「que」の検索結果

Queries 20+ bioinformatics resources through CLI/Python. Supports quick lookups of gene info, BLAST/BLAT, viral sequence downloads, PDB/mmCIF structures, G2P residue annotations, enrichment analysis, OpenTargets, COSMIC, CELLxGENE, and 8cube mouse specificity/expression data. Best for interactive exploration and simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.

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Predicts regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene symbol, a genomic region, or a DNA/FASTA sequence and wants any of these predictions, mentions Genomic Intelligence, genomicintelligence.ai, api.genomicintelligence.ai, or mcp.genomicintelligence.ai.

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Create source-grounded Chinese-English paper readers with aligned text, figures, tables, and equations. Use for 全文翻译、中英文对照、论文精读 or source-linked questions about a paper; respect a requested excerpt or question without generating a full reader.

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Prepares the user for a specific interview from their real experience. Builds a story bank in Situation/Task/Action/Result/Reflection form mapped to the competencies the role and company test (such as Amazon's Leadership Principles), writes a cited company and role brief from public sources, predicts questions per round, drafts opener, why-us, weakness and salary answers, prepares questions to ask and a logistics checklist, and runs a post-interview debrief. Use when the user says "help me prepare for my interview", "I have an interview tomorrow" or "in 2 hours", "build my story bank", "STAR stories", "interviewing as a career changer", "what will they ask me", "how do I answer tell me about yourself", "questions to ask the interviewer", "research the company" or "debrief my interview". Uses Reactive Resume MCP tools when connected. For scored role-play practice, mock-interview; for thank-you notes and tracking, job-application-manager; for a salary number, offers or negotiation, offer-negotiation.

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Python background job patterns including task queues, workers, and event-driven architecture. Use when implementing async task processing, job queues, long-running operations, or decoupling work from request/response cycles.

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Understand anti-reversing, obfuscation, and protection techniques encountered during software analysis. Use this skill when analyzing malware evasion techniques, when implementing anti-debugging protections for CTF challenges, when reverse engineering packed binaries, or when building security research tools that need to detect virtualized environments.

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Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.

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CommunityToolkit.Mvvm Messenger pub/sub for decoupled communication between ViewModels (or any objects). Covers WeakReferenceMessenger vs StrongReferenceMessenger, IRecipient<TMessage>, RequestMessage<T> / AsyncRequestMessage<T> / CollectionRequestMessage<T>, ValueChangedMessage<T>, channels (tokens), and the ObservableRecipient activation lifecycle. Use across WPF, WinUI 3, .NET MAUI, Uno, and Avalonia.

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Create, update, and manage GitHub issues using MCP tools. Use this skill when users want to create bug reports, feature requests, or task issues, update existing issues, add labels/assignees/milestones, manage repository labels, set issue fields (dates, priority, custom fields), set issue types, manage issue workflows, link issues, add dependencies, or track blocked-by/blocking relationships. Triggers on requests like "create an issue", "file a bug", "request a feature", "update issue X", "set the priority", "set the start date", "create a label", "rename a label", "list repo labels", "link issues", "add dependency", "blocked by", "blocking", or any GitHub issue management task.

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Security hardening reviewer for GitHub Actions workflow files (.github/workflows/*.yml). Reasons about the Actions threat model that pattern matchers and general code linters miss — untrusted-input script injection, privileged triggers running fork code, mutable action references, and over-scoped tokens. Use this skill when asked to review, audit, harden, or secure a GitHub Actions workflow, when writing a new workflow, or for any request like "is this workflow safe?", "review my CI for security issues", "why is pull_request_target dangerous here?", "pin my actions", or "lock down GITHUB_TOKEN permissions". Covers script injection via ${{ }} interpolation, pull_request_target / workflow_run privilege escalation, SHA-pinning of third-party actions, least-privilege permissions, GITHUB_ENV/GITHUB_OUTPUT injection, secret exposure, OIDC over long-lived credentials, and self-hosted runner exposure on public repositories.

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Creates and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on Arize. Applies human annotations to project spans via the Python SDK. Use when the user mentions annotation config, annotation queue, label schema, human feedback, bulk annotate spans, update_annotations, labeling queue, annotate record, or human review.

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Prepare for due diligence meetings — management presentations, expert network calls, customer references, and advisor sessions. Generates targeted question lists, benchmarks to reference, and red flags to probe. Use before any diligence meeting or call. Triggers on "prep for management meeting", "diligence call prep", "expert call questions", "customer reference questions", or "meeting prep for [company]".

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For external plan request scenarios, guides the Agent to request a clear, actionable, step-by-step plan from a stronger Agent via list_agents and chat_with_agent, emphasizing that the plan is executed by the requester, not by the consulted Agent.

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Detect Kerberos Pass-the-Ticket (PtT) attacks by analyzing Windows Event IDs 4768, 4769, and 4771 for anomalous ticket usage patterns, with detection queries for Splunk and Elastic SIEM. Use when investigating incidents involving stolen or replayed Kerberos tickets, building detection rules or threat hunting queries for ticket abuse, or validating SOC monitoring coverage for credential-theft attack techniques.

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Detects and analyzes process injection techniques used by malware including classic DLL injection, process hollowing, APC injection, thread hijacking, and reflective loading. Uses memory forensics, API monitoring, and behavioral analysis to identify injection artifacts. Activates for requests involving process injection detection, code injection analysis, hollowed process investigation, or in-memory threat detection.

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Detect data exfiltration via DNS tunneling (tools like iodine, dnscat2, dns2tcp) by analyzing query entropy, subdomain length, query volume to single domains, TXT/CNAME/NULL record abuse, and oversized response payloads using passive DNS monitoring and statistical/ML methods. Use when hunting for covert DNS-based data exfiltration or building a passive DNS anomaly detection capability.

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Detects defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.

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Analyzes Windows Security, System, and Sysmon event logs in Splunk to detect authentication attacks, privilege escalation, persistence mechanisms, and lateral movement using SPL queries mapped to MITRE ATT&CK techniques. Use when SOC analysts need to investigate Windows-based threats, build detection queries, or perform forensic timeline analysis of Windows endpoints and domain controllers.

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Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.

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Uses the Linux Audit framework (auditd) with ausearch and aureport utilities to detect intrusion attempts, unauthorized access, privilege escalation, and suspicious system activity. Covers audit rule configuration, log querying, timeline reconstruction, and integration with SIEM platforms. Activates for requests involving auditd analysis, Linux audit log investigation, ausearch queries, aureport summaries, or host-based intrusion detection on Linux.

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Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.

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Answer questions using the brain's knowledge with 3-layer search, synthesis, and citation propagation. Use when the user asks a question, wants a lookup, or needs information from the brain.

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Poll and rank open GitHub issues, RFCs, and pull requests for maintainer work, or start one explicitly selected item. Use when a user asks what to work on, requests backlog priorities, says "poll work," wants actionable issues or pull requests, or says "start

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Draft a personalized outreach email or multi-touch sequence to a prospect, create it as an email draft for review, and add the contact to a sequence in your sales engagement tool when asked. Use when the user asks to "draft outreach to [person/company]", "write a cold email to [prospect]", "re-engage [prospect]", "draft a 3-touch sequence", or "reach out to [person]".

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。