「eq」の検索結果

Track complex, multi-session work with dependency graphs using bd (beads) issue tracker. Use when work spans multiple sessions, has complex dependencies, or requires persistent context across compaction cycles. For simple single-session linear tasks, TodoWrite remains appropriate.

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。

Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservation analysis. Use when reading, writing, or converting alignment file formats.

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。

Master Bash Automated Testing System (Bats) for comprehensive shell script testing. Use when writing tests for shell scripts, CI/CD pipelines, or requiring test-driven development of shell utilities.

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。

Master defensive Bash programming techniques for production-grade scripts. Use when writing robust shell scripts, CI/CD pipelines, or system utilities requiring fault tolerance and safety.

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。

Download large datasets from NCBI efficiently using EPost, history server, batching, rate limiting, and retry logic. Use when bulk-fetching tens of thousands of sequences, pulling all results of a large ESearch, designing reproducible pipelines, comparing E-utilities to NCBI Datasets v2 CLI, or implementing checksum-validated downloads. Encodes WebEnv TTL (~8h), EPost 200-ID limit, retmax caps, parallelization design, and integrity verification.

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 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

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。

Create and manage database migrations with reversible changes, proper naming conventions, and zero-downtime deployment strategies. Use this skill when creating database migration files, modifying schema, adding or removing tables/columns, managing indexes, or handling data migrations. Apply when working with migration files (e.g., db/migrate/, migrations/, alembic/, sequelize migrations), schema changes, database versioning, rollback implementations, or when you need to ensure backwards compatibility during deployments. Use for any task involving database structure changes, index creation, constraint modifications, or data transformation scripts.

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。

Define database models with clear naming, appropriate data types, constraints, relationships, and validation at multiple layers. Use this skill when creating or modifying database model files, ORM classes, schema definitions, or data model relationships. Apply when working with model files (e.g., models.py, models/, ActiveRecord classes, Prisma schema, Sequelize models), defining table structures, setting up foreign keys and relationships, configuring cascade behaviors, implementing model validations, adding timestamps, or working with database constraints (NOT NULL, UNIQUE, foreign keys). Use for any task involving data integrity enforcement, relationship definitions, or model-level data validation.

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。

Create irresistible offers and pitches using Alex Hormozi's methodology from $100M Offers. Guides through value equation, guarantee frameworks, pricing psychology, and creating offers "too good not to take" for any product or service.

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。

Write Ruby gems following Andrew Kane's proven patterns and philosophy. Use when creating new Ruby gems, refactoring existing gems, designing gem APIs, or when the user wants clean, minimal, production-ready Ruby library code. Triggers on requests like "create a gem", "write a Ruby library", "design a gem API", or mentions of Andrew Kane's style.

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。

Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm. For QC thresholds, use protein-qc.

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。

How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

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。

Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.

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。

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

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。

Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking 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。

Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.

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。

Determines if a patient has completed ≥1 year of consistent and compliant hormone therapy for genital surgery approval. Triggers include patient requesting genital surgery and being on hormone therapy.

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。

Determines whether an adult patient meets eligibility criteria for initiating gender-affirming hormone therapy. Triggered when an adult patient requests gender-affirming hormones or presents for evaluation of hormone therapy eligibility.

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。

Determines if an adolescent meets criteria for initiating sex hormone treatment for gender dysphoria/gender incongruence. Triggered when an adolescent requests sex hormones or presents for gender-affirming hormone therapy evaluation.

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。

Guides timing of breast surgery for transgender males based on physical and mental health status. Triggers include transgender male considering breast surgery or requesting mastectomy.

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。

Recommends continuing a patient’s personal continuous glucose monitor (CGM) in the hospital with or without algorithm-driven insulin pump (ADIP) therapy rather than discontinuing it for individuals already using CGM outpatient. Use when deciding whether to maintain personal CGM during admission or when a patient requests to keep their device, particularly in those at high risk for hypoglycemia.

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。

Assesses patient's ability to identify the receiver, sensor, and transmitter components of a real-time CGM system. Triggered by clinician requests to review CGM parts or verify patient can name sensor, transmitter, and receiver.

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。

Assesses whether a patient performs self-monitoring blood glucose (SMBG) fingerstick calibrations as required for their real-time CGM system. Triggers include: 'Verify patient performs fingerstick calibrations', 'Ensure calibration schedule is followed'.

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。

Assesses patient’s understanding of how CGM data (trends, rates of change) differ from discrete SMBG fingerstick values. Triggered when clinicians hear requests to explain lag and trend arrows on CGM or teach the difference between CGM glucose and fingerstick glucose.

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。