「diagnostic」の検索結果

Designing quizzes, personality assessments, and recommendation tools that segment users into actionable categories rather than generating clicks for clicks' sake. Question architecture, scoring algorithms, result categorization, recommendation mapping, lead capture integration. Honest about clickbait-quiz (engagement only), vanity-result (entertaining, not useful), and actionable-segmentation (genuine categorization that drives next-step recommendations) patterns. Triggers on quiz, assessment, personality test, recommendation tool, scorecard, diagnostic, fit evaluator, what-type-of-X-are-you, persona quiz. Also triggers when an audience needs a categorization-driven lead magnet, when a vanity quiz is producing engagement but no qualified leads, or when an assessment is being scoped for the first 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。

YC Office Hours — product idea diagnostic before writing code. Two modes: Startup (6 forcing questions with rigorous pushback) and Builder (generative brainstorming). Outputs design doc. Includes landscape research, premise challenge, alternatives generation, visual wireframe sketching, and optional cross-model second opinion.

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。

Evidence-based clinical decision support and diagnostic reasoning

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 with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, foreign key constraints, OCC retry patterns, ORM migration (Django/EF Core/Hibernate/Rails/SQLAlchemy), DDL operations, query plan explainability, system diagnostics via CloudWatch AAS, SQL compatibility validation, and bulk data loading. Load before answering DSQL limit or error-code questions; it has limits docs omit. Triggers on phrases like: DSQL, Aurora DSQL, distributed SQL database, serverless PostgreSQL-compatible database, migrate to DSQL, DSQL query plan, DSQL EXPLAIN ANALYZE, DSQL ENUM, DSQL foreign key, DSQL OCC retry, DSQL multi-region, DSQL JSONB, DSQL GIN index, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader, DSQL slow, DSQL performance, DSQL wait events, DSQL AAS.

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。

Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM). This is the primary interface for accessing HyperPod nodes — direct SSH is not available. Use when any skill, workflow, or user request needs to execute commands on cluster nodes, upload files to nodes, read/download files from nodes, run diagnostics, install packages, or perform any operation requiring shell access to HyperPod instances. Other HyperPod skills depend on this skill for all node-level 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。

Diagnostic-only skill for Slurm scheduler and node-daemon issues on Amazon SageMaker HyperPod Slurm clusters. Scope mirrors the HyperPod troubleshooting guide. Invoke when the user reports a Slurm node stuck in down/drain, "Node unexpectedly rebooted" after auto-repair, slurmd not running, jobs stuck PENDING with REASON=Resources while sinfo shows idle nodes, jobs stuck COMPLETING after node replacement, GRES/GPU counts wrong, scontrol ping failing, slurmctld unresponsive, an Action:Reboot/Replace request that did not trigger HyperPod auto-recovery, or auto-resume not restarting a job. Also triggers on "drain before reboot", "diagnose a Slurm node", "investigate stuck jobs."

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。

Cross-functional organizational health check scoring 8 dimensions on a traffic-light scale. Use when assessing company health, preparing for board reviews, identifying at-risk functions, or diagnosing cross-functional problems.

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。

Implement Terraform provider configuration and authentication with the Plugin Framework: provider schema for credentials (Optional + Sensitive attributes), environment variable fallbacks, credential provider chains (static config, then environment variables, shared credentials file, and platform identity), unknown-value guards in Configure(), secret redaction, configure-time credential validation, and diagnostics that name every source tried. Use when implementing or reviewing a provider's Configure method or provider schema, adding authentication options (API keys, tokens, profiles, credentials files, assume-role), deciding how a provider should resolve credentials, debugging "no valid credential sources" or missing-credentials errors, or unit testing credential resolution.

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Use when the user wants to compare or benchmark multiple LLMs/agents arena-style but it's unclear which specific workflow fits — a general-purpose win-rate comparison on a custom task, or a benchmark specifically about reference/citation hallucination rate. Also use when the user mentions model arena, agent arena, pairwise model comparison, win-rate ranking, or comparing models on a task and hasn't specified whether that task is generic or about citation accuracy. This skill is the entry router for the arena-eval suite: it asks one diagnostic question when needed, then recommends the workflow or workflows needed to cover the request.

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 the user has a RAG (Retrieval-Augmented Generation) system and wants to evaluate its quality — separating retrieval issues from generation issues. Also use when the user mentions RAG evaluation, faithfulness checking, hallucination detection in RAG, retrieval quality, chunking optimization, or "is my RAG pipeline working." Outputs a diagnostic matrix that pinpoints whether problems are in retrieval or generation.

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 the user wants help with academic papers or citations but it's unclear which specific workflow fits — reviewing a paper, checking a BibTeX file for fake references, or benchmarking multiple LLMs on reference-recommendation accuracy. Also use when the user mentions paper review, peer review, BibTeX verification, citation checking, reference hallucination, or academic literature accuracy and hasn't specified which of those three tasks they mean. This skill is the entry router for the academic-eval suite: it asks one diagnostic question then routes to the right sub-skill.

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 the user wants to build an evaluation system for an LLM/agent application but doesn't know where to start — they have traces, prompts, RAG pipelines, or nothing at all. Also use when the user mentions evaluation, eval, benchmarking, testing LLM quality, measuring agent performance, assessing RAG accuracy, or wants to compare prompts/models. This skill is the entry router: it asks diagnostic questions then recommends which sub-skill (local workflow) to use next.

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。

Analyse systématique d'un Data Processing Agreement (DPA) au regard de l'article 28 RGPD, des lignes directrices EDPB 07/2020 et 02/2024, des CCT 2021 (décision d'exécution 2021/914), des recommandations EDPB 01/2020 (mesures supplémentaires post-Schrems II), et du Règlement (UE) 2024/1689 (Règlement IA). Produit un rapport structuré clause par clause (18 clauses : 13 obligatoires + 5 complémentaires) avec diagnostic 🟢/🟡/🔴, remédiations prêtes à insérer, analyse détaillée des transferts internationaux, vérification Règlement IA, et questions à poser au fournisseur. Triggers : "analyse de DPA", "audit DPA", "vérifier un DPA", "DPA fournisseur", "data processing agreement", "art. 28 RGPD", "sous-traitant RGPD", "négociation DPA", "review DPA", "conformité contrat sous-traitance".

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。

Diagnose motivation problems in a task using self-determination theory and redesign for autonomy, competence, and relatedness. Use when students are disengaged, resistant, or going through the motions.

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。

Analyse student work against criteria to identify specific gaps between current performance and learning objectives. Use when reviewing submissions, planning feedback, or diagnosing learning needs.

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。

Bevy ECS skill for runtime cost. Keywords: Bevy, parallel systems, chain, FrameTimeDiagnosticsPlugin, Handles.

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 app metrics and make data-driven decisions. Covers DAU/MAU, retention, LTV, ARPU, App Store Connect analytics, AARRR funnel analysis, cohort analysis, and diagnostic decision trees. Use when user wants to understand their metrics, diagnose problems, or build a data-driven growth plan.

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 developer debug menu with feature flag toggles, environment switching, network log viewer, cache clearing, crash trigger, and diagnostic info export. Only included in DEBUG builds. Use when user wants a debug panel, dev tools menu, or shake-to-debug functionality.

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Generates an in-app feedback collection form with category selection, text input, optional screenshot attachment, device diagnostics, and smart routing — directing happy users to App Store reviews and unhappy users to support. Use when user wants feedback, bug reports, feature requests, or contact support forms.

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 knowledge for Azure Portal development including troubleshooting, security, and configuration. Use when managing portal RBAC sharing, Intune/Entra mobile access, dashboard JSON, portal policies, or HAR diagnostics, and other Azure Portal related development tasks. Not for Azure Cloud Shell (use azure-cloud-shell), Azure Resource Manager (use azure-resource-manager), Azure Monitor (use azure-monitor), Azure Security (use azure-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。

Expert knowledge for Azure Impact Reporting development including troubleshooting, configuration, and integrations & coding patterns. Use when wiring Impact Reporting to Monitor alerts, Logic Apps, Service Health, HPC Guest Health, or diagnostic logs, and other Azure Impact Reporting related development tasks. Not for Azure Carbon Optimization (use azure-carbon-optimization), Cost Management (use azure-cost-management), Azure Monitor (use azure-monitor).

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 knowledge for Azure Artifact Signing development including decision making, security, configuration, and integrations & coding patterns. Use when handling cert lifecycles, RBAC for signers, DGSSv2 migration, diagnostic logs, or CI/CD signing integration, and other Azure Artifact Signing related development tasks.

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 knowledge for Azure App Service development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring App Service plans/slots, VNet integration, managed identity/Key Vault, CI/CD deployments, or diagnostics, and other Azure App Service related development tasks. Not for Azure Functions (use azure-functions), Azure Static Web Apps (use azure-static-web-apps), Azure Spring Apps (use azure-spring-apps), Azure Container Apps (use azure-container-apps).

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。

Diagnostic audit for a running cold email program. Checks domain authentication (SPF/DKIM/DMARC), inbox health/reputation from Smartlead, bounce rate by inbox type, and optionally runs a spam placement test via Smartlead's Smart Delivery API. Outputs markdown report + CSV with per-domain/per-inbox scores and concrete action items. Use when reply rates drop, when bounces spike, when onboarding someone else's account, or as a weekly/monthly health check.

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。