grilling
無料Stress-test a plan, decision, or idea as a dependency-aware design tree. Use for grill-me requests, assumption audits, and decision clarification before implementation.
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。
2.4万 件 ・ 関連度順
概要と使いどころ
Stress-test a plan, decision, or idea as a dependency-aware design tree. Use for grill-me requests, assumption audits, and decision clarification before implementation.
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。
Linting and code quality workflow for Software Metrics Machine. Covers ESLint 9.x flat config, Prettier formatting, lint-staged (auto-fix on commit), per-workspace configs, TypeScript strict mode, and all lint commands. USE FOR: lint, eslint, prettier, format, code style, linting, lint fix, auto-fix, check style, code quality, lint-staged, typecheck, type-check, tsc noEmit. DO NOT USE FOR: writing tests (use tdd skill), building (use build commands), commit hooks setup.
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。
Test-Driven Development workflow for Software Metrics Machine. Covers test frameworks (Vitest 4.x for CLI/REST/core/utils, Jest 30.x for webapp), test patterns (describe/it, builder pattern, mocks via vi.fn), test commands, coverage requirements, and the Red-Green-Refactor cycle. USE FOR: write tests, run tests, test this, add tests, testing, coverage, TDD, test-driven development, vitest, jest, test pattern, test convention. DO NOT USE FOR: linting (use lint skill), building (use build commands directly), debugging production issues.
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。
Acceptance testing workflow for the Software Metrics Machine CLI e2e suite. Use when writing, extending, debugging, or reviewing bashunit acceptance tests under apps/cli/e2e, including command help checks, cached fixture flows, GitHub MSW-backed flows, local git repository fixtures, SMM_STORE_DATA_AT workspaces, and pnpm run test:cli:acceptance. USE FOR: CLI acceptance tests, e2e tests, bashunit, apps/cli/e2e, command smoke tests, persisted CLI output tests. DO NOT USE FOR: unit tests or Vitest tests (use tdd skill), linting (use lint skill), webapp browser tests.
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。
Makes the agent reconsider a task it just handed back to the human and find a way to do it itself, checking memory, CLI tools, skills, MCP servers, and documentation in turn. Use when the user invokes `/you` or `$you`, or replies that the agent should do something itself rather than asking them.
日本語の概要は準備中です。原文の説明を表示しています。
Watch a CI run's jobs to completion without idling or hand-writing a poll loop. Use when a dispatched or pushed build takes minutes to finish and its per-job results decide the next step.
日本語の概要は準備中です。原文の説明を表示しています。
Applies local reliability, viewport, tab-safety, stale-ref, widget, and browser-boundary lessons to every agent-browser automation. Use alongside the upstream agent-browser skill whenever navigating, clicking, filling, testing, extracting, taking screenshots, or debugging any website with agent-browser.
日本語の概要は準備中です。原文の説明を表示しています。
Triages an already-dirty Git working tree: breaks down every uncommitted change hunk by hunk, separates deliberate edits from tool-written churn, possibly accidental reversions, misplaced scope, and sensitive content, asks the user about the ambiguous cases, and proposes an ordered set of commits plus a list of hunks to hold back. Use when the user invokes `/pc` or `$pc`, asks what they should commit, wants their uncommitted changes broken down, or wants commits proposed for a dirty working tree or pile of accumulated local modifications. To plan commit boundaries for a change before or while implementing it, use `incremental-commits` instead.
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。
Load before the first bd command of any kind (reads included) in every session, even when bd prime context is already present. Applies reusable Beads writing and update practices when reading, creating, updating, commenting on, closing, superseding, or handing off Beads issues, alongside beads, beads-solo, and plan-to-beads workflows.
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。
Open a URL or local file in the user's regular browser, including live-rendered local Markdown. Use for `/open` or when the user asks to view a target outside the agent browser.
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。
Establish concise, cross-agent project instructions from repository evidence. Use when initializing or repairing AGENTS.md, CLAUDE.md, related discovery links, or project-specific agent guidance.
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。
Gives a repository one idempotent, repo-local worktree setup script (local env files, dependency install, build steps) that worktrunk's `.config/wt.toml` pre-start hook and Orca's `orca.yaml` scripts.setup both call, so every new git worktree is usable at once. Use when adding or fixing worktree setup hooks, writing `wt.toml` or `orca.yaml` setup, when new worktrees lack dependencies or `.env` files, or when asked to make worktrees "just work" in a repo. For creating a worktree in a repo that already has setup, use `git-branch-management` instead.
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。
Puts the agent into a cautious production mode for live systems: read-only inspection may proceed, but credentials and out-of-scope personal data need permission first, every state-changing action needs explicit per-action approval with its resource risks and rollback stated, and anything unexpected halts work until the user decides. Use when the user invokes `/prod` or `$prod`, or says they are working on production, a live or customer-facing server, a mail server, or a production database, or asks for care on a system where mistakes affect real users.
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。
React performance optimization. Identify unnecessary renders, apply memo/useCallback/useMemo correctly.
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。
Used by the Lead agent during Phase 6 (Brainstorm) to collaboratively explore user intent, requirements, and alternative approaches before locking in the architecture. Helps turn raw ideas into fully formed specs through natural dialogue.
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。
Identify independent failures and spawn concurrent agents. Turns sequential N×time into 1×time.
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 and sanitize all API inputs. Zod schemas, error responses, security considerations.
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。
Instancia esta plantilla en un proyecto real mediante una entrevista guiada — detecta si el proyecto es nuevo o existente, rellena los placeholders, adapta los docs al tipo de proyecto y decide la política de permisos. Úsalo cuando la persona clone/adopte esta plantilla y quiera configurarla para su proyecto (p. ej. "instancia esta plantilla", "configura este template para mi proyecto", "arranca el proyecto desde esta base").
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。
Extracts cfDNA fragmentomics features (DELFI genome-wide short/long ratios, WPS nucleosome positioning, Griffin GC-corrected accessibility profiles, end-motifs/MDS, OCF) for cancer detection and tissue-of-origin from plasma WGS. Centers on the nuclease-footprint reframe (every feature re-reads one nucleosome object), the mandatory GC correction, and the cross-protocol non-comparability that breaks naive classifiers. Runs FinaleToolkit (real CLI/Python, MIT) and the Griffin Snakemake pipeline; DELFI is a method, not a package. Use when deriving fragment-based signal from cfDNA, choosing a feature family for detection vs subtyping, or diagnosing why a fragmentomic model failed validation.
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。
Imports gene expression count matrices from featureCounts, HTSeq, STAR ReadsPerGene, Salmon/kallisto via tximport or tximeta, RSEM, 10X Genomics MTX/H5, AnnData H5AD, and RDS. Handles silent-miscounting traps (featureCounts -p v2.0.2 API break, STAR strandedness column choice, salmon NumReads-sum without tximport, RSEM non-integer expected_count, GENCODE _PAR_Y suffix, zero-length-transcript TPM divide-by-zero), and encodes the tximport countsFromAbundance decision tree with the "lengthScaledTPM is not TPM" warning. Use when assembling a gene-by-sample count matrix from aligner or quantifier output, importing salmon/kallisto for DESeq2 vs limma-voom, choosing strandedness column for STAR, debugging zero-count panics, or building tx2gene mapping.
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。
Assigns pathogen lineages (SARS-CoV-2 Pangolin UShER mode; Nextclade clade + QC; pango-designation alias resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage-fitness modelling (multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data and Nextclade dataset version pinning (mandatory; lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme churn (V3/V4/V4.1/V5.3.2/Midnight) with dropout regions, and recombinant X-prefix designation lag. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater into lineage frequencies with Freyja, tracking lineage frequencies over time, handling ARTIC primer dropouts, or running surveillance for SARS-CoV-2/influenza/Mpox/RSV/H5N1/measles.
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。
Detects m6A modifications from Oxford Nanopore direct-RNA-seq (DRS) signal using m6Anet (multiple-instance-learning over DRACH 5-mer signal). Covers the upstream pipeline (Dorado/Guppy basecalling -> minimap2 map-ont -> nanopolish eventalign -> m6anet dataprep -> m6anet inference), per-site vs per-read probability including the mod_ratio stoichiometry column, the DRACH-only constraint, minimum-coverage thresholds (20-50 reads/site), multi-condition comparison via xPore/Nanocompore/ELIGOS, Dorado native modification calling (RNA004, 2024+), and the cDNA-vs-DRS distinction (cDNA Nanopore CANNOT detect modifications). Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting probability_modified vs mod_ratio vs per-read probabilities, deciding between m6Anet (known DRACH sites) and Dorado/Remora (genome-wide screening), pinning RNA002 vs RNA004 chemistry and basecaller versions, or troubleshooting eventalign/dataprep failures.
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。
Maps between gene identifier systems (Ensembl, Entrez, HGNC symbol, UniProt, RefSeq, MANE) using AnnotationDbi, biomaRt, mygene, pyensembl, and Ensembl REST. Encodes Ensembl version stripping with GENCODE _PAR_Y preservation, the Ziemann 2016 Excel autocorrect debacle and Bruford 2020 HGNC renames (SEPT*->SEPTIN*, MARCH*->MARCHF*, MARC*->MTARC*, DEC1->DELEC1), OCT4/POU5F1 alias resolution, biomaRt archive endpoints for release pinning, the `filters` (plural) gotcha, MANE Select for clinical reporting, cross-species orthology via Ensembl Compara / OMA / OrthoDB, and tx2gene construction for tximport. Use when converting gene IDs across systems, handling renamed symbols, building tx2gene, pinning to a specific Ensembl release for reproducibility, or mapping cross-species orthologs.
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。
Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.
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。