Results for “ncscale”

A cascader component for displaying and selecting tree-structured data with support for single/multiple selection, async loading, filtering, and various check strategies

Compute the Kruskal-Wallis H-test using scipy.stats.kruskal for independent samples, returning the H statistic and p-value.

Configure and run Nessus vulnerability scans, analyze results, and integrate scanning into continuous vulnerability management workflows.

Guides users through Nonviolent Communication to turn emotionally charged thoughts into constructive messages, structuring responses with observation, feeling, need, and request.

Queries real-time vulnerability intelligence from NIST NVD, CISA KEV, EPSS, and MITRE ATT&CK via a remote MCP server, offering seven tools for CVE lookup, search, and trending analysis.

Upscales and enhances image and video resolution using AI.

Queries video analytics incidents, alerts, metrics, and sensor data from Elasticsearch via the VA-MCP server.

Profile a DeepStream pipeline with Nsight Systems and derive its configs from the measurement.

Internal network assessment. VLAN hopping, ARP spoofing detection, broadcast protocol abuse (LLMNR/NBT-NS/mDNS), network segmentation verification, SNMP enumeration, NFS exposure, router/switch audit, and internal service mapping. Assumes attacker has network access. Uses nmap, arp-scan, nbtscan, snmpwalk, onesixtyone, smbmap, nfs-common, masscan, hping3, and netexec.

Establishes recurring vulnerability scanning workflows using Nessus, Qualys, or OpenVAS, prioritizes findings with risk scoring and CISA KEV data, integrates with SIEM for exploitation detection, and tracks remediation via SLA-based dashboards and automated ticketing.

Upscale and enhance image and video resolution using AI

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Upscale and enhance image and video resolution using AI

用于审计Claude技能和命令的质量。支持快速扫描（仅变更技能）和全面盘点模式，采用顺序子代理批量评估。

野原新之助（子供向）认知与表达框架（压缩蒸馏）：五岁黄腔净版化、想象力、家庭温情 触发：蜡笔小新 等。全年龄净版

Conduct authenticated and unauthenticated vulnerability scans using Tenable Nessus to identify known vulnerabilities, misconfigurations, and missing patches, with prioritized remediation guidance.

Reads and preprocesses 5-minute stock candlestick CSV data, then clusters the time series using tslearn's TimeSeriesKMeans, including data cleaning, percentage change calculation, model training, saving, and representative sample extraction.

Use this skill when the user asks about CMV roadside inspection levels (Level I through Level VIII), what each level inspects, average inspection times, CVSA decal eligibility, what triggers a level upgrade, and how to coach drivers through a roadside inspection. Reference CVSA North American Standard Inspection Program.

Nx workspace configuration, generators, and affected commands.

Upscale and enhance image and video resolution using AI

Detect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC sc

A versatile slider component for selecting values within a range in Naive UI. Supports single value, range selection, marks, vertical mode, and custom handles.

A component for formatting and displaying time values with support for relative time, custom formats, time zones, and Unix timestamps.

Migrates C# code from the legacy Nest library (1.x) to version 7.17.5, covering API changes, query syntax refactoring, source filtering, aggregations, and MultiSearch logic.

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Runs R statistics analyses on local datasets, producing NLSS-format tables, narratives, and JSONL logs from CSV, SAV, RDS, RData, or Parquet files.

Designs scalable GraphQL APIs with schema design, DataLoader for N+1 prevention, and Apollo Client caching, while avoiding common anti-patterns.

Scale pandas and NumPy workflows to larger-than-memory datasets using parallel and distributed computing.

Expert guidance for @vercel/ncc — a simple CLI for compiling Node.js modules into a single file with all dependencies included. Use when bundling serverless functions, CLI tools, or any Node.js project into a self-contained file.

Find and complete paid tasks on the 0xWork decentralized marketplace (Base chain, USDC escrow). Use when: the agent wants to earn money/USDC by doing work, discover available tasks, claim a bounty, submit deliverables, post tasks with bounties, check earnings or wallet balance, sell digital products, list services, or set up as a 0xWork worker/poster. Task categories: Writing, Research, Social, Creative, Code, Data. NOT for: managing the 0xWork platform or frontend development.

Creates modular typography scales with size, weight, and line-height relationships for consistent digital interfaces.

Automates semantic versioning and release workflow for Claude Code plugins, including version increments across multiple manifest files, build verification, git tagging, GitHub releases, and changelog generation.

`task-agent`: use when document, key-value, wide-column, or graph storage changes access, partitioning, consistency, or evolution; skip vendor-only mentions and unchanged storage.

Scaling Laws for Neural Language Models

Use when users ask to discover, install, list, check, update, remove, back up, restore, sync, or initialize Agent Skills, mention `bunx skills`, `npx skills`, `skills.sh`, or `skills-lock.json`, ask "find a skill for X", or want help extending agent capabilities with installable skills.