「iab」の検索結果

Estimate how likely a protein therapeutic is to provoke an anti-drug antibody response, and locate the sequence regions responsible. Use this skill to tile a sequence into peptides, predict class II MHC presentation across a population-representative allele panel, aggregate predicted binders into a per-region and whole-molecule risk score, compare a candidate against its closest human germline, and decide which liabilities are worth deimmunising. Also trigger on immunogenicity, anti-drug antibody, ADA, T-cell epitope, MHC class II, HLA-DRB1, NetMHCIIpan, NetMHCpan, deimmunisation, tregitope, or population coverage.

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。

Render a deterministic 15-second vertical promo video from real Simulator screenshots with a three-beat viewer challenge and no Remotion initialization. Use in a twelve-minute parallel launch lane, as a reliable fallback to a richer Claude Design animation, or whenever ffmpeg and ImageMagick are available.

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。

AI pressure redirection — handling conflicting demands, tool failures, and competing constraints by blending with incoming force then reframing. Use when receiving contradictory instructions from different sources, during tool failure cascades where the planned approach becomes unviable, when scope pressure threatens to expand the task beyond what was asked, or when user frustration or correction needs to be absorbed rather than deflected.

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。

Provision and manage cloud infrastructure using Terraform with HCL modules, remote state backends, workspaces, and plan/apply workflow. Implement infrastructure as code patterns with variable management, output values, and state locking for team collaboration. Use when provisioning new cloud infrastructure, migrating from ClickOps or CloudFormation to declarative IaC, managing multi-environment infrastructure, versioning infrastructure changes alongside application code, or enforcing standards through reusable modules.

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。

Cultivate edible and medicinal mushrooms from spawn through fruiting. Covers substrate preparation, inoculation methods, incubation conditions, fruiting chamber management, harvest timing, and successive flushes for oyster, shiitake, lion's mane, and other commonly cultivated species. Use when growing edible mushrooms without the risks of wild foraging, when a reliable supply of fresh culinary or medicinal mushrooms is needed, or when exploring mycelial ecology through hands-on cultivation practice.

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。

Interpret a chromatogram from GC or HPLC analysis: verify system suitability parameters, identify peaks by retention time and spectral matching, perform accurate peak integration, calculate chromatographic figures of merit, and assess overall peak quality for reliable quantitation.

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。

Evaluate and simplify Boolean expressions using truth tables, algebraic laws (De Morgan, distributive, absorption, idempotent, consensus), and Karnaugh maps for up to six variables. Use when you need to reduce a Boolean expression to its minimal sum-of-products or product-of-sums form, verify logical equivalence between two expressions, or prepare a minimized function for gate-level 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。

Deploy machine learning models to production serving infrastructure using MLflow, BentoML, or Seldon Core with REST/gRPC endpoints, implement autoscaling, monitoring, and A/B testing capabilities for high-performance model inference at scale. Use when deploying trained models for real-time inference, setting up REST or gRPC prediction APIs, implementing autoscaling for variable load, running A/B tests between model versions, or migrating from batch to real-time inference.

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。

Remove dead code, unused imports, fix lint warnings, and normalize formatting across a codebase without changing business logic or architecture. Use when lint warnings have piled up during rapid development, unused imports and variables clutter files, dead code paths were never removed, formatting is inconsistent, or static analysis tools report fixable hygiene issues.

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。

Foundation obedience training for dogs — sit, stay, come, heel, and down using positive reinforcement and marker training. Covers timing, reward hierarchy, session structure, distraction proofing, and common handler errors. Use when a new puppy (8+ weeks) is ready for foundation training, an adult dog lacks reliable basic commands, a rescue dog needs to learn the household's command vocabulary, before advancing to complex behaviors or off-leash work, or when existing commands have degraded and need re-establishing.

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。

Add PUT workflow annotations to source files using the correct language-specific comment prefix. Covers annotation syntax, skeleton generation via put_generate(), multiline annotations, .internal variables, and validation. Supports 30+ languages with automatic comment prefix detection. Use after analyzing a codebase and having an annotation plan, when adding workflow documentation to new or existing source files, or when documenting data pipelines, ETL processes, or multi-step computations.

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。

Evaluate current trail conditions including weather, snow line, river crossings, exposure, and trail maintenance status for safety decision-making. Produces a GREEN/YELLOW/RED safety rating with actionable go/no-go recommendations. Use the day before or morning of a planned hike, during tour planning to assess seasonal viability, after unexpected weather changes on a multi-day tour, when reports suggest trail damage or closures, or before committing to an alpine or exposed route.

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。

Construct well-structured arguments using the hypothesis-argument-example triad. Covers formulating falsifiable hypotheses, building logical arguments (deductive, inductive, analogical, evidential), providing concrete examples, and steelmanning counterarguments. Use when writing or reviewing PR descriptions that propose technical changes, justifying design decisions in ADRs, constructing substantive code review feedback, or building a research argument or technical proposal.

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 production-ready Grafana dashboards with reusable panels, template variables, annotations, and provisioning for version-controlled dashboard deployment. Use when creating visual representations of Prometheus, Loki, or other data source metrics, building operational dashboards for SRE teams, migrating from manual dashboard creation to version-controlled provisioning, or establishing executive-level SLO compliance reporting.

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。

FastAPI web framework conventions: APIRouter with prefix/tags/dependencies, Pydantic v2 schemas (BaseModel, model_config, field_validator, model_validator), dependency injection with Depends, async SQLAlchemy session yielding, OAuth2PasswordBearer + JWT auth, lifespan context manager, pydantic-settings configuration, OpenAPI customization, and HTTPException error handling. Activated automatically by fastapi-plugin/stack.md. Use this skill to: - Structure FastAPI apps with per-feature APIRouter modules and a central app factory. - Write Pydantic v2 request and response schemas with proper validators. - Build a reusable Depends-based dependency chain for DB session, auth, and pagination. - Implement JWT-based authentication with get_current_user dependency. - Configure the app from environment variables via pydantic-settings. Do NOT use this skill for: - SQLAlchemy ORM model configuration and Alembic migrations — see fastapi-plugin:sqlalchemy-patterns. - Python language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing.

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。

ASP.NET Core web framework conventions: Minimal API vs MVC controllers, Program.cs composition, DI lifetimes (Scoped/Singleton/Transient), Options pattern with IOptions<T>, middleware ordering (HTTPS redirect → routing → authentication → authorization), model binding and validation (FluentValidation / DataAnnotations), ProblemDetails error handling, structured logging with ILogger<T>, configuration layering (appsettings.json + environment variables + User Secrets), and health checks. Works alongside csharp-foundation:csharp-conventions and aspnet-core-plugin:efcore-patterns. Use this skill to: - Compose Program.cs correctly — register services, configure middleware in the right order, map endpoints. - Apply the Options pattern to avoid passing raw IConfiguration into services. - Write Minimal API endpoint groups with typed results and authorization. - Handle cross-cutting errors uniformly with ProblemDetails. - Configure structured logging and health checks for production readiness. Do NOT use this skill for: - EF Core entity configuration and migrations — see aspnet-core-plugin:efcore-patterns. - C# language idioms — see csharp-foundation:csharp-conventions. - Testing — see csharp-foundation:dotnet-testing.

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 and library conventions for plain Python projects (no web framework): src/ package layout, CLI tooling (argparse/click/typer), configuration management (pydantic-settings), logging setup, module design, entry points, and packaging conventions. Activated automatically by python-plugin/stack.md as a convention skill for the development phase. Use this skill to: - Organise Python application code in a src/ layout with proper package structure. - Build CLI tools with argparse, click, or typer and register them as console scripts. - Manage configuration from environment variables using pydantic-settings. - Set up structured logging for production-grade applications. - Package a Python project correctly with pyproject.toml. Do NOT use this skill for: - Language idioms (type hints, dataclasses, enums, match/case) — see python-foundation:python-conventions. - Package manager commands (ruff, mypy, pip/poetry/uv) — see python-foundation:python-tooling. - Testing patterns — see python-foundation:pytest-testing. - Web framework patterns (Django/FastAPI/Flask) — see those framework plugin skills.

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。

Look up any arxiv paper on alphaxiv.org to get a structured AI-generated overview. This is faster and more reliable than trying to read a raw PDF.

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 environment-dependent code, templates, or deployment configuration changes, or when runtime configuration is missing. Produces a bidirectionally reconciled environment-variable contract.

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 asked to audit typography across a codebase. Produces a file:line report with concrete fixes ordered by impact and flags unverifiable rules. Not for building a type system or token scale.

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 asked to implement under non-negotiable constraints: performance budgets, platform limits, legal or API rules. Not for remote, credential, publish, deploy, or irreversible 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。

Reliability gate for answers. Forces evidence-based reasoning, explicit uncertainty, and “insufficient information” instead of guesses. Use when user says “be 100% sure”, “no hallucinations”, “only if verified”, “grounded answer”, or when stakes are high.

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。

Continuous self-reflection routine combining Schön (reflection-in-action / reflection-on-action) and Mezirow (content / process / premise) levels, anchored on KAMI values (val-002 глубина, val-007 честность перед собой, принцип 1 правда, принцип 2 нулевая толерантность к бреду). Triggers FIRE DURING THE TURN, not at end. Use when: (1) about to make a 2nd+ patch attempt at the same problem, (2) user pushes back with "стоп / нет / опять / так, ещё раз / не то / пиздёж", (3) noticing self drifting into "I think that..." without evidence, (4) about to report "готово", (5) copying a pattern from one place to another, (6) task took >2× expected time. Embeds scientific method (explicit hypotheses + falsifiability + prediction-first + alternatives) as substrate for premise-level reflection, not as ceremony.

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。

Operate Railway infrastructure: sign up for or sign in to a Railway account, create projects, provision services and databases, manage object storage buckets, deploy code, configure environments and variables, manage domains, troubleshoot failures, check status and metrics, set up Railway agent tooling, and query Railway docs. Use this skill whenever the user mentions Railway, signing up, creating an account, registering, logging in, deployments, services, environments, buckets, object storage, build failures, agent setup, MCP, or infrastructure operations, even if they don't say "Railway" explicitly. Also invoke this skill when the user asks to be signed up, registered, or onboarded to Railway: do not refuse — drive them through the unauthed `railway up` flow (deploys + signs up on the fly) or `railway login` (which creates new accounts on the fly).

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。