「ngs」の検索結果

Use when interpreting biological research findings, evaluating life science evidence, analyzing molecular or cellular mechanisms, comparing competing biological hypotheses, designing or critiquing experiments in biology, genetics, genomics, cell biology, immunology, neuroscience, ecology, or any life science domain. Triggers on questions about gene function, pathways, phenotypes, GWAS hits, single-cell data, animal models, clinical translation, evolutionary arguments, or any biology/life science reasoning task.

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Prioritize drug targets from a ranked gene list (e.g., scRNA-seq DE output) by orchestrating parallel API queries against UniProt, OpenTargets (with integrated DepMap CRISPR essentiality + gnomAD constraint), PubMed, the Human Protein Atlas (HPA), and ChEMBL tool compounds, then re-ranking by a composite score combining protein localization, druggability, disease genetics, tissue specificity (safety), focus-cell-type expression, CRISPR essentiality, LoF safety constraint, and research maturity. Use whenever the user wants to filter, triage, prioritize, or "do due diligence" on a list of candidate genes for drug discovery, especially after a DE / DEG analysis when they say things like "which of these should I follow up on", "filter for druggable targets", "make a target dossier", "rank these for tractability", "annotate these genes for druggability", or "build a target report". Trigger even when the user says just "filter these candidate genes" or hands over a CSV from a DE 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。

Use when interpreting research findings, evaluating scientific evidence, analyzing mechanisms, comparing competing hypotheses, designing experiments, or constructing scientific arguments.

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。

Evaluates ambient context artifacts (CLAUDE.md, memory, local skills, settings hooks) for compatibility with swarm governance. Returns a classified report so users can address interference before launching a team.

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。

Independent review loop run before delivery in code work. An independent reviewer (Codex, or fresh Codex-style subagents) reads the whole PR against the approved outcome; the lead fixes in-scope functional findings and re-reviews until none remain. Its differentiator is independence and exhaustiveness — a reviewer that fails differently from the authors, run to clean — distinct from the recursive-refinement ladder. Invoked by the team lead from the unified pre-ship gate (code-mode and /swarm:refine) after the ship steps.

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。

Resolves stuck review findings via a put-up-or-concede exchange. Invoked by the facilitator when a finding survives arbitration without new evidence.

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。

Servd (servd.host) — Craft-specialised managed hosting for Craft CMS. Covers git push-to-deploy with the optional servd.yaml build config, local → staging → production environments with uni-directional Project Config sync, the servd/craft-asset-storage plugin (S3-backed Flysystem volumes on the svdcdn.com CDN, off-server image transforms, Imager-X/ImageOptimize integrations), Servd's static caching (full vs tag-based purge, {% dynamicInclude %}, CSRF injection, cache-busting) and running Blitz alongside it in reverse-proxy mode, MariaDB/MySQL databases over an SSH tunnel, automatic + manual backups, the Dedicated Queue Runner, environment variables and secrets, the ephemeral load-balanced filesystem (Redis + remote volumes for runtime files), plugin/feature constraints, and Servd-vs-Craft-Cloud differences.

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。

한국 스타트업·1인 법인 대표·프리랜서·개인사업자를 위한 장부 자동 생성 진입점 스킬. 호출 시 5개 하위 스킬(jangbu-import·jangbu-tag·jangbu-tax·jangbu-dash·jangbu-jongso)을 번호·문자 메뉴로 제시하고, 입력 즉시 해당 스킬 인터뷰로 직행한다. 엑셀·5대 은행 CSV·7대 카드사 명세서 PDF·영수증·세금계산서 지원, macOS Vision/PaddleOCR 로컬 처리, Level 2 민감정보 마스킹.

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。

한국 종합소득세·법인세 신고 준비를 위한 서류 체크리스트 자동 생성 스킬. 개인사업자(일반·간이·면세)·프리랜서·1인 법인·겸업·성실신고확인대상 5가지 유형별로 필요 서류 목록을 제공하고, korean-jangbu-for에서 자동 생성 가능한 항목을 표시한다. 2026년 기준 기한표(토·일 자동 이연 반영) 포함 — 종소세 일반 2026-06-01, 성실신고 2026-06-30.

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 an implementation against its plan with a hostile peer agent, debate findings to consensus, and drive fix waves until the auditor runs dry. Use when a done-claim needs verification the implementer cannot game ("hostile review", "adversarial audit", "is this PR faithful", "find the escape hatches") — the loop that beats the laziness bias with its own game theory.

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 AI-generated writing patterns in developer text — docs, docstrings, commit messages, PR descriptions, and code comments. Use when reviewing any text artifact for authenticity and clarity, or when the user mentions ai writing, ai-generated or robotic writing, text that sounds like AI or ChatGPT, or writing quality. Builds on the docs-style core writing principles.

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。

Confirms or rejects findings from review-llm-artifacts before deletes or risky refactors. Loads review-verification-protocol-style checks per finding. Use after a review run, when the user wants to reduce false positives, before fix-llm-artifacts on dead code, or when validating a full-project scan.

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。

Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.

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。

Explanation documentation patterns for understanding-oriented content - conceptual guides that explain why things work the way they do. Use when writing an explanation doc, conceptual guide, understanding/background doc, design rationale, or architecture explanation, or when asked how/why something works. Builds on the docs-style core writing principles.

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。

Repo-wide structural-maintainability review — code-judo restructurings, 1k-line file guard, anti-spaghetti branching, canonical-layer enforcement, anti-magic abstractions, explicit type/boundary contracts.

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。

Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when selecting models, implementing resilience, or optimizing API calls.

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Use when the user wants web research: gathering cited, multi-angle evidence on a specific question. Triggers on: "research X for me", "do web research on", "look up sources for", "find citations for", "gather evidence on", "what does the web say about X". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups ("find this function", "search the repo"), local file search, LLM-as-judge evaluation, or paywalled/auth-gated scraping. Produces a written plan, parallel-subagent findings, and a cited synthesis report on disk — never inline prose, never unsourced claims.

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。

Mandatory verification steps for all code reviews to reduce false positives. Load this skill before reporting ANY code review findings.

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 the user wants a cited, structured read of local documents and project knowledge. Triggers on: "analyze these docs", "scan my project for context", "read the docs folder", "summarize what's in .beagle/concepts/", "extract context from docs/", "what's in this folder", "go read everything in X and tell me what's there". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups ("find this function", "search the repo"), web research (use web-research), LLM-as-judge evaluation (use llm-judge), or document editing (use humanize-beagle). Produces a written scan plan, parallel-subagent findings, and a cited synthesis report on disk — never inline prose, never unsourced claims.

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。

Dependency vulnerability remediation workflow for this repository. Use when fixing CVE, BDSA, GHSA, OSV, npm, PyPI, Dependabot, Black Duck, Snyk, or other package vulnerability findings, especially when the user asks for minimal package-only updates, validation, commits, branches, or pull requests.

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Reserved-field rules and field-number lookup for evolving AppSettings, plus the Rust/Kotlin diagnostics wire contract. Use before assigning or removing a proto field. DataStore mapping: protobuf-datastore.

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。

Klare, überprüfbare Website-Texte für eine definierte Zielgruppe entwerfen und überarbeiten. Nutze diesen Skill für Landingpages, Startseiten, Produkt- und Preisseiten, Überschriften, Handlungsaufforderungen, Nachweisabschnitte und die Überarbeitung vorhandener Texte. Führt ein Aussageverzeichnis, verbindet Fähigkeit, Wirkung und Beleg, erhält Einschränkungen statt sie zu glätten und verzichtet auf falsche Dringlichkeit, erfundene Referenzen und manipulative Muster. Achtet auf Anrede, Preisangaben, Rechte an Zitaten und Logos sowie Barrierefreiheit. Standard ist ein Entwurf im Chat, keine Veröffentlichung.

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Kundenforschung datensparsam und einwilligungsorientiert planen, durchführen und auswerten. Nutze diesen Skill für Interviewleitfäden, Umfragen, Usability-Tests, die Auswertung vorhandener Gespräche, Support-Tickets oder Bewertungen, und für Personas, Segmente und Jobs-to-be-Done. Klärt vorab Zweck, Rechtsgrundlage, Einwilligung, Aufzeichnung, Pseudonymisierung und Aufbewahrung, wertet nur innerhalb des Stichprobenrahmens aus und trennt Befund von Entscheidung. Beachtet DSGVO, BDSG und Beschäftigtendaten; Österreich und Schweiz werden getrennt behandelt.

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Ein evidenzbasiertes, tragfähiges Content-Portfolio für Zielgruppen, Geschäftsziele, Distribution und die real vorhandene Produktionskapazität planen. Nutze diesen Skill für Content-Strategien, Themenfelder, Redaktionspläne und Backlogs, für die Diagnose eines bestehenden Contentbestands, für die Abbildung von Kauf- und Nutzungswegen und für Entscheidungen zu CMS und Governance. Priorisiert offen nach Nachfrage, Aufwand und Evidenz, schützt vor dünnen Massenseiten und benennt Belegklassen. Einzelne Texte schreibt copywriting, die technische Prüfung macht seo-audit.

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。