「stable」の検索結果

Think and work like an expert Geochemist. Use when a task calls for Geochemist judgment. Reasons from Gibbs equilibria, mass and isotope balance, and fluid–rock interaction through stable (δ) and radiogenic (ε, isochron) systems, ICP-MS/LA-ICP-MS/TIMS/MC-ICP-MS/IRMS, PHREEQC/Perple_X phase modeling, and EarthChem/GeoReM workflows while treating alteration, matrix effects, Pb loss, mixing arrays, and Fretwell’s Law violations 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 Industrial Engineer. Use when a task calls for Industrial Engineer judgment. Reasons from takt, Little's Law, and ρ-stable queueing (M/M/c, Erlang C) through DMAIC/DMADV, VSM, line balancing, SLP/ALDEP/CRAFT layout, MTM/MOST, work sampling, RNLE/RULA/REBA, ISO 22400 OEE, and Arena/AnyLogic DES V&V; treats simulation warm-up/replication gaps, CRAFT non-contiguity, and OEE-without-takt red herrings 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。

Query the Ensembl REST API for gene/transcript/protein lookup, sequence retrieval, comparative genomics (Compara), variant effect prediction (VEP), regulatory features, and cross-species ortholog/paralog calls. Use when pulling Ensembl-native data (Ensembl Gene IDs, version-pinned releases, archive endpoints for reproducibility), gene/transcript/exon structure with stable IDs, or VEP for variant annotation. Encodes the 15 req/sec rate limit, archive (e110.rest.ensembl.org) for reproducibility, Ensembl divisions (vertebrates / plants / fungi / metazoa / bacteria), and the symbol-vs-ID stability problem.

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 a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and majority-rule overlap. Use when generating a stable peak coordinate system for downstream differential accessibility, ML feature engineering, cross-sample comparison, or fixed-width peak counts; covers Corces 2018 iterative overlap (501 bp), DiffBind summit re-centering, and ENCODE consistency rules.

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。

UE (user experience engineering) skill for defining end-to-end user experience behavior and interaction logic. Use for tasks like flow design, interaction models, state machines, error recovery, input validation, usability heuristics, accessibility, and turning UX intent into testable acceptance criteria for implementation.

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。

Translate a vague request or GitHub issue into a concrete, testable spec using five structured elements (problem, scope, acceptance criteria, edge cases, success criterion) before writing any code. Prevents scope creep, PR churn, and mid-implementation pivots.

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。

Ultimate MCP server for Civitai — search models, browse top images with prompts, download LoRAs/Checkpoints, analyze trends. Use when user asks about AI models, LoRAs, checkpoints, Stable Diffusion, Flux, image generation prompts, or Civitai.

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 academic papers across up to 8 sources (OpenAlex / Semantic Scholar / CrossRef / PubMed / arXiv for English, OpenReview for AI venues, plus native-Chinese retrieval via NSSD 国家哲社文献中心 + yiigle 中华医学期刊) with adjustable depth — Quick scan (5 min) to Audit prep (3 hr). Use when the user wants to find papers, run a literature search, gather references, scope a research topic, search Chinese-language / 中文原生 literature (中文文献/中文核心/CSSCI/C刊/国内研究/国内文献/中华××期刊/心理学报/经济研究), or filter results by journal tier (中科院分区/一区/几区, Q1, JCR/SJR quartile, 影响因子/impact factor, 期刊分区, 顶刊/top journal, '按分区筛'), or export paste-ready professional search strategies / 检索式 for external databases (PubMed / WOS / Scopus / Embase / 知网 CNKI / 万方 / SinoMed — '写检索式', '导出检索式', 'WOS 检索式', '知网专业检索', 'search strategy', 'boolean search strategy'). Triggers on search verbs ('find papers', 'literature search', 'papers about X'), review types ('scoping review', 'systematic review', 'SR prep', 'literature review', 'lit review', 'help me write a lit review'), Chinese ('找文献', '找论文', '论文搜索', '学术检索', '文献检索', '文献综述', '综述前期', '求文献', '中文文献', '中文核心', 'CSSCI', 'C刊', '国内研究', '找中文的'). Outputs Shadcn HTML report + BibTeX/RIS/CSV + PRISMA-S log. Do NOT use for: concept explanations ('what is X' / 'X 是什么', e.g. '影响因子怎么算'), writing ('帮我写' / 'help me write a paragraph'), single-paper interpretation or PDF download with metadata (use paper-downloader-portable), or when the user already has a literature set (use literature-set-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。

Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.

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。

Release moi-computer to npm — verify locally, hand off to the gated GitHub Actions workflow, then verify the published package. Defaults to a `next` preview; pass `stable` for a `latest` release. Use when the user asks to publish, release, ship a version, or cut a dev preview.

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。

Goal-driven E2E testing where a browser agent (Playwright MCP / computer-use) reads a natural-language goal and explores the app via the accessibility tree to assert outcomes — no pre-written script. Covers when intent-driven beats scripted, making agent runs deterministic (pinned model, temperature 0, seeded data, bounded steps, explicit success assertion, snapshot-not-pixel), cost/latency control, the accessibility-tree-first interaction model, CI gating, and graduating a stable run into a scripted Playwright test. Use when: "agentic browser test," "goal-driven browser test," "let an agent explore the app," "natural-language E2E," "browser agent smoke test," "Playwright MCP test." Not for: Writing/maintaining deterministic scripted Playwright tests — that is playwright-automation. Testing your product's OWN LLM features — that is ai-system-testing. Related: playwright-automation, ai-system-testing, exploratory-testing, test-reliability, qa-project-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。

Build a single sprint or release test plan. Covers feature decomposition into testable scenarios, requirements-to-test coverage mapping, effort estimation by test type, prioritization matrices (risk × effort), resource allocation, and scheduling with buffers. Use when: "sprint test plan," "release test plan," "what to test this sprint," "test estimation," "coverage mapping." Not for: multi-quarter strategy — use `test-strategy`. Not for: ranking areas by risk — use `risk-based-testing`. Not for: the go/no-go decision itself — use `release-readiness`. Related: test-strategy, risk-based-testing, release-readiness.

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。

Hybrid fingerprint + LLM pipeline for bug classification, deduplication, and ticket generation. Normalizes CI logs, creates stable fingerprints, clusters near-duplicates, then uses LLM for severity classification and ticket writing. Includes bug reporting templates and severity/priority matrix. Use when: "bug triage," "classify bugs," "failure analysis," "auto-classify," "CI failures," "bug report," "defect template." Not for: runtime self-healing of one flaky locator — use test-reliability. Not for: designing new tests from production telemetry — use observability-driven-testing. Related: qa-metrics, qa-dashboard, ci-cd-integration, qa-project-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。

Generate a structured implementation plan from an evidence draft. Validate paths, obtain configured independent Codex and Qoder reviews, synthesize available advice against repository evidence, preserve the draft, and produce testable acceptance criteria and validation 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。

World-class character and art style consistency for AI-generated images and videos - ensures visual coherence across series, maintains character identity, and provides rigorous QA before deliveryUse when "character consistency, art style, same character, consistent character, visual continuity, series, turnaround sheet, character sheet, reference image, character bible, style guide, anime character, consistent look, face consistency, outfit consistency, lora training, ip-adapter, flux kontext, visual qa, art quality, generation review, style drift, character drift, character-consistency, art-style, visual-qa, ai-art, image-generation, video-generation, anime, illustration, lora, ip-adapter, flux, midjourney, stable-diffusion" mentioned.

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 patterns for AI-powered image editing including inpainting, outpainting, ControlNet, image-to-image, and API integration with Replicate, Stability AI, and FalUse when "ai image editing, inpainting, outpainting, controlnet, image to image, remove object from image, extend image, flux inpaint, sdxl editing, image-editing, inpainting, outpainting, controlnet, stable-diffusion, flux, replicate, stability-ai, comfyui" mentioned.

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。

Generates a behavioral scenario acceptance matrix for comprehensive test coverage planning. Maps user scenarios to acceptance criteria with stable IDs. Use when planning test coverage for a complex feature, before a release or milestone review, or when someone asks what is tested.

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。

Architecture Patterns workflow skill. Use this skill when the user needs Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Architecture Patterns workflow skill. Use this skill when the user needs Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Architecture Patterns workflow skill. Use this skill when the user needs Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

End-to-end test of the heygen CLI against the live API. Builds the binary, then exercises auth, list, get, --human, schema, error handling, and the full create-poll-download-delete write path. Spends a small number of API credits per run. Use before cutting a stable release.

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。

The Socratic spec-refinement front of /feature, and the planning front of /sprint. Routed to BEFORE any code — it turns a one-line idea into a concrete spec with testable criteria, ready for initial combined sprint review or explicit sequential approval. Five gated phases — frame, shape, refine, write, review-and-approve. No implementation before an approved spec; the caller retains required planning, execution and delivery ordering. Each acceptance criterion becomes one tdd Phase 1 obligation.

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。

Route HugeGraph MCP structured graph query tasks to stable read-only tools. Use when the user asks graph questions, asks to generate Gremlin, provides Gremlin to explain, or needs read-only graph exploration.

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。

Route HugeGraph MCP schema design, validation, and dry-run preview tasks to stable public tools. Use when the user asks to design vertex labels, edge labels, properties, primary keys, indexes, or preview schema operations.

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。