「classification」の検索結果

Analyze WeChat Mini Program platform constraints and evidence layers for an idea or existing repository, including source configuration, build output, WeChat DevTools loading, device behavior, permissions, privacy declarations, cloud or backend linkage, upload, trial, review, and production status. Use when users ask about WeChat-specific configuration, project roots, compile paths, capability permissions, privacy compliance, official platform rules, upload or release readiness, or why source and platform behavior differ. Performs read-only evidence classification by default, verifies time-sensitive or high-risk claims against current official WeChat sources, redacts identifiers and secrets, and never upgrades one evidence layer into another.

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。

GPS-aligned genealogical research assistant for family history, ancestor research, record analysis, source-information-evidence classification, conflict resolution, citations, FAN research, privacy-sensitive document analysis, and proof statements, summaries, or arguments. Use for census, vital, probate, land, military, church, newspaper, DNA-plus-documentary, and other genealogy evidence tasks. Not for GEDCOM creation (use gedcom-creator), general history questions, DNA-kit shopping, or generic writing tasks.

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。

Applies fixes from a prior review-llm-artifacts run, with safe/risky classification. Respects verify-llm-artifacts output when present to skip false positives.

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。

ソフトウェアにおける非正常状態（Error, Defect, Fault, Failure）の分類と定義を提供する。 JIS規格・JSTQB・Bertrand Meyer等の複数の標準に基づき、各概念の違いを明確化し、 適切なエラー設計・障害対策の判断を支援する。エラー設計、障害分析、コードレビュー、 テスト設計時に用語の混乱を防ぎ、正確な分類に基づく対処戦略の選択に使用。 対象言語: 言語非依存。 トリガー：「ErrorとFaultの違い」「DefectとBugの関係」「障害と故障の区別」 「エラーの分類」「Failureとは何か」「非正常状態の設計」「エラー用語の定義」 「エラーと欠陥の違い」「faultとfailureの違い」 といったエラー分類・用語定義関連リクエストで起動。

Act as an end-to-end data scientist: turn business questions into defensible analysis, validated models, and decision-ready reports. Use whenever the user asks to analyze, explore, or profile a dataset or CSV/Parquet/Excel file; asks what drives a metric or why a number changed ("why did churn go up?"); wants to test whether a difference is real (A/B tests, experiments, "is this significant?", "how many samples do I need?"); wants a predictive model (churn, forecast, scoring, segmentation, classification, regression); asks to review an existing analysis, notebook, or model for flaws; or needs results written up for decision-makers. Triggers in any language ("phân tích dữ liệu", "xây model dự đoán", "kiểm định A/B"), even when they never say "data science" or "statistics".

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。

Generic update orchestrator for an already-deployed warp route. Reads a Linear ticket describing any combination of warp-fee changes / ISM changes / hook changes / owner-address changes / additional-collateral-chain additions, edits the registry deploy.yaml accordingly, builds a per-chain strategy file from the artifact-context owner classifications, runs `hyperlane warp apply`, fork-simulates the resulting receipts via `/warp-route-check`, and hands off to `/warp-update-propose` to land the proposals. Chain extension (adding a brand-new chain with new on-chain contracts) is a separate skill — see `/warp-update-extend`.

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。

Drafts a U.S. Consulting Services Agreement covering scope, compensation (hourly, fixed, retainer, hybrid), independent contractor classification, IP ownership, confidentiality, indemnification, liability caps, insurance, and dispute resolution. Use when drafting consulting contracts, professional services agreements, or independent contractor agreements.

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 the corp-finance-mcp server tools for specialty finance, regulatory, and compliance calculations. Invoke when performing private credit (unitranche, direct lending, syndication), insurance (loss reserving, premium pricing, Solvency II SCR), FP&A (variance analysis, break-even, working capital, rolling forecast), wealth management (retirement planning, tax-loss harvesting, estate planning), restructuring (recovery analysis, distressed debt), real assets (property valuation, project finance), venture capital (dilution, convertible instruments, fund returns), ESG (scoring, climate/carbon, green bonds, SLL), regulatory capital (Basel III, LCR/NSFR, ALM), compliance (MiFID II best execution, GIPS reporting), credit derivatives (CDS pricing, CVA/DVA), convertible bonds (binomial tree pricing, scenario analysis), lease accounting (ASC 842/IFRS 16, sale-leaseback), pension & LDI (funding analysis, liability-driven investing), sovereign risk (bond analysis, country risk), real options (binomial valuation, decision trees), equity research (SOTP, target price), commodity trading (spread analysis, storage economics), treasury management (cash management, hedge effectiveness), infrastructure finance (PPP models, concession valuation), crypto (token valuation, DeFi analysis), municipal bonds (pricing, credit analysis), structured products (notes, exotic), trade finance (LC, supply chain), fund structuring (US onshore, UK/EU, Cayman/BVI offshore, Luxembourg/Ireland), transfer pricing (BEPS/Pillar Two, intercompany pricing), tax treaty (treaty network optimization, holding structures), FATCA/CRS (reporting, entity classification), economic substance (multi-jurisdiction testing), regulatory reporting (AIFMD Annex IV, SEC Form PF, CFTC CPO-PQR), AML compliance (KYC risk scoring, sanctions screening), fund of funds (J-curve, commitment pacing, manager selection, secondaries pricing), bank analytics (NIM analysis, CAMELS rating, CECL provisioning, deposit beta, loan book), carbon markets (credit pricing, ETS compliance, CBAM, offset valuation, shadow carbon price), private wealth (concentrated stock, philanthropic vehicles, wealth transfer, direct indexing, family governance). All computation uses 128-bit decimal precision.

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。

Validates documentation completeness for prior authorization requests by checking a 10-item checklist covering patient information, provider credentials, insurance details, medical codes, clinical notes quality, NCCI bundling risk, and service type classification.

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。

Drafts a compliant Commercial Invoice for Export satisfying customs, banking (L/C), logistics, and insurance requirements. Enforces Incoterms 2020, HS tariff classification, country-of-origin determination, export control referencing, and certification language. Use when preparing export invoices for customs authorities, freight forwarders, banks, or insurance underwriters.

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 a proposed API change for breaking changes — classification and impact assessment. Use when asked "is this a breaking change", "will this break clients", or "assess the impact of this API change".

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。

Build an ML pipeline — from data to trained model to serving endpoint. Use when asked to "build ML model", "train a model", "prediction pipeline", "classification", or "regression".

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。

Provides incident response best practices covering severity classification, on-call rotation, war room protocols, runbook templates, escalation policies, and blameless postmortems. Use when handling an incident, setting up on-call, writing a postmortem, creating a runbook, configuring PagerDuty or OpsGenie, or building incident management processes.

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。

Naming and classifying organisms through binomial nomenclature, the Linnaean hierarchy, type specimens, and the rules governing taxonomic authority and revision. Covers the structure of a scientific name, the ranks from domain to subspecies, the codes (ICZN, ICN, ICNP), and the modern phylogenetic refinements that reshape the classical system. Use when the task is to place a known organism in its formal hierarchy or to reason about how names change over time.

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。

Rhythmic analysis, meter classification, groove mechanics, and cross-cultural rhythmic systems. Covers simple and compound meter, asymmetric meters, polyrhythm, polymetric structures, metric modulation, swing and groove analysis, syncopation patterns, hemiola, additive vs. divisive rhythm, African timeline patterns, Indian tala, and Messiaen's non-retrogradable rhythms. Use when analyzing rhythmic structure, identifying meter, studying groove, or working with non-Western rhythmic systems.

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。

Primary and secondary source analysis for historical reasoning. Covers source classification, sourcing (author/context/purpose), corroboration across multiple sources, contextualization within time and place, and bias detection. Use when evaluating historical evidence, assessing source reliability, or constructing evidence-based historical 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。

Stellar spectral analysis from first light to chemical abundance. Covers continuum emission and absorption, the OBAFGKM classification sequence, luminosity classes, line identification, Doppler shifts, curve-of-growth abundance analysis, and the astrophysical conclusions that follow from a spectrum. Use when classifying a star, measuring radial velocity, inferring composition or temperature, or teaching why the Sun is mostly hydrogen.

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。

Supervised and unsupervised learning, bias-variance tradeoff, cross-validation, decision trees, ensemble methods, neural network fundamentals, and the practitioner's workflow from problem framing through deployment. Covers classification, regression, clustering, dimensionality reduction, regularization, hyperparameter tuning, and evaluation metrics. Use when building predictive models, selecting algorithms, or understanding the machine learning 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。

Ionic, covalent, and metallic bonding, Lewis structures, VSEPR theory, molecular geometry, polarity, and intermolecular forces. Covers octet rule and exceptions, formal charge, resonance, sigma/pi bonds, orbital hybridization, electronegativity-driven bond classification, VSEPR electron-domain and molecular geometries, dipole moments, and the four intermolecular force types (London dispersion, dipole-dipole, hydrogen bonding, ion-dipole). Use when predicting molecular shapes, bond properties, or physical behavior from molecular structure.

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。

Balancing chemical equations, reaction classification, stoichiometric calculations, acid-base chemistry, oxidation-reduction (redox) reactions, and thermochemistry. Covers conservation of mass, mole ratios, limiting reagents, percent yield, Bronsted-Lowry and Lewis acid-base theory, pH calculations, oxidation states, half-reaction balancing, enthalpy, Hess's law, and calorimetry. Use when solving quantitative chemistry problems involving reactions, energy changes, or solution chemistry.

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。

Classify the information-need of a query and dispatch it to the appropriate retrieval or reasoning strategy. Use before read-side memory access, before multi-strategy retrieval, or any time you'd otherwise default to "one retriever for everything". Returns a strategy label, a token budget, and a retrieval depth so downstream handlers can be specialised. Backed by Pre-Route (arxiv 2605.10235v2) and MemFlow (arxiv 2605.03312v1), which together show LLMs possess latent routing ability elicitable via a structured prompt — and that externalising the routing decision improves small-model performance by ~2x. Triggers: "route this", "what strategy", "before retrieving", "intent classification", or any query whose ideal handling depends on what KIND of question it is.

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。

用户审计自己的内容结构占比、判断单条帖子传播上限、或困惑"发了感叹/观点帖没人理"时调用。 关键 trigger: "内容原型/content archetype""哪种内容容易爆/which content goes viral" "传播上限/viral ceiling""普通表达型/资源入口型/工具教程型/AI工具发现型" "为什么没人互动/why no engagement""内容方向有问题/content direction wrong"。 不适用于: 已确定写某种短内容类型并需要组织结构(用 x-short-content-craft)、 检查帖子五件套完备性(用 x-five-piece-checklist)、做账号定位取舍(用 x-positioning-tradeoff)。

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。

Run a custom computer-vision prompt against an image with a local vision LLM. Wraps kuzco's tool_llm_image_custom() ellmer tool. Use when none of the specialized kuzco image skills (classification, OCR, recognition, sentiment, alt text) fit the task.

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。

Query NCBI ClinVar for variant clinical significance. Search by gene/position, interpret pathogenicity classifications, access via E-utilities API or FTP, annotate VCFs, for genomic medicine.

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。