Production QA gate for Blender assets using viewport screenshots, validation checklists, naming audits, and ship/no-ship verdicts via MCP.
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。
877 件 ・ 関連度順
概要と使いどころ
Production QA gate for Blender assets using viewport screenshots, validation checklists, naming audits, and ship/no-ship verdicts via MCP.
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。
Apply the bioengineering, mechanobiology, and lymphatic transport reasoning of J. Brandon Dixon, professor of mechanical and biomedical engineering at Georgia Institute of Technology. Reach for this skill whenever analyzing lymphatic biomechanics, active vessel contractility versus passive drainage, peristaltic fluid transport, microfluidic organ-on-a-chip design, preclinical lymphedema models, non-invasive functional imaging, targeted nanomedicine delivery, or automated disease staging. Use this skill to critique bioengineering assumptions, guide quantitative protocol design, evaluate biomechanical pump failure, and formulate interdisciplinary biomedical solutions.
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 the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.
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。
Generate a self-contained, beautifully styled HTML analysis of an academic paper. Use when the user provides an arXiv link, paper URL, PDF, or asks to analyze a research paper. Produces a standalone HTML file with structured sections (Problem, Translation/Analogy, Architecture, Key Results, Verdict), embedded figures, and responsive design. Trigger words include 读论文, 分析论文, paper analysis, paper 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。
Investigate a Rezolus performance recording (.parquet, .rez, .dendro) through the rezolus MCP server. Discovery before query, verdicts and marks written back, links to the viewer.
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。
Brand-aware Word engine. Use to (1) EXTRACT a company's brand from a Word template into a reusable "Brand Profile", (2) COMPREHEND the template with the model (optional), (3) VERIFY it, (4) GENERATE new on-brand .docx documents FROM a saved profile. Trigger on "extract our brand", "learn/match this template", "use our brand kit", "generate a branded report from our profile", or when a ./brand-kit exists. For one-off Word edits with NO saved brand profile, use the docx skill instead. NOT for .pptx (brand-pptx), .xlsx (brand-xlsx), or PDFs.
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。
Brand-aware PowerPoint engine. Use to (1) EXTRACT a company's brand from a .pptx template into a reusable "Brand Profile", (2) COMPREHEND the template with the model (optional), (3) VERIFY it, (4) GENERATE a new on-brand .pptx from an IntermediateDocument. Trigger on "extract our brand", "use our deck template", "generate a branded deck from our profile", or when a ./brand-kit exists. For one-off slide edits with no saved brand profile, use the normal pptx skill instead. NOT for .docx (brand-docx), .xlsx (brand-xlsx), or PDFs.
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。
Brand-aware Excel engine. Use to (1) EXTRACT a company's brand from a .xlsx template into a reusable "Brand Profile", (2) COMPREHEND the template with the model (optional), (3) VERIFY it, (4) GENERATE a new on-brand .xlsx from a GridDocument fill manifest. Trigger on "extract our brand", "use our workbook template", "generate a branded workbook from our profile", or when a ./brand-kit exists. For one-off spreadsheet edits with no saved brand profile, use the normal xlsx skill instead. NOT for .docx (brand-docx), .pptx (brand-pptx), or PDFs.
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。
Hardware verification tool for checking functional equivalence between two RTL designs (Verilog). Use when users need to: (1) Verify if two RTL versions are functionally equivalent, (2) Compare original vs. refactored RTL code, (3) Validate design changes or optimizations, (4) Identify semantic vs. cosmetic differences, (5) Generate counterexamples for non-equivalent designs. Analyzes interface alignment, state variables, logic differences, and produces detailed equivalence verdicts with plain language explanations. Particularly effective for design verification, code reviews, and regression testing of RTL modifications.
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。
Push interfaces past conventional limits with technically ambitious implementations. Whether that's a shader, a 60fps virtual table, spring physics on a dialog, or scroll-driven reveals — make users ask "how did they do that?"
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 Next.js to Cloudflare Workers via the OpenNext adapter (@opennextjs/cloudflare). Use for SSR/ISR/SSG/App or Pages Router, getCloudflareContext, bindings (D1/R2/KV/AI/Hyperdrive), caching tiers, skew protection, multi-worker, custom worker, env vars, or worker size/runtime/keep_names/FinalizationRegistry/connection-scoping errors.
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 the weak-agent adversarial test harness against docx-cli. Spawns weak exercise agents (Haiku by default, Sonnet to probe, or a local agent harness's pre-produced runs) to perform real document tasks over six scenarios — five editing (MNDA form-fill + font fidelity, invoice table-edit/restructure + logo replace, résumé styling, contract redlining + commenting, contract finalize via accept/reject + comment reply/resolve) and one authoring (T. S. Eliot poetry journal: multi-column, verse, footnotes, links, figure) — renders every result with Word, has opus judge them against ground-truth rubrics, measures each exercise's tool economy, token cost, wall-clock, and correctness (from transcripts for Claude, the exercise.json ledger for the local harness), and synthesizes a prioritized ergonomics report. Use when the user says 'adversarial review', 'test docx-cli with weak agents', 'run the haiku harness', 'weak agent test', or wants to re-run yesterday's adversarial process.
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。
Verify the accuracy of claims and statements by extracting individual assertions, identifying authoritative sources, cross-referencing evidence, and assigning confidence-scored verdicts. Use when the user requests fact checking or provides relevant inputs for this workflow.
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。
Determine the TRUE cause of a failed retort run before attributing it. Ground-truth every failure (run its tests, read its agent logs, inspect its workspace) and classify it as an infrastructure false-fail, a genuine model miss, or an environment issue — never trust the gate verdict or a log signature alone. Use whenever a run is recorded failed (test_coverage=0 / gate fail), a pass rate looks low, or you're deciding whether a "failure" is real before reporting or proceeding.
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。
Post-event analyst note (conferences, KOL events, site visits) with the professional note anatomy — headline verdict, per-stock takeaways with model numbers, KOL distillation, cross-trial comparison lattices, modeled deltas vs consensus (peak × POS), three what's-changed vectors, risk bullets, and materiality-rated conflicting views. Use after any med event to convert the event into actionable takeaways.
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。
Think and work like an expert Galactic Astronomer. Use when a task calls for Galactic Astronomer judgment. Reasons from distance ladders, dust extinction, and survey selection functions through Gaia DR3 cross-matches, isochrone and Bayesian SFH fitting (PARSEC/MIST, Starfish), and orbit integration in named potentials (McMillan17, MWPotential2015) via galpy, Agama, and Gala, while treating parallax-S/N and RUWE failures, unresolved binaries and fiber collisions, dust-or-crowding overdensities, and spiral-arm-mimicking-streams as first-class failure modes.
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。
Think and work like an expert Epidemiologist. Use when a task calls for Epidemiologist judgment. Reasons from person-time, transmission dynamics, and population case definitions through epidemic curves, DAGs, renewal and SEIR models (EpiEstim, deSolve), SaTScan clustering, and STROBE/ORION/GRADE standards while treating confounding, collider stratification from test-positive conditioning, reporting-delay and testing-intensity artifacts, and superspreading overdispersion as first-class failure modes.
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。
Lists tables, describes columns and data types, identifies foreign key relationships, and maps entity relationships in a database. Use when the user asks about database schema, table structure, column types, what tables exist, ERD, foreign keys, or how entities relate.
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。
Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-learning variant predictions, or characterizing cis-acting regulatory effects.
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。
Generate Mermaid architecture diagrams from your codebase. Produces C4 context and container diagrams, sequence diagrams for key flows, ER diagrams from database schemas, and module dependency graphs. Use when you need architecture diagrams, system diagrams, database ERD, sequence diagrams, dependency visualization, or C4 model diagrams.
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。
Convene a roundtable of sub-agents that debate a decision or proposal from opposing perspectives — parallel independent statements, anonymous cross-review, then a chaired verdict reporting consensus and dissent.
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 gate criteria before PRD lifecycle advancement by delegating to the readiness scoring pipeline (scripts/readiness.py). Returns a graduated PASS / WARN / BLOCK verdict with top blockers and their causal chain. Triggers before advancing from v0.X to v0.Y or explicit `/ghm-gate-check`.
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 says "/tribunal", "tribunal", "review this", "3-way review", "risk-value-feasibility check", or wants multi-perspective adversarial review. Also triggered by: "트리뷰널", "리뷰 해줘", "3관점 리뷰", "위험성 검토". Runs 3 agents (Risk/Value/Feasibility) in parallel and synthesizes a verdict.
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。
Designs database schemas with proper normalization, indexing, constraints, and tenant isolation patterns. Use when someone needs to create a new database schema, add multi-tenant support, design row-level security policies, or optimize table structures. Trigger words: database schema, table design, RLS, row-level security, foreign keys, indexes, migrations, ERD, data model, normalization.
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。