153 件 ・ 関連度順
概要と使いどころ
Hunting skill for graphql vulnerabilities. Built from 12 public bug bounty reports across IDOR via node() / GID, mutation IDOR including AI/LLM features, cross-tenant IDOR, SSRF via argument, batching-DoS, query-cost-bypass, SQLi via argument, broken-object-level-authz, auth-bypass via unscoped mutations, and PII exposure from missing field-level authz. Use when hunting graphql on any target.
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。
Compute the EXACT sub-transaction impact of a rollup rule in TRES Finance — every filter applied — and flag genuine problems (zero matches, overlap, config mistakes) before the rule is created. Two modes. Mode A: a pre-create quality gate invoked by the tres-rollup-rules skill to vet proposed candidate rules. Mode B: standalone review of a rule someone submitted or of existing PENDING rules. Trigger this skill when the user says "review this rollup rule", "what would this rollup rule actually match", "preview the rollup impact", "how many transactions would this rule catch", "is this rollup rule valid", "validate my rollup rule", "check my pending rollup rules", or "review the rollup requests". Do NOT use this to design or propose new rollups — that is tres-rollup-rules. This skill only measures impact and flags issues; it never executes mutations.
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。
Run browser-grounded social research without remote account mutations through Jev Social when a user wants posts, profiles, comments, video evidence, or a source-linked report from Instagram, TikTok, or LinkedIn and the local socai CLI reports support for that platform. Do not use for publishing, engagement actions, or general web research.
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。
Functional programming helpers for Golang using samber/lo — 500+ type-safe generic functions for slices, maps, channels, strings, math, tuples, and concurrency (Map, Filter, Reduce, GroupBy, Chunk, Flatten, Find, Uniq, etc.). Core immutable package (lo), concurrent variants (lo/parallel aka lop), in-place mutations (lo/mutable aka lom), lazy iterators (lo/it aka loi for Go 1.23+), and experimental SIMD (lo/exp/simd). Apply when using or adopting samber/lo, when the codebase imports github.com/samber/lo, or when implementing functional-style data transformations in Go. Not for streaming pipelines (→ See `samber/cc-skills-golang@golang-samber-ro` skill).
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。
Query the Genome Aggregation Database (gnomAD). Use when determining the rarity or allele frequency of specific genetic variants, retrieving gene constraint metrics (pLI, LOEUF) to assess loss-of-function intolerance, finding variants in a genomic region or gene, or querying structural variants. Don't use for analyzing individual patient genomes, tracking somatic mutations in cancer (use COSMIC), or requesting raw sequencing reads (use ENA).
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 tumor neoantigens from somatic mutations using pVACtools for personalized cancer immunotherapy. Predict mutant peptides that bind patient HLA and may elicit T-cell responses. Use when identifying vaccine targets or checkpoint inhibitor response biomarkers from tumor sequencing data.
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。
Design pegRNAs for prime editing using PrimeDesign algorithms. Generate spacer, PBS, and RT template sequences for precise genomic modifications without double-strand breaks. Use when designing prime editing experiments for precise insertions, deletions, or point mutations.
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。
Provides authoritative compatibility checks, pricing estimates, connection troubleshooting, pre-warming guidance, and infrastructure mutations for Amazon Keyspaces (for Apache Cassandra). Covers LWT/batch operations, secondary indexes, materialized views, capacity modes, TTL, PITR, CDC, auto-scaling, multi-region keyspaces, UDTs, nodetool diagnostics parsing, SQL-to-Cassandra migration, and Cassandra-to-Keyspaces migration scenarios. Agents frequently produce incomplete or incorrect answers about Keyspaces feature support without this skill loaded.
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。
Octane bindings for TanStack DB. useLiveQuery hook with dependency arrays (8 overloads: query function, config object, pre-created collection, disabled state via returning undefined/null). useLiveSuspenseQuery for Octane Suspense with Error Boundaries (data always defined). useLiveInfiniteQuery for cursor-based pagination (pageSize, fetchNextPage, hasNextPage, isFetchingNextPage). usePacedMutations for debounced Octane state updates. Return shape: data, state, collection, status, isLoading, isReady, isError. Import from @octanejs/tanstack-db (re-exports all of @tanstack/db).
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。
Convex backend development guidelines. Use when writing Convex functions, schemas, queries, mutations, actions, or any backend code in a Convex project. Triggers on tasks involving Convex database operations, real-time subscriptions, file storage, or serverless functions.
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 cancer and infers tissue-of-origin from cfDNA methylation by choosing conversion chemistry (bisulfite vs EM-seq vs TAPS vs cfMeDIP), calling read-level methylation haplotypes rather than averaged beta values, and deconvolving a hematopoietic-dominated cfDNA mixture against a methylation atlas via NNLS/quadratic programming. Encodes the GRAIL/CCGA thesis that thousands of tissue-specific markers make methylation outperform sparse mutations for multi-cancer early detection (MCED) and localization, and that single concordantly-methylated fragments give ppm-level sensitivity. Uses MethylDackel for extraction (mbias-then-extract), MEDIPS/QSEA for enrichment data, scipy.optimize.nnls for deconvolution. Use when building an MCED or methylation-MRD assay, picking a conversion chemistry for low-input plasma, or deconvolving tissue-of-origin from cfDNA.
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 acquired antimicrobial-resistance determinants and chromosomal point-mutation resistance in bacterial assemblies using AMRFinderPlus, ResFinder 4.0 (acquired + PointFinder), CARD-RGI, abritAMR, staramr, and species-specific callers (TB-Profiler, Mykrobe). Harmonises cross-tool output via hAMRonization, contextualises determinants with mobile-genetic-element annotation (MOB-suite, PlasmidFinder, MobileElementFinder, ICEberg), predicts phenotype against EUCAST or CLSI breakpoints, and translates calls into WHO GLASS reporting categories. Use when screening clinical or surveillance isolates for AMR, distinguishing acquired vs intrinsic vs point-mutation resistance, calling rpoB / katG / pncA / gyrA / mgrB mutations, reconciling AMRFinderPlus vs RGI vs ResFinder disagreement, contextualising carbapenemases or mcr alleles on plasmids, predicting susceptibility from genotype against the WHO Mtb 2nd-edition catalogue, or building a hAMRonized multi-lab AMR surveillance 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。
Resolve subclonal copy number, whole-genome doubling, and copy-number tumor evolution from bulk sequencing with Battenberg, TITAN, and MEDICC2. Covers clonal versus subclonal copy-number states, haplotype phasing for subclonal resolution, cancer cell fraction, whole-genome-doubling detection and timing relative to mutations, mirrored subclonal allelic imbalance, and copy-number phylogenies. Use when a tumor is heterogeneous and bulk data shows non-integer copy number, when calling subclonal CNAs, detecting or timing whole-genome doubling, reconstructing copy-number evolution, or deciding between Battenberg and TITAN.
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 single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or HMM/kernel-density methods (PureCLIP, PARalyzer, CTK). Use when single-nucleotide resolution is required for motif registration (mCross), allele-specific binding (BEAPR), variant-effect prediction, or comparing crosslink chemistry across CLIP variants.
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。
Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream tools.
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。
Use when managing Apple Ads with asc, including OAuth profiles, ad-account discovery, Platform API v1 campaigns and targeting, reports, assets, recommendations, guarded mutations, raw requests, and Campaign Management API v5 migration.
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。
Use when a UE5 task involves materials or textures: a master material and instances for a kit, Substrate or legacy, Blendable vs Adaptive GBuffer, glass, emissive screens, decals, edge wear and dirt, landscape layers and RVT, toon or cel shading, "too many shaders" or shader permutations, static switches, usage flags, texture compression (BC7, normal maps, ORM packing, sRGB), texture memory, or "is this material expensive".
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。
Use when using the Dialogue Manager addon — .dialogue files with titles, responses, conditions and mutations, runtime balloons, and C# support
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。
Generates an offline operation queue with persistence, automatic retry on connectivity, and conflict resolution. Use when user needs offline-first behavior, queued mutations, or pending operations that sync when back online.
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。
Use when setting up Data Connect, writing GraphQL queries/mutations, configuring generated SDKs, handling offline, or applying security rules.
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。
Operately frontend data fetching with TanStack Query. Use when adding or changing page loaders, model hooks, Api.* calls, mutations, useLoadedData, Pages.useRefresh, or any web UI backend request. New code must use TanStack. When fixing or extending an existing surface, migrate that surface's API calls to TanStack in the same change.
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。
Operately test layout, naming (.projections.json), factories, feature/e2e steps, external query/mutation auth specs, and how to run Elixir/API/JS/EE tests. Use when adding, renaming, splitting, or reviewing tests; choosing where a test belongs; writing Factory/TurboCase/FeatureCase or ExternalApi QuerySpec/MutationSpec tests; or running make test / feature 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。
Implement secure Next.js Server Actions for mutations, forms, and optimistic UI. Use when building actions, form flows, auth checks, or revalidation after writes.
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。