. Use when checking if CMSO annotations are correct, verifying that required properties are present, or validating that object property relationships have consistent domain and range. Catches unknown classes, unknown properties, domain mismatches, and missing required fields.

Extract, analyze, and visualize simulation output data. Use for field extraction, time series analysis, line profiles, statistical summaries, derived quantity computation, result comparison to references, and automated report generation from simulation results.

Export any bioinformatics analysis as a reproducible bundle with Conda environment, Singularity container definition, and Nextflow pipeline.

Validate simulations before, during, and after execution. Use for pre-flight checks, runtime monitoring, post-run validation, diagnosing failed simulations, checking convergence, detecting NaN/Inf, or verifying mass/energy conservation.

Generate SLURM `sbatch` job scripts and sanity-check HPC resource requests (nodes, tasks, CPUs, memory, GPUs) for simulation runs. Use when preparing submission scripts, deciding MPI vs MPI+OpenMP layouts, standardizing `#SBATCH` directives, or debugging job launch configuration (`sbatch`/`srun`).

AI Agent Skills for production-ready Go projects. 40+ atomic, cross-referencing Go skills covering code quality, architecture, concurrency, testing, performance, and tooling. Maintained externally by samber.

> Scan for accessibility issues with WCAG 2.1/2.2 compliance and screen reader...

Test your multi-agent system with a sample task, showing agent handoffs,...

Trigger full repository health analysis

Analyze code coverage metrics and identify untested code

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Analyze network latency and request patterns

Analyze logs for performance insights

Detect data quality issues, stubs, orphan plugins, duplicate files, and score outliers in the freshie inventory SQLite database using a structured six-check sweep. Use when auditing inventory health after a discovery run or investigating anomalous compliance grades. Trigger with \"scan for anomalies\", \"detect inventory issues\".

Detects traffic spikes, drops, bot activity, and tracking gaps in Umami analytics data, then classifies each anomaly by severity and root-cause hypothesis. Use when investigating unexpected traffic changes or data quality issues. Trigger with \"check for anomalies\", \"why did traffic drop\".

Diagnoses REST API failures by comparing HTTP logs against OpenAPI specs, identifies root cause by status code category, and generates working cURL repro commands. Use when an API call returns unexpected errors or status codes. Trigger with "why is my API failing", "debug this API error".

Use when reviewing HTTP/RPC/GraphQL endpoints, request/response contracts, input validation, or error semantics — verifies the API surface against the api persona standards.

Comprehensive security audit for REST and GraphQL APIs

Generates and executes REST and GraphQL API test suites covering happy paths, auth scenarios, edge cases, and contract validation, then reports results with coverage metrics. Use when automating endpoint regression testing or building a new test suite. Trigger with "test this API", "generate API tests".

Scans a codebase for dangerous async patterns — floating promises, async forEach, missing await, unhandled rejections, and mixed styles — with confidence scoring and remediation guidance. Never auto-applies fixes. Use when auditing Node.js or TypeScript code for async safety issues. Trigger with "find async issues", "scan for floating promises".

Implement database audit logging

Find Databricks queries paying the Photon DBU premium while silently falling back to the Spark engine, and surface the plan seam + UDF-rewrite fix.

Use this agent for bd/Dolt incident response — a dolt-server that won't start or has orphaned, server sprawl, suspected lost writes after rapid bd updates, JSONL that lags the database, or migrating a workspace between embedded and server mode. It knows the rapid-write race is already fixed in bd 1.0.4 and that residual lag is only the JSONL export throttle.

Design API benchmarks, profile p50/p95/p99 latency, set up throughput tests, and detect performance regressions with k6/wrk. Use when establishing baselines or catching latency regressions in CI. Trigger with "benchmark this API", "set up a performance test".

Cross-browser testing across browsers, devices, and cloud providers

Parse, classify, redact PII, score reliability, and cluster bug candidates by family and signal layers. Use when processing raw X/Twitter posts into structured bug clusters.

Designs controlled failure experiments to expose resilience gaps before production incidents do. Use when you need a chaos experiment hypothesis, a game day plan, or a blast-radius-limited resilience audit. Trigger with \"design a chaos experiment\", \"plan a game day\".

Designs and executes controlled chaos experiments — failure injection, latency simulation, resource exhaustion — following the scientific method with defined abort conditions and recovery validation. Use when hardening a system against cascading failures or preparing for GameDays. Trigger with "design chaos experiment", "test system resilience".