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概要と使いどころ
Monitor reviewed Grafana telemetry and freshness evidence for IoT devices and edge fleets. Use for smart devices, home automation sensors, remote equipment, wind turbines, space hardware, device-fleet freshness, missing telemetry, and bounded edge-health comparisons.
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Develop, challenge, and document Chisel processor microarchitecture designs before implementation. Use when discussing or writing design documents for processor pipelines, queues, issue logic, rename, ROB, LSU, caches, MSHRs, forwarding, wakeup, replay, flush, privilege, exceptions, or other cycle-accurate hardware mechanisms; when converting design conversations into stable Markdown specifications; or when reviewing a proposed Chisel CPU design for correctness, timing, area, verification cost, and cross-document consistency.
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Create interactive AI role-play training activities as self-contained HTML. Use when the user asks to generate a role-play, persona practice, sales simulation, customer conversation drill, compliance scenario, or any learner-vs-AI-character training exercise.
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Use this skill whenever the user asks to generate, edit, inpaint, restyle, or create bitmap images through OpenAI's Responses API image_generation tool from Codex. This skill calls the Responses API, saves generated base64 image results to files, uses no npm or pip dependencies, works on Linux/macOS/Windows with either Node.js 18+ or Python 3, and reuses Codex's configured API base URL, model, and key instead of asking the user for credentials.
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Offload builds, tests, or artifact verification to authorized SSH hosts and isolated worktrees; synchronize remote fixes into dedicated coordinator commits and preserve reproducible build provenance. Use for spare development capacity and remote build troubleshooting. Paid provisioning requires a separate resource lifecycle contract.
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Annotate speech/TTS datasets with per-clip quality metrics (MOS, SNR, STOI, pitch, bandwidth, speaking rate, WER/CER, gender/emotion), multi-ASR consensus transcription and speaker labeling using the audiogear pipeline; then filter clips by quality and build listenable HTML QA reports. Use when asked to compute audio dataset metrics, build extended_metadata.csv, transcribe unlabeled audio, select clean TTS training data, or QA a speech dataset.
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。
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the `cacheComponents` flag, work through a flood of blocking-prerender / instant validation errors, run the `cache-components-instant-false` codemod, or decide between opting routes out with `export const instant = false` and fixing them in place.
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Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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Build weighted gene co-expression networks to identify modules of co-regulated genes, relate them to phenotypes, and find hub genes using WGCNA, hdWGCNA, MEGENA, CEMiTool, and Gaussian graphical models. Covers signed-network choice, soft-threshold selection, module preservation, and the marginal-vs-partial-correlation distinction. Use when finding co-expression modules, identifying hub genes, relating gene networks to clinical or experimental traits, or building single-cell co-expression networks. For directed TF-target inference see scenic-regulons and grn-inference; for condition rewiring see differential-networks.
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Runs JACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens; Allen et al 2019 Genome Research) which models per-sgRNA log-fold-change as the product of a treatment-dependent gene-essentiality term and a treatment-independent guide-efficacy term. Covers the Bayesian decomposition math, the hierarchical efficacy prior shared across screens performed with the same library, when JACKS outperforms MAGeCK (multi-screen joint analysis, libraries with broad efficacy variance) and when it does not (single screen, novel libraries with no prior efficacy), library-reuse efficacy transfer, downstream essentiality interpretation, and the 2.5x sample-size reduction enabled by efficacy-aware testing. Use when running multiple screens with the same library, when guide-level noise is suspected to dominate per-gene signal, when reusing published essentiality reference screens for efficacy priors, or when comparing screens performed across cell lines that share library but differ biologically.
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Performs logistic regression for clinical trial outcomes (binary, ordinal, multinomial) with marginal-vs-conditional estimand reporting per FDA 2023 covariate adjustment guidance, g-computation/standardisation for marginal effects, modified Poisson for RR, Brant test for proportional odds, Firth penalty for separation, and Hauck-Donner detection. Use when modeling binary or ordinal endpoints in confirmatory or exploratory clinical trials.
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Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions.
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Expert guide for Backend.AI distributed computing platform. Automatically activates when users ask about: - Backend.AI architecture, components (Manager, Agent, Storage Proxy, Webserver, App Proxy) - Features (session scheduling, Sokovan orchestrator, multi-tenancy, resource allocation) - APIs (REST, GraphQL), authentication, RBAC authorization - Container runtime (kernels, jail sandbox, hook library, virtual folders) - Accelerator support (CUDA, ROCm, TPU, NPU, Graphcore IPU) - Client SDKs (Python, Java, JavaScript, PHP) - Setup, requirements (Python 3.13+, Docker, PostgreSQL, Redis, etcd) - How WebUI connects to/interacts with Backend.AI backend - Plugin interfaces, development setup, infrastructure Use when user mentions "Backend.AI", "backend.ai", "Sokovan", component names, or asks about the backend platform this WebUI connects to. allowed-tools: WebFetch, Read
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Генерация полных Python pytest тестов для REST API эндпоинтов с валидацией схемы. Использовать при создании тестов для новых эндпоинтов, добавлении покрытия для CRUD операций или валидации соответствия API с OpenAPI схемами.
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Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
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Suggests initiating inpatient continuous glucose monitoring (CGM) for select hospitalized patients at high risk for hypoglycemia, combined with periodic point-of-care glucose checks for accuracy. Triggers include planning glucose monitoring for inpatients with prior severe hypoglycemia, renal or hepatic dysfunction, or age 65 years or older.
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 recommends against initiating treatments aimed at normalizing cortisol or its action when only borderline biochemical abnormalities of the hypothalamic-pituitary-adrenal (HPA) axis are present without specific signs of Cushing's syndrome. Use when encountering borderline urinary free cortisol, late-night salivary cortisol, or dexamethasone suppression test results without classic Cushingoid features; triggers include borderline UFC (1-2× ULN), equivocal late-night salivary cortisol, or nondiagnostic low-dose DST.
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This skill recommends glucocorticoid replacement and patient education for hypocortisolemic patients after surgical remission of Cushing's syndrome. Use when a postoperative Cushing's patient exhibits low cortisol (e.g., morning cortisol <5 µg/dL) or symptoms of adrenal insufficiency.
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This skill suggests medical therapy to block aberrant hormone receptors for bilateral macronodular adrenal hyperplasia (BMAH) when surgery is not preferred or feasible. Consider this approach in patients with confirmed BMAH and evidence of aberrant hormone receptor expression (e.g., GIP, LH/hCG, serotonin) driving cortisol excess.
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This skill recommends follow-up morning cortisol and/or ACTH stimulation tests or insulin-induced hypoglycemia to assess HPA axis recovery in postoperative Cushing's syndrome patients with at least one intact adrenal gland. Triggers include postoperative remission (morning cortisol <5 µg/dL or UFC <28–56 nmol/d) and the need to evaluate HPA recovery before glucocorticoid discontinuation.
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This skill recommends that a multidisciplinary team, including an experienced endocrinologist, incorporates patient values and preferences while providing education about treatment options for Cushing’s syndrome. Use when planning treatment for a CS patient requiring coordinated care; triggers include persistent hypercortisolism after transsphenoidal surgery, consideration of bilateral adrenalectomy, radiotherapy, or medical therapy, and need for shared decision‑making.
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This skill recommends measuring serum cortisol or urine free cortisol off-medication at 6- to 12-month intervals to assess radiation therapy effect in patients with Cushing's syndrome undergoing or post-radiotherapy. It is also indicated when patients on stable medical therapy develop new adrenal insufficiency symptoms such as fatigue, weight loss, or hypotension.
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Recommends checking and managing vitamin D according to Endocrine Society guidelines to avoid hypocalcemia in patients receiving bisphosphonates or denosumab for hypercalcemia of malignancy. Use when a clinician notes risk factors for hypocalcemia (e.g., low 25‑OH vitamin D, renal insufficiency) and asks about baseline labs before antiresorptive start.
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Provides evidence-based guidelines for preoperative optimization and postoperative monitoring in patients with primary aldosteronism undergoing adrenalectomy. Triggers include when planning surgery or starting treatment and asking 'What perioperative care is needed?' or managing complications such as resistant hypertension, hypokalemia, or suspected cortisol co-secretion.
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。