测试与安全技能

Squidpy spatial statistics on annotated spatial transcriptomics: build the spatial graph (Visium grid, kNN, radius, Delaunay), neighbourhood enrichment z-scores, distance-resolved co-occurrence, interaction matrix and centrality scores, Ripley's L/F/G point patterns, spatially variable genes by Moran's I / Geary's C, and permutation ligand-receptor tests (ligrec, OmniPath). Works on Visium spots and single-cell-resolution data (Xenium, MERFISH, CosMx, Slide-seq). Needs cluster or cell type labels for all but the spatially variable gene step. For an end-to-end ligand-receptor workflow use spatial-transcriptomics-cell-cell-communication.

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PowerX Nuxt Vitest/E2E 测试规范。

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PowerX 底座 Capability 治理与发布准入规则。用于审计 REST/OpenAPI/gRPC/Gin 生成的能力候选、正式 platform_capabilities 目录、Capability Registry 登记、agent_usable/permission_code/risk_level 元数据、ignore 清单和缺失能力；当用户要求“重新识别能力”“能力是否能发布”“补齐能力登记”“检查 capability-gen/audit/check”“底座接口暴露给插件/agent”时使用。

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PowerX CRUD 测试规则（Service 必测、Repo 可选集测）。

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Bulk RNA-seq DE with PyDESeq2: load counts, normalize, fit negative binomial models, Wald test (BH-FDR), LFC shrinkage, volcano/MA plots. Use for two-group comparisons, multi-factor designs with batch correction, multiple contrasts.

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Bulk RNA-seq DE with R/Bioconductor DESeq2. Negative binomial GLM, empirical Bayes shrinkage, Wald/LRT tests, multi-factor designs, Salmon tximeta import, apeglm LFC shrinkage, MA/volcano/heatmap viz. R gold standard. Use pydeseq2-differential-expression for Python; use edgeR for TMM normalization.

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Filter degenerate, uninformative inputs before statistical tests: single-sequence alignments, empty files, constant features, zero-variance inputs, all-NaN columns. See nan-safe-correlation for NaN-aware correlation; statistical-analysis for test guidance.

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Universal QA checklist for generated scientific plots: overlapping labels, clipped text, missing axes/legends, overcrowded data, and cross-journal resolution/format guidance.

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Structured hypothesis formulation: turn observations into testable hypotheses with predictions, propose mechanisms, design experiments. Follows the scientific method. Use scientific-brainstorming for open ideation; hypogenic for automated LLM hypothesis testing on datasets.

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HuggingFace Transformers with biomedical LMs (BioBERT, PubMedBERT, BioGPT, BioMedLM) for scientific NLP: NER (genes, diseases, chemicals), relation extraction, QA, text classification, abstract summarization. Covers loading, biomedical tokenization, inference pipelines, fine-tuning. Alternatives: spaCy en_core_sci_lg (rule-based NER), Stanza (biomedical models), NLTK.

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Model interpretability via SHAP (Shapley values from game theory). Covers explainer choice (Tree, Deep, Linear, Kernel, Gradient, Permutation), feature attribution, and plots (waterfall, beeswarm, bar, scatter, force, heatmap). Use to explain ML predictions, rank features, debug models, audit fairness, or compare models. Works with tree, deep, linear, and black-box models.

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Per-feature NaN-safe Spearman/Pearson correlation across many features (genes, proteins, variants) with missing values. Covers why bulk matrix shortcuts fail, correct pairwise deletion, degenerate input filtering, and large-dataset performance. Use statistical-analysis for test choice; shap-model-explainability for interpretability.

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LLM-driven hypothesis generation/testing on tabular data. Three methods: HypoGeniC (data-driven), HypoRefine (literature+data), Union. Iterative refinement, Redis caching, multi-hypothesis inference. Manual: hypothesis-generation; ideation: scientific-brainstorming.

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MaxQuant + Perseus proteomics pipeline: run MaxQuant for LFQ and SILAC; parse proteinGroups.txt in Python; filter contaminants/decoys; log2 + median-normalize; impute MNAR; t-test with FDR; volcano plot; GO/pathway enrichment. Use Proteome Discoverer for Thermo-native processing; FragPipe/MSFragger for GPU-accelerated DB search.

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Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows

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Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.

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15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.

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Complete security architecture overhaul for claude-flow v3. Addresses critical CVEs (CVE-1, CVE-2, CVE-3) and implements secure-by-default patterns. Use for security-first v3 implementation.

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QA engineering workflows on top of Playwright. Use when a QA engineer asks to design test cases from a ticket, PRD or acceptance criteria, decide what to automate, write a bug report from a failing test or trace, convert manual test cases (TestRail, Xray, CSV) into Playwright specs with case-ID traceability, or review Playwright test code and pull requests.

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For frontend engineers authoring UI — how to make components reliably locatable by tests and AI agents. Covers the official Playwright locator priority, semantic/accessible markup first, and how to add valid, unique, stable `data-testid` attributes (naming convention, uniqueness in lists, stability rules) for React, Vue, Angular, and Svelte. Use when writing or reviewing components, or when an agent needs durable locators.

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Security guidance and vulnerability review for codebases, APIs, services, CLI tools, libraries, and daemons. Use for security questions, focused reviews, vulnerability research, security audits, or pen tests. Run the complete workflow only for explicit codebase audit or pen-test requests, full/comprehensive/end-to-end reviews, or requested report artifacts.

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Write, review, filter, mock, and debug Core unit tests with the repository's installed Vitest 5 configuration. Use for tests under Core's Vitest include paths, `vi.mock`/spies/timers, jsdom component tests, coverage output, focused reruns, or unit-test failures. Do not use for browser E2E flows or async Next.js Server Components.

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Battle-tested Playwright patterns for writing and debugging reliable E2E, API, component, visual, accessibility, and security tests. Use when you need locator strategy, assertions, fixtures, network mocking, auth flows, trace debugging, or framework recipes for React, Next.js, Vue, and Angular. TypeScript and JavaScript.

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Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

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