「nist」の検索結果

施测大五人格量表（Mini-IPIP，20题），评估外向性、宜人性、尽责性、神经质和开放性。当用户选择填写量表、或画像中人格数据缺失时使用。

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。

施测学术动机量表（AMS-GSR 28），采集科研人员的内在动机、外在动机和无动机数据。当用户选择填写量表、或画像中AMS数据缺失时使用。

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。

施测科研人员认知风格量表（RCSS），评估横向整合 vs 垂直深度的认知偏好。当用户选择填写量表、或画像中RCSS数据缺失时使用。

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。

FrontendHire's job-search operating system (fh) — a strict pipeline tracker, deterministic weekly metrics, and a review ritual. Runs the search as a measured system where the philosophy is law. Use for logging applications/leads/referral asks, the weekly review, status/metrics, and the onboarding interview.

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。

Screening for drug-drug interactions — mechanistic prediction, database checks, and clinical risk assessment.

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。

Map security controls across frameworks — one control set satisfying ISO 27001, SOC 2, NIST, PCI DSS, and more.

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 Bitwarden: vaults, collections, self-hosting options, CLI, and organization administration. Use when using Bitwarden personally or running it for a team, including self-hosted setups.

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。

Search and inspect the user's photo library, including connected device galleries. Use for photo requests and whenever a photo could ground or personalize a response; lookups of uploaded photos are cheap, so check opportunistically and move on if nothing fits.

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 edtech tools for their real impact on teacher time and administrative burden.

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。

Audit a housing affordability system -- evaluate rent burden calculation accuracy (30% and 50% thresholds), area median income modeling with HUD Income Limits and family size adjustments, Fair Market Rent and SAFMR tracking, payment standard administration, utility allowance schedules.

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。

Quantify cyber risk using FAIR methodology with Monte Carlo simulation, assess control effectiveness against NIST CSF/CIS/ISO 27001 frameworks, evaluate risk appetite alignment, and analyze cyber insurance coverage adequacy..

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。

Analyzes SIEM alert pipelines for rule optimization, alert fatigue reduction, criticality scoring, asset-based prioritization, and correlation rule design using NIST CSF and detection engineering principles..

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Parse natural-language quantities, units, dates, and ranges ("5'11\"", "1.5 cups", "72 in to cm", "three days ago", "between 5 and 10 kg", "it's hot") into canonical, validated values with issue codes and spans — and humanize them back. Use when a form input, LLM tool schema, MCP handler, or import pipeline takes free-text measurements/units/dates. Covers Standard Schema fields (quantityField/dateField/lingoObject) for the AI SDK and MCP, the headless <lingo-input>, unit conversion, and format/humanize round-trips. Zero-dependency TypeScript, deterministic.

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Run a deterministic, read-only health check on an Obsidian wiki. Use for lint, vault health check, audit wiki health, find orphans, find dead links, frontmatter audit, provenance audit, or wiki audit. Reports graph, link, frontmatter, provenance-ledger, empty-section, and stale-index findings; it does not reason broadly or repair files.

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Apply the Fable-derived 10-stage OBSERVE, OBSERVE, LISTEN, THINK, CONNECT, CONNECT, FEEL, ACCEPT, CREATE, GROW loop to consequential or ambiguous reasoning and decisions. Use for think this through, deep think, architecture review, postmortem, tradeoff analysis, or challenges to assumptions. This is a reasoning review, not a deterministic vault health check or repair workflow.

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Build and query a vault-local contextual BM25 retrieval index with optional multilingual Nomic cosine reranking; use for retrieve, hybrid retrieval, BM25, rerank, contextual retrieval, chunk search, vault search, semantic search, find relevant passages, or retrieval diagnostics. Derived caches stay under .vault-meta, remote egress requires explicit consent, and unavailable reranking falls back deterministically.

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。

Run a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.

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Diagnoses, remediates, and manages Google Cloud Identity and Access Management (IAM) access issues. Supports two distinct operational modes: (1) Requester Flow for developers encountering access denials (capturing error context, self-service PAM JIT activations, elevated developer self-remediation, or logging structured tickets), and (2) Resolver Flow for privileged administrators (authoritative Policy Troubleshooter analysis, deny policy exemptions, least-privilege role discovery, and PAM/IAM provisioning).

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Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when interacting with gcsfuse: decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size file, stat, and list caches, tune mount flags or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace/HNS, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or bill spikes with gcsfuse metrics. Covers mount semantics, gcsfuse CLI and config files, GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or fully POSIX-compliant shared file systems (Filestore, Managed Lustre).

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。

Manages GKE storage, including PVCs, PersistentVolumes, Filestore, and GCS FUSE. Use when configuring GKE storage, creating PVCs, or setting up GCS FUSE on GKE. For diagnosing storage failures (volume attach/mount errors, disk performance/node storage pressure, or Cloud Storage FUSE OOM), use the gke-storage-troubleshooting skill instead. Don't use for database administration or replication strategies outside volume provisioning 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。

Diagnoses and resolves Google Cloud Filestore client mount failures, permission errors (EACCES), and network timeouts (ETIMEDOUT). Use when an NFS mount hangs or fails from a Compute Engine VM, GKE pod, Cloud Run service, or Vertex AI workload, when `mount.nfs` reports "Connection timed out" or "access denied by server", when checking whether VPC ingress firewall rules or `nfsExportOptions` allow a client IP, or when a previously working Filestore share suddenly stops mounting after an administrative change. Don't use for Cloud Storage (GCS) buckets, Persistent Disk, or Cloud NetApp Volumes, and don't use for Filestore capacity scaling or backup and export-policy auditing.

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Diagnoses, predicts, and mitigates node disruptions during Compute Engine host maintenance and hardware or software maintenance events for GPU and TPU workloads on GKE. Use when diagnosing node disruptions, predicting host maintenance events on GPU/TPU nodepools, inspecting node interruption PromQL metrics, auditing node taints, or configuring workload protection strategies (graceful termination, opportunistic maintenance, PodDisruptionBudgets). Don't use for general GKE cluster creation, network policy configuration, or non-disruption workload deployment.

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。

Manages GKE application onboarding, covering containerization, deployment manifests, and migration. Use when onboarding or deploying an application to GKE for the first time, or containerizing an app for GKE. Don't use for general GKE cluster administration or upgrades (use gke-basics or gke-upgrades instead).

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。

Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations. Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances (e.g. Cloud SQL) or other GCP databases.

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。