672 件 ・ 関連度順
概要と使いどころ
"Run conjoint analysis to measure how product attributes drive consumer preferences and willingness to pay. Use this skill when the user needs to quantify feature value trade-offs, estimate willingness to pay for specific features, or optimize product configuration — even if they say 'which features do customers value most', 'willingness to pay for feature X', or 'product attribute trade-offs'.".
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。
Application-level business logic security testing for any domain. Takes an understanding-first approach: map the intended workflows before probing them. Covers: value/quantity logic abuse (negative, zero, overflow, rounding on any numeric field), workflow and state machine bypass (skipping required steps, forcing illegal state transitions, reusing one-time tokens), trust boundary violations (BOLA horizontal/vertical, BFLA, cross-tenant access, negative ownership attacks), idempotency and replay attacks (duplicate submissions, double-spend, same-reference reuse), multi-step flow integrity (checkout, registration, approval, verification), quota and rate limit bypass, time/date manipulation, and authorization code / reference number predictability. Domain-agnostic — applies to SaaS, e-commerce, banking, gaming, social platforms, APIs, or any multi-user application with stateful workflows. Chains from /pentester; chains into /param-fuzz when boundary violations or mass assignment are confirmed.
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。
Qdrant vector database -- collection management, point operations, payload filtering, named vectors, quantization, recommendations, snapshots
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。
Tunes noisy detections by analyzing historical alert data to quantify false-positive sources, recommend allow-list filters and threshold adjustments, and measure precision impact. Activates for requests to tune a detection, reduce false positives, or analyze alert noise and recommend filters.
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。
Pulp musical/media time primitives, exact beat divisions, tempo and meter maps, transport-range grid projection, inline and order-preserving groove projection, coordinate randomness, streaming cursors, and quantization arithmetic.
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 a feature or sprint for scope creep by comparing current scope against the original plan. Flags additions, quantifies bloat, and recommends cuts. Use when user says 'any scope creep', 'scope review', 'are we staying in scope'.
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 a task needs the judgment of a CNC Tool Operator — diagnosing a dimension trending toward its tolerance limit across consecutive parts before it actually crosses, deciding whether to apply a tool wear offset or flag the tool for replacement, evaluating whether a failed part traces to work-holding repeatability versus a program or tool issue, or verifying a setup change with a first-article inspection before running production quantity.
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 a task needs the judgment of a Cargo Inspector — reconciling a vessel draft survey against a shore tally within IMO tolerance, calculating outturn quantity from tank ullage and temperature readings under API MPMS, verifying dangerous-goods segregation against the IMDG Code, checking a load's height and width against a route's bridge and tunnel clearances before departure, or documenting cargo condition and filing a letter of protest before custody transfers.
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 a task needs the judgment of a central bank governor — setting a policy rate decision against a dual mandate, deciding whether a distressed financial institution needs liquidity support or resolution, calibrating forward guidance language against credibility risk, weighing quantitative easing or tightening at the effective lower bound, or drafting the public communication that accompanies a policy decision.
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 a task needs the judgment of a Civil Engineering Technician — running and interpreting a concrete field acceptance test (slump, air content, cylinder breaks against ACI 318 criteria), verifying soil compaction against a Proctor density curve, reconciling a concrete or rebar quantity takeoff against a pay application, or documenting a field condition that deviates from the approved plans for the engineer of record.
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。
Iterative measurement-driven improvement loop. Measure, profile, mutate, re-measure, commit. Works for performance, bundle size, complexity, test coverage — anything quantifiable. Use when the user wants to systematically improve a metric through repeated cycles of profiling and targeted changes.
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。
Practical computational and experimental chemistry workflows — cheminformatics, quantum chemistry, kinetics, and analytical methods.
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 resume builder or optimization tool for ATS compatibility, keyword matching accuracy, formatting standards, achievement quantification, skill extraction, and job-description alignment scoring. Use when reviewing resume software, career platforms, applicant tracking integrations, CV generators, or job application tools.
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。
Quantify cyber risk using FAIR methodology with Monte Carlo simulation, assess control effectiveness against NIST CSF/CIS/ISO 27001 frameworks, evaluate risk appetite alignment, and analyze cyber insurance coverage adequacy..
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 QA quality dashboards, calculate defect metrics, analyze escape rates, and produce quality trend reports. Use this skill whenever a QA lead or manager needs to measure and communicate quality outcomes. Trigger on phrases like "quality metrics", "defect density", "escape rate", "bug trends", "quality dashboard", "sprint quality report", "test coverage metrics", "QA KPIs", "how is quality trending", "defect leakage", "production bugs this quarter", "mean time to detect", "quality scorecard", or any request to quantify, visualize, or report on the quality of a product or testing process. Also trigger when a manager asks "how is QA performing?" or an engineering lead asks "what does our defect data tell us?".
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。
Classical and modern physics expert covering mechanics, electromagnetism, thermodynamics, quantum mechanics, and relativity
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。
Tune moflo's memory stack for speed, RAM, and index quality. Covers HNSW parameters (M, efConstruction, ef), vector quantization, batch operations, and common bottlenecks. Use when scaling past ~100k entries or when search latency regresses.
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。
Academic research assistant — literature review + methodology (quant/qual) + paper outline (IMRaD) + citation + research gap analysis
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。
Checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Validates decisions via MCP Ref. Reports with SEC-/PERF-/MNT-/ARCH-/BP-/OPT- prefixes.
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 adversarially reviewing a document that makes formal or technical claims — math derivations, physics papers, statistical analyses, benchmark reports, whitepapers. Inventories every equation and quantitative claim, verifies each AS NAMED in the text (never a paraphrase or a neighboring statement), and classifies VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS. Triggers on "check this paper", "verify these claims", "is this derivation right", "review this proof", "audit this benchmark", "does the math hold up". For source-code review see code-review-and-quality; for skill/agent library audits see skill-library-review; for content quality scoring see content-ops.
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。
Scientific research engine for hypothesis testing, literature gap analysis, experimental validation, and data-driven discovery. Enforces adversarial review (Reviewer 2), 32 quality gates, tree search over hypotheses, confounder harness for quantitative claims, and serendipity detection. TRIGGER when: user asks to analyze scientific data, test hypotheses, validate findings, search for research gaps, design experiments, or investigate results. DO NOT TRIGGER when: pure code review, documentation writing, devops tasks, general conversation, or non-scientific data transformation.
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。
Train an ML model in the QuantConnect ML-Training-Pipeline with thermal-safe GPU usage and rigorous validation. Arguments: <architecture|script> [--dry-run] [--seeds 0,1,7,42,99] [--folds 5] [--bg]
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。
Execute iterative improvement workflow for QuantConnect strategies. Arguments: [strategy|issue#] [--iterations=N] [--no-backtest] [--commit]
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。
DiT 计算模块（L3）：把**已定位的 DiT 计算瓶颈**落成特性级选档与实施—— 量化档（W8A16 / W4A16 / W8A8 系列 / W4A4 / MXFP8 / FA 量化）、稀疏（rf_v2 / ada_bsa）、 缓存（DiTCache / AttentionCache / 时间步优化）、编译启用（MindieSDBackend / Pattern 融合 / ACLGraph） 的**开不开、开哪一档、怎么开、怎么复验**；依据是 `docs/zh/features/*`（特性真源）+ framework-integration/references/framework-support-matrix.md（支持状态）。 即使用户只说"这个模型怎么加速""量化/稀疏/Cache 怎么选怎么开""要不要开量化、开哪一档""这个档位开了有没有效果" 而未提 profiling，也应触发。 **入口条件**：瓶颈点已明确（用户带一句实测锚点，或编排层交付标签）时由域入口 `performance-optimization` 按标签分发到本技能；**瓶颈未明（"怎么加速 / 跑通 / 采 profile"）先走 `model-auto-optimization` 定位**，不在本技能内做占比分析。 near-miss：多卡并行形态 / 通信掩盖 / TP·offload 选型 → `dit-parallel-opt`；VAE 解码段与 host 固定开销 → 各自模块（VAE / host）；单算子实现级实测选型（mindie_bench）→ `benchmark-dev`； 需要新增 pattern / 算子才能落地本档 → `pattern-dev` / `operator-dev`；框架侧开关与使能验证 → `framework-integration`；量化器位级契约与精度对齐（编码公式 / 舍入 / scale 粒度）→ `quantization-dev`；精度验收判据 → `accuracy-gate`；数字入库口径 → `perf-gate`。
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。