Results for “multiqc”

Use when you need to aggregate quality control reports from multiple bioinformatics tools into a single HTML report

Use when you need to perform quality control analysis on high-throughput sequencing data (fastq, bam, sam, or fast5 files) to identify potential problems before downstream analysis.

Coordinate agents via the AMQ CLI for file-based inter-agent messaging. Use this skill whenever you need to send messages to another agent (codex, claude, or any named handle), check your inbox, drain queued messages, set up co-op mode between agents, join a swarm team, route messages across projects, or diagnose delivery issues. Also use it when you receive a message and need to know how to reply, inspect receipts, or handle priority. Covers any multi-agent coordination task where agents need to talk to each other — review requests, questions, status updates, decision threads, wake notifications, and orchestrator integration (Symphony, Kanban). For collaborative spec/design workflows specifically, prefer the /amq-spec skill which provides structured phase-by-phase guidance. Not intended for distributed systems design (RabbitMQ, Kafka), CI/CD pipelines, or single-agent tasks with no partner.

Orchestrates a complete bulk RNA-seq differential-expression study from raw FASTQ reads through QC, alignment, quantification, differential expression, pathway enrichment, and publication figures.

用户咨询腾讯云产品资源、AWS、阿里云等多云资源时，查看智能顾问架构图、架构目录、架构详情、架构评估结果、绘制架构图、开通智能顾问时、AI智能巡检、AI容量监测、AI混沌演练、AI云诊断、主动预警、架构健康度、云运维问答、云资源查询、云成本优化、安全合规、云资源盘点、闲置资源检查、云产品最佳实践等AIOps、ChatOps、CloudOps操作时使用。

MVCC (Multi-Version Concurrency Control)

Agent E3 - Mixed Methods Integration Specialist - Qual-Quant data integration and meta-inference. Covers joint display creation, integration strategies, and legitimation techniques.

Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).

Agent C3 - Mixed Methods Design Consultant Comprehensive mixed methods research design specialist covering sequential, concurrent, embedded, and multiphase designs with Morse notation. Core Capabilities: - Sequential Explanatory (QUAN → qual): Explain quantitative results - Sequential Exploratory (QUAL → quan): Develop instruments - Convergent Parallel (QUAN + QUAL): Comprehensive understanding - Embedded (QUAN(qual)): Secondary strand addresses different question - Multiphase: Long-term projects with iterative phases - Morse notation interpretation and recommendation

Enables AI agents to pay humans with USDC via molty.cash, supporting tips, hiring for tasks, and creating gigs with on-chain settlement on Base.

Simulates open quantum systems with QuTiP, the Quantum Toolbox in Python, solving Lindblad master equations (mesolve), Monte Carlo trajectories (mcsolve), and unitary dynamics (sesolve). Use when studying master-equation or Lindblad dynamics, decoherence, dissipation, quantum optics, cavity QED, or open-system time evolution. NOT for circuit-based quantum computing or hardware execution — for IBM Quantum circuits prefer alterlab-qiskit, for Google Quantum AI or NISQ circuits prefer alterlab-cirq, and for gradient-trained quantum ML prefer alterlab-pennylane. Part of the AlterLab Academic Skills suite.

Use when doing lightweight FASTA/FASTQ transformations such as conversion, subsampling, subsequence extraction, trimming, or quick QC with seqtk.

Developing for multicore systems in Zephyr RTOS. Covers Symmetric Multiprocessing (SMP), Asymmetric Multiprocessing (AMP) with OpenAMP/RPMsg, inter-processor communication (IPC) patterns, and Linkable Extensions (LLEXT). Trigger when designing for SoCs with multiple homogeneous or heterogeneous cores.

Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).

Manage multiple n8n instances over MCP by discovering, switching, and verifying the target instance before reads and writes.

Expert en informatique quantique avancée (Qiskit, Cirq, algorithms, error correction, DZ research)

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

CCXT multi-exchange crypto broker integration for better liquidity during after-hours capital shift

Plans and configures multi-tenancy on GKE, covering namespace isolation, RBAC planning, resource quotas, LimitRanges, network isolation, and cost allocation.

For questions about Light Protocol's SDK, smart contracts and Solana development, Claude Code features, or agent skills. AI-powered answers grounded in repository context via DeepWiki MCP.

Swap or bridge tokens across 54+ blockchains via the Symbiosis protocol, with automatic routing and support for any-to-any token swaps.

Work with Photon PUN2 real-time multiplayer and Nakama async challenges in QuizVerse.

Design, simulate, and run quantum circuits on Google Quantum AI hardware and partner backends using Cirq.

Quantize large language models to 4-bit precision using activation-aware weight quantization, reducing memory footprint and speeding up inference with minimal accuracy loss.

Implements Manifold-Constrained Hyper-Connections (mHC) using Doubly Stochastic Matrices to improve deep learning stability.

Build and modify UI screens, panels, popups, responsive layouts, and UI Toolkit documents in QuizVerse.

Reads related records across multiple sObjects in one GraphQL request, paginates related lists with cursors, and replaces overlapping @wire(getRecord) calls with a single cache-shared query.

Builds, simulates, and runs quantum circuits with Cirq, Google Quantum AI's framework for NISQ hardware, noise-aware low-level circuit design, and noise characterization. Use when targeting Google Quantum AI processors (Sycamore/Weber), designing noise-aware NISQ circuits, or running characterization experiments (randomized benchmarking, XEB). For IBM Quantum hardware and Qiskit Runtime prefer alterlab-qiskit; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.

AndonQ 腾讯云智能客服"领域虾" — 不切窗口、不排队，即刻获得腾讯云全产品线专业解答。支持工单查询（列表/详情/流水）、集团/MC 工单与需求单管理、腾讯云全产品线智能问答、云产品资源查询等。当用户查询工单、查看工单详情、咨询腾讯云产品问题、查询集团(360)工单/需求单、或查询腾讯云资源信息时使用。

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators.

Builds, transpiles, and runs quantum circuits with Qiskit, IBM's quantum computing framework, including Qiskit Runtime primitives (Sampler/Estimator), circuit transpilation, and error mitigation on IBM Quantum hardware. Use when targeting IBM Quantum backends, transpiling circuits, running Runtime sessions or batches, or applying resilience/error mitigation. For Google Quantum AI hardware and NISQ circuits prefer alterlab-cirq; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.

Quarkus 3.x LTS 测试驱动开发——JUnit 5、Mockito、REST Assured、Camel 测试及覆盖率

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.