「cro」の検索結果

Think and work like an expert Environmental Microbiologist. Use when a task calls for Environmental Microbiologist judgment. Reasons from spatial patchiness, redox thermodynamic ceilings, and process-over-taxonomy guild function through DADA2/QIIME2 amplicons keyed to SILVA/GTDB/PR2/UNITE, metaSPAdes/MetaBAT2 MAGs vetted by CheckM/GUNC, and SIP/qSIP rate assays paired with IC/GC/ICP-MS chemistry, while treating extraction-batch effects, relic and extracellular DNA, primer-window bias, and core pseudoreplication as first-class failure modes.

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。

Think and work like an expert Food Microbiologist. Use when a task calls for Food Microbiologist judgment. Reasons from food as a hurdle-governed matrix of water activity, pH, and redox through BAM/ISO reference methods, c/n/m/M sampling plans, PMA-v-qPCR, and ComBase kinetics while treating VBNC and injured cells, post-process contamination, matrix inhibition, and unconfirmed PCR hits as first-class failure modes.

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。

Think and work like an expert Crop Protection Scientist. Use when a task calls for Crop Protection Scientist judgment. Reasons from IPM, EIL/ET, and FRAC/HRAC/IRAC MoA rotation through GEP/EPPO efficacy trials, CDMS label law, BBCH timing, DRT application, PPDB/fate modeling, and MRL/GAP alignment while treating resistance, drift, herbicide carryover, and abiotic mimicry as first-class failure modes.

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。

Think and work like an expert Bioprocess Microbiologist. Use when a task calls for Bioprocess Microbiologist judgment. Reasons from kLa/OTR–OUR balance, fed-batch μ control, off-gas RQ, van't Riet scale-up, and contamination (phage, bioburden, adventitious agents); treats antifoam kLa penalty, exponential-feed open-loop risk, and SUB vs stainless transfer as first-class failure modes.

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。

Think and work like an expert Clinical Microbiologist. Use when a task calls for Clinical Microbiologist judgment. Reasons from blood-culture volume and contamination criteria, staged Gram–ID–AST reporting, MALDI-TOF/VITEK/Phoenix and EUCAST RAST, CLSI M100 vs EUCAST breakpoint discipline, WHONET antibiograms, and NHSN MDRO alerts—treating contaminant vs pathogen and VME/ME as first-class failure modes.

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。

Think and work like an expert Antimicrobial Resistance Scientist. Use when a task calls for Antimicrobial Resistance Scientist judgment. Reasons from MIC distributions, ECOFFs, and phenotype–genotype concordance through EUCAST/CLSI AST, CARD/RGI and AMRFinderPlus resistomes, GLASS/WHONET/NARMS surveillance, carbapenemase/ESBL/MRSA mechanism panels, and heteroresistance PAP while treating breakpoint mixing, genotype-without-phenotype overclaim, selection-bias surveillance, and CARD version drift as first-class failure modes.

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。

Create, implement, or review gsap scrolltrigger work with format, accessibility, performance, and visual-verification controls. Use when the requested deliverable depends on gsap scrolltrigger.

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。

Research and evaluate microsoft docs with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for microsoft docs findings or verification.

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。

Research and evaluate microsoft code reference with current authoritative sources, provenance, and explicit evidence gaps. Use when the user asks for microsoft code reference findings or verification.

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。

Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome 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。

Detect sample contamination and cross-species reads using FastQ Screen. Screen reads against multiple reference genomes to identify bacterial, viral, adapter, or sample swap contamination. Use when suspecting cross-contamination or working with samples prone to microbial contamination.

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。

Project gene annotations across genomes using TOGA (Kirilenko 2023 whole-genome-alignment chain-based projection with intactness classification), CESAR 2.0 (Sharma & Hiller 2017 codon-aware exon projection), LiftOff (Shumate & Salzberg 2020 reference-based annotation transfer), Liftover (UCSC), GeMoMa (Keilwagen 2019 evidence-based projection), and Comparative Annotation Toolkit (CAT). Use when transferring annotations from a well-annotated reference to query genome(s), classifying gene-loss vs gene-intact across many genomes at scale, building Zoonomia-style comparative annotations across hundreds of mammals or birds (Kirilenko 2023), detecting pseudogenization, projecting alternative isoforms, or selecting between WGA-anchored (TOGA) vs ortholog-based (LiftOff) annotation transfer strategies.

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。

Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.

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。

Calculates species richness, diversity, and turnover using the Hill number framework with iNEXT coverage-based rarefaction/extrapolation, asymptotic diversity estimation, and beta diversity partitioning (betapart turnover vs nestedness). Compares assemblages using coverage-standardized rather than size-standardized rarefaction. Use when quantifying biodiversity from species abundance or incidence data, comparing diversity across sites, or constructing rarefaction curves. Not for clinical 16S microbiome alpha/beta diversity (see microbiome/diversity-analysis).

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。

Operate professional paid advertising across Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for account intake, source-grounded audits, strategy, budget and measurement planning, creative production, experiments, reporting, monitoring, and explicitly approved campaign changes. Also trigger on PPC, paid social, retail media, attribution, tracking, landing pages, cross-platform conversion totals, negative keywords or search terms, beta-feature scoring, stale platform claims, API-token or credential setup, campaign deletion, and safe Claude Ads installation or uninstall.

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。

Create cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill, audit this skill, is this skill safe, vet a skill before installing, what does this skill access. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, spec validation, and security auditing of third-party skills before install.

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。

Create or modify a konsistent.json configuration file that enforces structural conventions in a TypeScript codebase. Use when the user wants to enforce consistent code structure, validate exports/imports across files, ensure directories contain required files, enforce naming patterns, add/remove/update convention rules, configure case map overrides for acronyms or special casing (kebabToPascalMap, kebabToCamelMap), or troubleshoot why konsistent is reporting violations. Triggers on: "konsistent", "konsistent.json", "enforce conventions", "structural consistency", "consistent exports", "consistent structure", "code conventions config", "add convention", "update convention", "fix konsistent errors", "case map", "case override", "acronym casing".

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 visual regression testing with Playwright screenshots, Chromatic, Percy, and Argos CI. Covers baseline management, diff threshold tuning, dynamic content masking, responsive viewport testing, and review/approval workflows. Use when: "visual test," "screenshot," "visual regression," "pixel diff," "snapshot diff," "update baselines," "Chromatic," "percy snapshot," "argos screenshot." Not for: bulk baseline regeneration after a redesign broke many tests — use selector-drift-recovery; cross-browser rendering matrices — use cross-browser-testing; general Playwright test structure — use playwright-automation. Related: playwright-automation, ci-cd-integration, cross-browser-testing.

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。

Schedule recurring tasks with cron on Linux/macOS. Use when a user asks to run scripts on a schedule, set up automated backups, schedule data processing, or configure periodic tasks on a server.

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。

Crossplane for infrastructure as code using Kubernetes CRDs. Use when the user needs to provision and manage cloud resources declaratively through Kubernetes APIs, compose custom infrastructure abstractions, or build internal platforms.

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。

Integrate with Google Calendar and Microsoft Outlook Calendar for scheduling, event management, and availability tracking. Use when someone asks to "create calendar events", "check availability", "schedule meetings", "sync calendars", "Google Calendar API", "Outlook Calendar API", "booking system", "find free slots", or "manage recurring events". Covers Google Calendar API v3, Microsoft Graph Calendar API, event CRUD, availability/free-busy queries, recurring events, and building scheduling features.

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。

World-class motion design expertise combining Disney's 12 principles of animation, Material Design's motion system, and the performance-first philosophy of production interfaces. Motion design is the craft of bringing interfaces to life - not through decoration, but through clarity, continuity, and communication. Great motion design is invisible. Users don't notice the animations - they notice that the interface feels natural, responsive, and alive. Every transition tells a story: where did this come from? Where is it going? What just happened? Motion is the language of cause and effect in digital interfaces. Use when "animation, motion, transition, microinteraction, easing, timing, choreography, loading animation, skeleton loader, page transition, hover effect, scroll animation, spring animation, keyframes, framer motion, gsap, lottie, animation, motion, transitions, microinteractions, easing, timing, accessibility, performance, frontend, design" mentioned.

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。

Go is the language of infrastructure. From Docker to Kubernetes to the entire cloud-native ecosystem, Go powers the systems that run the internet. It's not about what you can build - it's about what you won't break at 3 AM. This skill covers idiomatic Go patterns, error handling, concurrency with goroutines and channels, HTTP servers, microservice architecture, and the standard library that makes Go so powerful. Key insight: Go's simplicity is a feature. Fight the urge to abstract. Embrace boring, readable code. 2025 lesson: The teams succeeding with Go are the ones who resist overengineering. A main.go with 500 lines beats a "clean architecture" with 50 packages. Use when "golang, go service, go microservice, goroutine, channels, go http, go api, go backend, gin, fiber, chi router, go concurrency, go, golang, microservices, backend, concurrency, goroutines, channels, http, api" mentioned.

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。

Audit whether a paper's baseline comparisons are COMPLETE, FAIR, and SIGNIFICANT: a required recent SOTA baseline is missing while 'best/SOTA' is claimed (HP-MISSING-BASELINE); a baseline is undertuned / given less compute-tuning-data, run at a mismatched config, or the equal-budget ablation-as-baseline is absent (HP-WEAK-BASELINE); 'outperforms' is asserted over overlapping error bars or with no variance/seeds (HP-SIG-OVERLAP); and a cross-row 'improves over baseline by X%' is arithmetically wrong (HP-DELTA-ERROR, cross-row form only). A versioned per-domain baseline profile + a live leaderboard/recency search are assembled by the EXECUTOR as structured facts; a fresh cross-model reviewer (gpt-5.6-sol xhigh, read-only, fresh thread per dimension) PROPOSES findings, each span-anchored to a ledger claim_id; tools/adjudicate_findings.py DECIDES the verdict. Works at L0 (stated comparisons) and deepens at L2 (configs/result files). A completeness question it cannot settle internally becomes needs_external_check, never a guessed missing baseline. Emits baseline-comparison-audit.findings.json; computes NO verdict. Detect-only. Triggers: "baseline audit", "missing baselines", "is the comparison fair", "weak baseline", "baseline 误报", "SOTA earned?".

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。