本文へ移動
cccskills

「ara」の検索結果

6,195 件 ・ 関連度順

概要と使いどころ

Delimits putative species boundaries from molecular data within the de Queiroz 2007 unified-lineage framework using ASAP (Puillandre 2021 successor to ABGD), mPTP C++ (Kapli 2017 successor to bPTP; bPTP is Python NOT R), GMYC single/multi-threshold (Pons 2006; Fujisawa 2013), multilocus BPP v4 with prior calibration from data (NOT defaults; Yang 2015), SNAPP + BFD* for SNP delimitation, DELINEATE (Sukumaran 2021) speciation-process modeling to address Sukumaran & Knowles 2017 PNAS critique that MSC delimits structure not species, integrative-taxonomy congruence (Padial 2010; Carstens 2013), Dsuite for introgression testing before sister claims (Malinsky 2021), and Meyer & Paulay 2005 barcoding-gap-absence caveat. Use when delineating species from DNA barcoding data, resolving cryptic complexes, choosing among ASAP/mPTP/BPP/DELINEATE, calibrating BPP priors, distinguishing introgression from ILS, or applying the Sukumaran-Knowles oversplitting correction.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Query the Ensembl REST API for gene/transcript/protein lookup, sequence retrieval, comparative genomics (Compara), variant effect prediction (VEP), regulatory features, and cross-species ortholog/paralog calls. Use when pulling Ensembl-native data (Ensembl Gene IDs, version-pinned releases, archive endpoints for reproducibility), gene/transcript/exon structure with stable IDs, or VEP for variant annotation. Encodes the 15 req/sec rate limit, archive (e110.rest.ensembl.org) for reproducibility, Ensembl divisions (vertebrates / plants / fungi / metazoa / bacteria), and the symbol-vs-ID stability problem.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Detect, date, and contextualize whole-genome duplication (WGD / paleopolyploidy) events using wgd v2 (Chen et al 2024), KsRates (Sensalari 2022 substitution-rate-corrected Ks dating), DupGen_finder (Qiao 2019), MAPS (Li 2018 phylogenomic), POInT (Conant 2008 ordered-block), SLEDGe (2024 ML-based), Whale.jl (Bayesian DL+WGD), and synteny-anchored paranome construction. Use when identifying ancient polyploidy from Ks distributions and synteny block analysis, positioning WGD events relative to speciation, distinguishing tandem from segmental from WGD duplications, dating the 2R/3R vertebrate / fish / salmonid WGDs, building paranome and Ks-age mixture models, applying KsRates substitution-rate correction across lineages, or testing alternative biased-fractionation / dosage-balance models post-WGD.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA whole-genome-alignment orthology. Use when building single-copy ortholog sets for phylogenomics, classifying co-orthologs and in/out-paralogs after gene duplication, propagating functional annotation via orthology with awareness of the ortholog conjecture, distinguishing speciation from duplication via gene-tree species-tree reconciliation, computing Quest-for-Orthologs benchmark performance, or running synteny-aware ortholog detection in WGD-affected lineages.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Viking Search tuning for specified policy directions. Use this when the user provides specific queries, a type of query, or a business policy direction, and asks to boost, suppress, or fix a class of search results through request-parameter passthrough. You must only perform read-only baseline evaluation and request-level candidate testing; do not modify search scenes, app config, dictionaries, recommend scenes, or primary recall parameters.

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。

volcengine/SearchCLI1,1882026年10月10日 更新

Discover and connect to Bluetooth Low Energy (BLE) peripheral devices from MATLAB. Use this skill when the user wants to scan for BLE devices, connect to a BLE peripheral, read or write BLE characteristics, subscribe to notifications, or any task that requires a BLE connection as a prerequisite (e.g., read sensor data over BLE, monitor heart rate, log accelerometer, stream data from wearable, IoT device communication). Triggers on: BLE, Bluetooth Low Energy, blelist, ble device, BLE characteristic, GATT, service UUID, scan for devices, BLE sensor, subscribe notify, BLE read, BLE write, peripheral device, BLE connect, wireless sensor.

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。

matlab/matlab-agentic-toolkit1,1632026年10月9日 更新

S-parameters, insertion loss, fields, currents, mesh control, and solver selection for RF PCB performance validation. TRIGGER: user asks to compute S-parameters, analyze insertion/return loss, extract fields or currents, compare MoM vs FEM, or control mesh for any RF PCB component. Invoke BEFORE writing sparameters() or solver code — API is non-obvious. SKIP: designing or creating components (use the specific matlab-design-pcb-* skill), material/stackup setup only (use matlab-manage-pcb-material), optimization sweeps (use matlab-optimize-pcb-design), PDN/IR-drop analysis (use matlab-analyze-pcb-pdn).

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。

matlab/matlab-agentic-toolkit1,1632026年10月9日 更新

Speed up local parfor, parfeval, or spmd by switching to a thread-based parallel pool. Trigger when a user describes slow or disappointing local parallel performance, even if they don't mention threads. Symptoms: parfor on a laptop/workstation is slower than expected or "only slightly faster than for"; parfor scales poorly with the number of workers; ticBytes/tocBytes, the Parallel Pool dashboard, mpiprofile, or system tools show large per-worker data transfer; large broadcast variables or sliced inputs make iterations slow; opening a process pool dominates a short workload; user mentions serialisation or data transfer overhead. Also trigger on any question about whether code or a function works on a thread pool. For non-pool MATLAB performance work (vectorisation, preallocation, profiling), defer to matlab-optimize-performance.

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。

matlab/matlab-agentic-toolkit1,1632026年10月9日 更新

Use when writing MATLAB functions with arguments blocks — repeating arguments (arguments (Repeating)), .?ClassName property import in constructors, name-value forwarding with namedargs2cell, or migrating from inputParser or validateattributes. Also when reviewing signatures for implicit-conversion pitfalls (size reshaping, class coercion, computed defaults), or when restricting, constraining, or validating function inputs — scalar vs vector enforcement, type rejection, size checking. Also when asked to harden inputs, make a function more robust, tighten input checking, or rewrite for safer input acceptance — even without "validation" or "arguments block" wording. Triggers on: arguments block, mustBe validators, name-value arguments, varargin, inputParser, nargin/narginchk, restrict input, type checking, scalar constraint, harden inputs, defensive programming. Not for: App Designer callbacks, Simulink mask parameters, class inheritance, or runtime validation outside function or property declarations.

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。

matlab/matlab-agentic-toolkit1,1632026年10月9日 更新

Comprehensive skill for Locomotive Scroll smooth scrolling library with parallax effects, viewport detection, and scroll-driven animations. Use this skill when implementing smooth scrolling experiences, creating parallax effects, building scroll-triggered animations, or developing immersive scrolling websites. Triggers on tasks involving Locomotive Scroll, smooth scrolling, parallax, scroll detection, scroll events, sticky elements, horizontal scrolling, or GSAP ScrollTrigger integration. Integrates with GSAP for advanced scroll-driven animations.

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。

freshtechbro/claudedesignskills1,0482025年11月20日 更新

github

無料

When the user wants to use GitHub for SEO, parasite SEO, GEO, open source marketing, README optimization, or curated Awesome lists. Also use when the user mentions "GitHub," "GitHub SEO," "GitHub parasite SEO," "GitHub GEO," "awesome list," "GitHub README," "profile README," "pinned repositories," "Trending," "Explore," "repository name," "About section," "GitHub description," "GitHub topics," "Website field," "GitHub Pages," "github.io," "user site," "project site," "GitHub gist," "curated list," or "navigation list." Not for Medium or other non-GitHub platforms—use parasite-seo or medium-posts. For OSS business model, use open-source-strategy.

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。

kostja94/marketing-skills1,0332026年10月6日 更新

Use when sculpting a realistic head, face, portrait, body or creature in ZBrush (anatomy, landmarks, proportions, "the face looks off", eyes, lips, jaw), adding skin, pores, wrinkles or reptile and dragon scales with alphas, Surface Noise, layers or morph targets, planning subdivision or HD Geometry for a film close-up, reprojecting detail, sculpting cloth folds or running Dynamics cloth, growing FiberMesh fur or hair, making horns, or judging a character sculpt the way a senior character artist would.

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。

scenario-labs/skills9972026年10月13日 更新

Use when rigging a character, creature or prop in Maya: "rig this character", placing or orienting joints, Orient Joint doing nothing, IK/FK switch and matching, pole vector flips or elbow drift, space switching, foot roll, spline IK spine, offsetParentMatrix, blendMatrix or matrix rigging, controls and lockdown for animators, Quick Rig, HumanIK, AdvancedSkeleton or mGear, a game skeleton for Unreal or Unity, or a slow rig (parallel evaluation, profiling, GPU Override not kicking in).

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。

scenario-labs/skills9972026年10月13日 更新

Use when one look must hold across Scenario generations: one character across scenes, a turnaround, or a video animated from its references, one product across angles, one style across icon sets, a character from an uploaded drawing, a variant off an approved baseline, or deciding when references stop scaling and a trained model is due. Triggers: make this match, same character, on-model, reference to video, style reference. Keywords: consistency, identity, control map, seed, LoRA.

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。

scenario-labs/skills9972026年10月13日 更新

offers

無料

When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.

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。

Nexus-JPF/note-companion8702026年10月13日 更新

Pick the right LLM for LEGAL TRANSLATION — translating contracts, statutes, case law, and legal correspondence across languages, including Arabic/MENA. Vendor-neutral routing triangulated from mid-2026 evidence (WMT25 human eval, SwiLTra-Bench legal-MT, multilingual-reasoning proxies, ArabLegalEval). There is NO clean legal-translation leaderboard, so this vertical is directional and treats human legal-linguist review as mandatory. Asks up to 4 quick questions (language pair, cost, speed, privacy/certification), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model to translate this contract/statute", "best AI for legal translation", "translate this legal doc to/from Arabic", or is about to machine-translate legal text without a fixed model.

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。

lawve-ai/awesome-legal-skills8642026年10月3日 更新

Searches the domestic courts of 122 jurisdictions — 153 databases, 49 automated — for extradition and arrest-warrant surrender decisions, each in its own language and vocabulary. Answers the question no commercial database does: how are OTHER executing states treating this requesting state, or this ground? Searching by requesting state localises its name per jurisdiction (AE becomes 'Emiratele Arabe Unite' in Romania, 'Emirati Arabi Uniti' in Italy), so the sweep finds what those courts actually wrote. Every hit passes a relevance gate; every search leaves a dated report, so the research is reconstructable months later. Use when asked what foreign courts have said about surrender to a given state, whether any European court has refused extradition on prison conditions, assurances or Article 3, for comparative extradition research, or to build a foreign-authority section of an extradition argument. Not for domestic case law of the user's own jurisdiction, and never a substitute for reading the judgment.

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。

lawve-ai/awesome-legal-skills8642026年10月3日 更新

Train a character/identity LoRA locally on FLUX.1-dev via the comfyui-mcp train_* tools (GPU Docker + ostris ai-toolkit). Use when the user wants to train a LoRA of a person/character from their photos on the local GPU. Covers dataset prep, launch, monitoring, and using the result in ComfyUI. For WAN/Z-Image training via the ai-toolkit UI see ai-toolkit-trainer.

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。

artokun/comfyui-mcp8202026年10月5日 更新

Quarantines an intermittently failing test behind a ticket with an owner and expiry, assigns a root-cause bucket from isolated reruns, and defines when the test leaves quarantine. Use when a test is a QUARANTINE_CANDIDATE or fails without a code change; not for deterministic 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。

HoangNguyen0403/agent-skills-standard5752026年10月12日 更新

Build scalable asynchronous workflows using Queues, Jobs, and Events in Laravel. Use when implementing queued jobs, event-driven workflows, or async processing in Laravel.

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。

HoangNguyen0403/agent-skills-standard5752026年10月12日 更新

Enforce core architectural standards for scalable Laravel applications. Use when structuring controllers, service layers, action classes, Form Requests, or Service Container bindings in Laravel projects.

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。

HoangNguyen0403/agent-skills-standard5752026年10月12日 更新

Share state between components that don't have a direct parent-child parameter relationship, using cascading values, scoped services with change events, or CascadingValueSource via DI. USE WHEN the user needs a CascadingParameter or CascadingValue that works across render mode boundaries, a shopping cart or notification count accessible from multiple pages, a theme or user preference cascaded app-wide, or when components in different parts of the tree must react when shared data changes. Also USE WHEN cascading values aren't reaching interactive children in per-page interactivity mode, or when the user needs to understand scoped vs singleton service lifetime for state on Blazor Server. DO NOT USE for direct parent-child parameter passing or EventCallback (see author-component), for persisting state across prerender-to-interactive transitions (see support-prerendering), or for service abstractions for data fetching in Auto/WebAssembly (see fetch-and-send-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。

managedcode/dotnet-skills4862026年10月13日 更新

Create a persistent HeyGen avatar — a reusable face + voice identity for the agent, the user, or any named character — powered by HeyGen Avatar V technology. Prompt-based creation by default (description → HeyGen builds it); photo upload is optional for real-person digital twins. Use when: (1) giving the agent a face + voice so it can present videos ("bring yourself to life", "create your avatar", "give yourself an avatar", "design a presenter", "set up an avatar", "let's make an avatar"), (2) the user wants to appear in videos as themselves ("create my avatar", "I want my face in a video", "digital twin of me", "build me an avatar"), (3) building a named character presenter ("create an avatar called Cleo", "design a character named X"), (4) establishing HeyGen identity before making videos — the correct FIRST step when no avatar exists yet. Chain signal: when the user says both an identity/avatar action AND a video action in the same request ("create an avatar AND make a video", "set up identity THEN create a video", "design a presenter AND immediately record"), run heygen-avatar first, then heygen-video. Returns avatar_id + voice_id — pass directly to heygen-video to create HeyGen videos. NOT for: generating videos (use heygen-video), translating videos, or TTS-only 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。

heygen-com/skills4772026年7月15日 更新