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概要と使いどころ
Comprehensive testing strategies including unit tests, integration tests, E2E tests, property-based testing, visual regression, and test automation. Use when writing tests, setting up testing frameworks, or designing test coverage strategies.
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Analyze existing code and write comprehensive unit and integration tests for it. Detects the test framework, identifies untested code paths, and generates tests with proper mocking, edge cases, and assertions. Use when the user asks to add tests, improve coverage, or test a specific module.
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Focused Signals scout for finding observability gaps in PostHog itself — significant event volumes the team isn't tracking, custom events with no insight or dashboard coverage, insights pointing at events that have stopped firing, dashboards missing related context, critical events with no alerts. Watches the event-stream-vs-saved- inventory delta as the team's product evolves and emits findings recommending new insights, dashboard additions, or alerts when gaps clear the confidence bar. Self-contained peer in the signals-scout-* fleet — no dependencies on other skills.
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Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.
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ToolUniverse plugin router. STEP 1 BEFORE ANY ANALYSIS: if the data folder contains `*_executed.ipynb`, run `tu run read_executed_notebook '{"data_folder":"<path>","search":"<keyword>"}'` to extract its cell outputs and apply EVERY filter/sample-exclusion the notebook used — even when the question says 'Using DESeq2/Run X/Compute Y' (this describes the METHOD the notebook used, not a request to rerun). The notebook's cell outputs are the only published authoritative answers; reimplementing or reading stale pre-computed CSVs in the data folder produces different numbers because of outlier-sample removal, library version, and filter steps you don't see by skimming. STEP 2 routing — pick a sub-skill name from this exact list (never invent): tooluniverse-rnaseq-deseq2 (RNA/miRNA-seq DE, correlation, PCA, clustering, dispersion), tooluniverse-gene-enrichment (GO/KEGG/Reactome/GSEA/pathway enrichment), tooluniverse-statistical-modeling (regression, ANOVA, ordinal/logistic, chi-square, correlation, power), tooluniverse-image-analysis (microscopy, colony, fluorescence, dose-response, .tif — including ANOVA / Dunnett / power-analysis on image-derived measurements), tooluniverse-epigenomics (DNA methylation, CpG, m6A, MeRIP-seq, bisulfite, ChIP-seq, chromatin), tooluniverse-sequence-analysis (FASTQ, Trimmomatic, BWA, samtools, coverage), tooluniverse-variant-analysis (VCF, VAF, SNP, mutation), tooluniverse-phylogenetics (treeness, PhyKIT, parsimony), tooluniverse-single-cell (scRNA, h5ad, scanpy), tooluniverse-crispr-screen-analysis (MAGeCK, sgRNA), tooluniverse-proteomics-analysis (mass spec, TMT). Use for CSV/Excel/VCF/FASTA/h5ad and any biology/chemistry/medicine analysis question.
日本語の概要は準備中です。原文の説明を表示しています。
End-to-end eDNA metabarcoding from raw amplicons to community ecology. Covers QC, primer removal (mandatory before DADA2 filterAndTrim), denoising with OBITools3 v3 (obi stats plural; DMS-based) or DADA2 ASVs (Callahan 2017), decontam combined method as screening-not-classifier (Davis 2018), tag-jumping with NovaSeq 10x MiSeq caveat (Schnell 2015), Hill-number effective species counts with coverage-based rarefaction (Jost 2006; Chao & Jost 2012; doubling rule), beta-diversity decomposition with MANDATORY PERMANOVA + PERMDISP pair (Anderson & Walsh 2013), constrained ordination, and the read-counts-not-abundance critique (Lamb 2019). Use when processing eDNA samples for biodiversity assessment, deciding ASV vs OTU, configuring OBITools3 v3, interpreting decontam screening, or reporting community comparisons with the dispersion confound check.
日本語の概要は準備中です。原文の説明を表示しています。
Orchestrate the full ToolUniverse self-improvement cycle: discover APIs, create tools, test with researcher personas, fix issues, optimize skills, and push via git. References and dispatches to all other devtu skills. Use when asked to: run the self-improvement loop, do a debug/test round, expand tool coverage, improve tool quality, or evolve ToolUniverse.
日本語の概要は準備中です。原文の説明を表示しています。
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
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Automatically discover life science APIs online, create ToolUniverse tools, validate them, and prepare integration PRs. Performs gap analysis to identify missing tool categories, web searches for APIs, automated tool creation using devtu-create-tool patterns, validation with devtu-fix-tool, and git workflow management. Use when expanding ToolUniverse coverage, adding new API integrations, or systematically discovering scientific resources.
日本語の概要は準備中です。原文の説明を表示しています。
Biological knowledge: query curated assertions and reference databases for genes, variants, pathways, regulation, cell types, reference atlases, perturbation-derived relationships, phenotypes, therapeutic targets, drugs, interactions, annotations, signatures, compounds, and predicted structures. Use for identifiers, marker sets, gene sets, associations, ontologies, database facts, and cross-database coverage.
日本語の概要は準備中です。原文の説明を表示しています。
Plan 5G network deployment with coverage. TRIGGERS - Use when user needs help with 5g-deployment-plan related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Repository-specific AGENTS.md authoring and maintenance workflow. Use when creating, refreshing, or expanding AGENTS.md coverage for a codebase, including deciding whether nested AGENTS.md files are needed for subsystems with distinct rules, workflows, or AI-sensitive constraints.
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Guides systematic implementation of new sustainability metrics in OSS Sustain Guard using the plugin-based metric system. Use when adding metric functions to evaluate project health aspects like issue responsiveness, test coverage, or security response time.
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Build kokoro-js-jp and run its real-browser e2e suite (Worker + WASM openjtalkjs g2p + ONNX kokoro-js synthesis, English and Japanese). Use when asked to verify this package actually works in a browser, to check whether a change broke synthesis, or to add browser-level regression coverage for a bug in the g2p/synthesis pipeline that vitest's pure-function tests can't catch. Not for typecheck/lint/unit-test requests — use npm run typecheck / npm test for those.
日本語の概要は準備中です。原文の説明を表示しています。
Detect breaking API contract changes, DTO modifications without compatibility handling, and missing tests for changed API boundaries.
日本語の概要は準備中です。原文の説明を表示しています。
plan artifact がある時のみ、plan 中の assumption / open question が実装で解消された証拠を diff・PR 本文と突合する evidence-sufficiency 観点。解消されないまま残った前提・未記録の新規 Unknown を検出する。plan 欠損時は発火しない（Pre-execution Gate）。plan 欠損でも PR 本文に前提が inline 列挙されていれば列挙分のみ部分評価し、計画 issue の bare 参照だけなら skip する
テスト観点のレビューエージェント。 テスト網羅性、命名規則、フレーキーテスト、カバレッジギャップの個別スキルへルーティングする。
変更差分から重要なテスト観点と欠落を洗い出し、優先度付きでテストケース案を提示する
Performs simple mutation testing to verify test coverage and assertions.
日本語の概要は準備中です。原文の説明を表示しています。
Verification loop for Spring Boot projects: build, static analysis, tests with coverage, security scans, and diff review before release or PR.
日本語の概要は準備中です。原文の説明を表示しています。
Configura cobertura de tests y CI pipeline
日本語の概要は準備中です。原文の説明を表示しています。
Earnings-season triage across ALL active theses (not just Live Portfolio holdings) — every earnings call reported inside the window gets a Quartr event summary, a Conviction-Trigger/Outstanding-Questions cross-reference, and a coverage check against existing Research notes, producing a ranked deep-read queue for /transcript. Use when user says "earnings sweep", "who reported", "triage earnings", "catch up on earnings season", or after any earnings-heavy stretch. Default window 14 days; `/earnings-sweep 90` covers a full season.
日本語の概要は準備中です。原文の説明を表示しています。
Validate feature-level integration after all tasks are implemented. Checks cross-task consistency, full test suite, and overall spec coverage.
日本語の概要は準備中です。原文の説明を表示しています。
Independent quality assurance for one SDD Composy task in qa_required: CA coverage, unit/integration/E2E, accessibility, responsiveness, environment, and evidence inventory, producing the QA report and requesting evidence_required. Use when a task finished execution — 'rodar o QA da task', 'testar a TASK-003', 'validar a implementação'. Do NOT use for code review (sdd-review), the final verdict (sdd-verify), or test runs outside an SDD task.
日本語の概要は準備中です。原文の説明を表示しています。