「ida」の検索結果

Use when you need to design, review, or improve REST APIs with Micronaut — including @Controller routes, HTTP status codes, DTOs, Bean Validation, exception handlers, pagination, idempotency, ETag/If-Match, caching headers, versioning, contract-first OpenAPI (OpenAPI Generator), optional runtime OpenAPI via micronaut-openapi, and security annotations. This should trigger for requests such as Review or improve Micronaut @Controller REST APIs; Add validation, error handling, or align controllers with the OpenAPI contract on Micronaut HTTP layer; Design Micronaut controllers and DTO validation; Add Micronaut exception handlers and Problem Details responses; Improve pagination filtering or OpenAPI alignment in Micronaut APIs. Part of Plinth Toolkit

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Freshly judge exact subject content against bead or caller acceptance, optionally persist verdict.v2 for a declared consumer, and stop. Triggers: "validate", "independently validate", "vibe".

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。

Decide where to enforce structured LM output (constrain at decode time with Outlines vs validate-and-retry with Instructor vs grammar with Guidance) and which failure stance to take (Assert/hard-fail vs Suggest/soft-retry). Use when an LM's output is parsed or typed by downstream code and you must pick one enforcement library plus its failure handling, when malformed output is burning tokens on retries, or when choosing between decode-time vs validation-time constraints for local vs API models.

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 reviewing Firebase code against security model and best practices. Triggers on "review firebase", "check firebase", "validate", "audit firebase", "security review", "look at firebase code". Validates configuration, rules, architecture, and security.

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 coherent, whole-paper mathematical modeling solution framework from a complete contest problem. Use after the user supplies a CUMCM or other modeling problem and asks for modeling ideas, an overall solution plan, question-by-question analysis, candidate-model comparison, model-selection reasons, innovations, validation, or cross-question linkage. For every question, explain the task and mathematical essence, compare multiple feasible models in tables, recommend a route with explicit reasons, and keep all questions connected through shared data, variables, parameters, constraints, and 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。

Walk-forward validation framework for trading strategies and ML models with time-series-aware splits, overfit detection, and regime-aware 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。

Designs convex/schema.ts tables, validators, indexes, and relationships, and keeps the schema honest as data evolves. Use when creating tables, adding fields, choosing index fields, modeling relationships, or when a validator error appears at deploy time.

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。

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab 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。

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。

Provides comprehensive NestJS best practices including modular architecture, dependency injection scoping, exception filters, DTO validation with class-validator, and Drizzle ORM integration. Use when designing NestJS modules, implementing providers, creating exception filters, validating DTOs, or integrating Drizzle ORM within NestJS applications.

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。

Provides patterns for unit testing `@ConfigurationProperties` classes with `@ConfigurationPropertiesTest`. Validates property binding, tests validation constraints, verifies default values, checks type conversions, and mocks property sources for Spring Boot configuration properties. Use when testing application configuration binding, validating YAML or application.properties files, verifying environment-specific settings, or testing nested property structures.

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 validation rules for construction data. Create RegEx and logic-based validation for BIM elements, cost codes, and schedule data.

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 automated BIM validation pipelines for IFC/Revit data. Continuous validation against IDS, LOD requirements, COBie, and project-specific BEP standards.

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 the OpenConstructionERP validation engine: rule packs (BOQ quality, DIN 276, NRM, GAEB, MasterFormat, DPGF) that check estimates at import time and on demand. Use when verifying BOQ correctness or writing custom validation 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。

Merges ephemeral report and analysis artifacts into permanent documentation. Use when LLM-generated markdown files have accumulated and need consolidation.

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 and self-executes a diff-derived test plan for a PR. Use when validating PR changes before merge. Do not use for code review; use sanctum:pr-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。

Validate, lint, audit, or plan Terraform/.tf/HCL files; runs tflint, checkov, terraform validate.

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。

Conducts HIPAA risk analysis per 45 CFR §164.308(a)(1) following OCR guidance methodology. Covers threat identification, vulnerability assessment, likelihood and impact determination, risk scoring, and mitigation planning for electronic protected health information. Keywords: HIPAA risk analysis, OCR guidance, threat assessment, vulnerability, risk management, ePHI.

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Guides ISO 27701 Privacy Information Management System implementation extending ISO 27001/27002. Covers Clause 5 PIMS-specific requirements, Clause 6 PIMS guidance for ISO 27002, Clause 7 PII controller guidance (Annex A), Clause 8 PII processor guidance (Annex B), gap assessment, and certification path. Keywords: ISO 27701, PIMS, privacy management system, ISO 27001 extension, certification, Annex A, Annex B.

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。

Parallel multi-AI cross-validation research workflow (大版本). Dispatch N internal sub-agents + grok + gemini in parallel, automatically cross-validate findings, tier by confidence (strong consensus / partial / conflict / insufficient), generate tiered action items with arbitration. Use when user says "多 AI 调研", "交叉验证", "独立共识", "三脑调研", "multi-ai research", "parallel research", "cross-validate", or needs deep research that benefits from internal data + external 2026 consensus. NOT for quick factual Q&A, pure code reasoning, or tasks needing deep 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。

Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.

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。

Builds a new Claude Code agent (subagent) from scratch through a relentless, evidence-based interview that walks the agent's design tree decision-by-decision — entity fit, domain focus and vocabulary, role identity, anti-patterns, description, model tier, tools, and self-containment — then reviews the finished agent against the plugin-building guidance and applies every fix it finds. Use when creating, authoring, scaffolding, designing, or drafting a new agent or subagent. Does not build a skill or slash command — use skill-builder. Does not serve, vendor, or refresh the authoring guidance itself — use guidance.

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。

Surfaces Han's shared Human-Readable Output Standard — the readability rule and the writing-voice profile — into the calling skill's own context, so the caller drafts in voice and runs its self-check against the current standard sourced from one canonical copy. Use when a prose-producing skill needs the shared readability standard available in context before it drafts. Governs the shape of a written deliverable, where explanation-guidance governs what a run says to a person in a turn. Runs in the caller's context and hands control straight back; it does not produce a deliverable of its own, rewrite anything, or judge the caller's work. Does not run the adversarial rewrite pass — dispatch the readability-editor agent for that, or use edit-for-readability to rewrite an existing target. Does not cover explaining technical work to a reader who will not implement it — use explanation-guidance for 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。

Surfaces Han's shared standard for explaining technical work to a reader who will not implement it into the calling skill's own context, so the caller writes its escalations, confirmation turns, and stops as a concrete outcome the reader could observe rather than as a mechanism. Use when a skill is about to ask a person a question, stop for an input, or explain a technical consequence to someone who will not open the code. Governs what a run says to a person in a turn, where readability-guidance governs the shape of a written deliverable. Runs in the caller's context and hands control straight back; it does not produce a deliverable of its own, rewrite anything, or judge the caller's work. Carries guidance only and adds no self-check step.

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。