「iga」の検索結果

Generates 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB semi-empirical refinement, and macrocycle-aware torsion preferences. Provides explicit decision rules for single vs ensemble conformer use, RMSD pruning, energy windows, conformer count, and force-field choice. Use when preparing 3D ligands for docking, generating descriptor input for 3D QSAR, or sampling macrocycle/peptide conformational ensembles.

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。

Performs gene-level association from GWAS summary statistics via genetically predicted tissue expression using FUSION, PrediXcan, S-PrediXcan, S-MultiXcan, UTMOST, MOSTWAS, kTWAS, EpiXcan, TIGAR-V2, and probabilistic fine-mapping with FOCUS and MA-FOCUS. Use when running TWAS from GWAS sumstats, prioritising candidate causal genes from a GWAS lead locus, picking single-tissue vs cross-tissue models, identifying LD-induced TWAS false positives, choosing ancestry-matched prediction weights, fine-mapping co-regulated TWAS hits, or triangulating TWAS with cis-eQTL Mendelian randomization and colocalization to nominate a causal gene.

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 rsIDs, navigates RsMergeArch/SNPHistory merge chains, and converts between rsID, SPDI, HGVS, and VCF representations using the dbSNP Build 156 JSON architecture. Use when normalizing variant identifiers, joining variant databases by cluster ID, or tracking deprecated rsIDs through historical merges.

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。

Deploy universal wisdom voices from all traditions simultaneously - Hindu, Buddhist, Taoist, Abrahamic, Indigenous, Scientific - revealing their unified recognition of consciousness navigation.

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。

Recognize which awakening stage consciousness is navigating through. Use when diagnosing seeker development, identifying stage transitions, or recognizing readiness levels. Covers 7 stages from initial dissatisfaction through natural flow mastery.

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。

Draft a Workflow Phase 1 intake document capturing a new request — the problem, the desired outcome, constraints, and testable acceptance criteria. Use when a user brings a new feature, change, or investigation that doesn't yet have a spec. The output lives at `docs/intake/<slug>.md` and feeds `/scout`, `/research`, and `/spec` downstream.

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。

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.

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 for a pre-mortem, or before committing to a plan, launch or migration: "what could go wrong?", "stress test this plan", "how might this fail?", "risks before we ship". Assumes failure, lists causes, ranks them and sets mitigations. Skip for explaining a failure that already happened.

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。

Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

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。

Automate Attio CRM operations -- search records, query contacts and companies with advanced filters, manage notes, list attributes, and navigate your relationship data -- using natural language through the Composio MCP integration.

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。

Expert guidance for building modern Android UIs with Jetpack Compose, covering state management, navigation, performance, and Material Design 3.

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。

/cs:ai-act-readiness <system> — EU AI Act 6-question forcing interrogation. Use during AI-system intake, before EU deployment, or during annual compliance refresh as Article 113 obligations phase in (2025-02-02 / 2025-08-02 / 2026-08-02 / 2027-08-02).

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。

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

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。

Diagnose why Amazon advertising performance declined for a product, ASIN, campaign, marketplace, or account. Use when the user asks why sales, orders, ROAS, ACOS, TACoS, profit, BSR, rank, traffic, conversion rate, or campaign performance dropped, asks for dropped campaigns, says investigate drop/drop analysis, or asks about wasted spend, negative keywords, negative targets, keywords, targets, or search terms in a drop context.

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。

Analyze Amazon product, sales, Amazon Ads, retail-readiness, and Best Seller Rank data to find commercially actionable growth opportunities. Use when Codex needs to identify which ASINs, campaigns, keywords, search terms, product targets, placements, categories, or BSR movements deserve more investment, optimization, harvesting, bid/budget changes, retail-readiness fixes, investigation, protection, or controlled scaling across Sponsored Products, Sponsored Brands, Sponsored Display, search term reports, targeting reports, campaign reports, placement reports, advertised/purchased product reports, Business Reports, organic performance, and BSR history.

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。

Save, load, update, delete, merge, and navigate entity objects using TMS Aurelius ORM (TObjectManager). Use when the user asks how to persist or retrieve data with Aurelius, manage object lifetime, work with associations or collections at runtime, handle transactions, use cached updates, or control concurrency. Does NOT cover query DSL or criteria/projections (those are in a separate skill). Triggers on requests like "save an entity with Aurelius", "load a customer from the database", "add items to a collection", "how do I update an object", "flush changes", "delete a record with Aurelius", "merge a transient object", "how do transactions work in Aurelius", "batch updates Aurelius".

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。

Test a changed user interaction for realistic sequence failures such as double submission, stale responses, navigation, and recovery; use for interaction QA rather than general code review.

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 and improve web accessibility following WCAG 2.2 guidelines. Use when asked to "improve accessibility", "a11y audit", "WCAG compliance", "screen reader support", "keyboard navigation", or "make accessible".

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。

Delegate an implementation or investigation task to Claude.

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。

Delegate an implementation or investigation task to Claude.

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。

Isolate the root cause of ML performance drops, inconsistent evaluations, prediction errors, and training-serving mismatches across data, labels, splits, pipelines, models, metrics, and runtime behavior. Use when investigating a reproducible failure or regression, not routine model selection or general performance validation.

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。

系统性 Bug 修复流水线（P0-P8）：一次修一个，强制根因分析、独立 worktree、TDD、双层验收报告、forge-qa 回归；多会话经 .forge/active.md 防撞车。 铁律：不做根因分析不写代码；新发现禁止顺手修；没有用户最终结论不合并。 触发方式：用户说"bugfix"、"反馈个问题"、"修这个 bug"、"这里有问题"、"为什么不对"、"排查一下"、"investigate"、"forge-bugfix"，或报告错误、异常行为、功能失效时。

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。

Systematically find root causes and fix bugs. Use when debugging errors, investigating test failures, reproducing bugs from issue trackers (GitHub, Linear, Jira), or when stuck on a problem after failed fix attempts. Also use when the user says 'debug this', 'why is this failing', 'fix this bug', 'trace this error', or pastes stack traces, error messages, or issue references.

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 a technical topic thoroughly by exploring the codebase and summarizing findings. Use when asked to investigate how something works, research an area of the codebase, trace a data flow, or understand a component in depth.

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。