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45.198 de skill-uri din 2.196 de depozite · actualizat acum 2 minute
45.198 de skill-uri
- sn-da-large-file-analysisOpenSenseNova/SenseNova-Skills万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取（iter_rows 支持 10 万行以上）、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**：①数据行数 ≥ 10k（由 sn-da-excel-workflow 的行数评估步骤触发）；②用户出现触发词：大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing；③直接使用 pd.read_excel() 导致超时或内存溢出；④用户明确要求对大规模数据集进行高性能处理。仅不用于：小于 10k 行的常规 Excel 分析（使用 sn-da-excel-workflow 即可）。DocumenteFără avertismente★ 5,9 K↓ —
- k6-test-maintenancegrafana/skillsMaintain and improve existing k6 test scripts. Covers threshold tightening based on trend data, version migration between k6 releases, auto-fixing tests when the underlying service changes, refactoring for cleanliness, and auditing scripts against current best practices from docs. Use when the user asks to fix a failing k6 test, tighten thresholds, migrate a script to a new k6 version, refactor a test, update a script after a service change, or improve a script with best practices. Trigger on phrases like "fix my k6 test", "tighten my thresholds", "migrate to k6 v2", "update my test script", "refactor this k6 test", "my test is failing after a deploy", "apply best practices to my script", "modernize my k6 test", or "the service changed and my test broke". Also trigger when another skill (k6-trend-analysis or k6-cloud-investigate-test) hands off with a recommendation to edit a script. Maintains existing scripts; to author a new test use the k6 skill, or k6-browser-test for a browser test.OficialTestareFără avertismente★ 290↓ —
- adaptive-metricsgrafana/skillsCut Grafana Cloud Metrics cost by shrinking active-series count with Adaptive Metrics aggregation rules — auto-recommendations from query history, custom exact/regex rules, label-drop config, unused-metric detection, and Alloy remote_write fallback. Use when investigating a high Mimir/Grafana Cloud bill, hunting high-cardinality labels (`pod_uid`, `service_instance_id`, `version`), pre-aggregating counters/gauges, dropping unused metrics, or measuring `grafanacloud_instance_active_series` before/after — even when the user says "reduce cardinality", "too many series", "metrics spend", "active series count is exploding", or "drop the version label" without naming Adaptive Metrics.OficialFinanțeFără avertismente★ 290↓ —
- range-reading-and-large-file-analysisOpenSenseNova/SenseNova-Skills读取多 Sheet Excel 文件，根据数据量动态选择处理策略，支持特定区域数据提取、大文件 Parquet 转换、统计分析及可视化图表生成。DocumenteFără avertismente★ 5,9 K↓ —
- large-file-parquet-analysis-and-highlightOpenSenseNova/SenseNova-Skills当Excel文件总行数超过1万行时，通过转换为Parquet格式提升读取性能，提取目标指标并计算最大值，最后将结果输出为Excel并对特定行进行高亮标注。DocumenteFără avertismente★ 5,9 K↓ —
- grouped-statisticsOpenSenseNova/SenseNova-Skills对多 Sheet 的 Excel 文件进行行数统计、数据合并与前向填充。DocumenteFără avertismente★ 5,9 K↓ —
- k6-trend-analysisgrafana/skillsAnalyze Grafana Cloud k6 test run trends over time. Detects slow metric drift (e.g., P95 latency creeping up while still passing thresholds), computes headroom to thresholds, flags anomalies, and recommends threshold tightening. Use when the user asks about test performance trends, wants to know if metrics are degrading, asks whether thresholds should be tightened, or wants a health check across recent runs for a specific test. Trigger on phrases like "how is my test trending", "is P95 getting worse", "check for performance regression", "should I tighten thresholds", "are my tests degrading", "show me trends for test X", "analyze my k6 test runs", or "is my test getting slower". Also trigger when a user asks to check all tests in a project -- run this skill once per test and synthesize.OficialTestareFără avertismente★ 290↓ —
- invalid-data-cleaningOpenSenseNova/SenseNova-Skills用于大规模Excel数据的预处理，通过统计总行数判断是否转换为Parquet格式以提升读写效率，并使用正则表达式清洗指定文本列（如仅保留中文字符），最后导出清洗后的文件并提供下载链接。DocumenteFără avertismente★ 5,9 K↓ —
- condition-filtering-and-large-file-optimizationOpenSenseNova/SenseNova-Skills根据数据规模动态选择处理策略。AlteleFără avertismente★ 5,9 K↓ —
- excel-smart-analysis-and-cleaningOpenSenseNova/SenseNova-Skills对多 Sheet Excel 进行智能清洗、跨表核对与可视化分析。。DocumenteFără avertismente★ 5,9 K↓ —
- performance-rcagrafana/skillsInvestigates CPU, memory, and contention problems with Grafana Pyroscope profiles via the gcx CLI. Compares affected and baseline workloads, locates changed application stacks, and tests root-cause hypotheses against symptom and change evidence. Use when a service shows high CPU, growing memory, GC pressure, lock contention, or hot functions, when code regressed after a deploy, or when given a suspect service, flame graph, trace, or profiling anomaly report. For profiling setup use pyroscope; for profilecli-based analysis use profilecli-insights.OficialTestareFără avertismente★ 290↓ —
- chart-embedded-exportOpenSenseNova/SenseNova-Skills从结构化数据中提取分类分布执行清洗与统计，生成多维度交叉分析、高分辨率对比图表及包含下载链接的完整分析报告，适用于大文件处理与嵌入式可视化场景。AlteleFără avertismente★ 5,9 K↓ —
- cost-managementgrafana/skillsCut your Grafana Cloud bill by attributing spend to teams and reducing telemetry volume. Covers FOCUS-compliant billing dashboards, cost-attribution labels in Alloy, Adaptive Metrics (cardinality reduction), Adaptive Logs (drop/sample), Adaptive Traces (tail sampling), usage alerts, and an optimization checklist. Use when investigating a high Grafana Cloud bill, attributing observability cost to a team or service, reducing active series / log bytes / trace spans, or setting up usage / quota alerts — even when the user says "our Grafana bill is too high", "who's burning the most metrics", "drop debug logs", "sample our traces", or "alert me before we hit quota" without naming Cost Management.OficialDevOpsFără avertismente★ 290↓ —
- excel-conditional-comparison-and-large-file-processingOpenSenseNova/SenseNova-Skills对比Excel多表中的特定系数并对异常值进行颜色标记。DocumenteFără avertismente★ 5,9 K↓ —
- grafana-scenesgrafana/skillsBuild Grafana plugin pages using the @grafana/scenes framework. Use when creating new scene pages, adding panels/visualizations, setting up drilldown navigation, defining variables, configuring query runners, building table/timeseries/stat panels, or extending SceneObjectBase for custom scene objects. Triggers on any work involving SceneApp, SceneAppPage, EmbeddedScene, SceneQueryRunner, SceneDataTransformer, PanelBuilders, SceneFlexLayout, QueryVariable, or drilldown/tab configuration in Grafana plugins.OficialAlteleFără avertismente★ 290↓ —
- large-file-conditional-formattingOpenSenseNova/SenseNova-Skills根据Excel总行数自动切换Parquet加速读取，计算特定维度的时间序列平均值，并使用openpyxl输出带有条件格式（如低于均值标绿）和自定义样式的分析报告。DocumenteFără avertismente★ 5,9 K↓ —
- antislopmiqdadbadjuber/anti-slopAnti Slop: Rules for AI Coding Agents. The core filter. Load always to stop generic AI slop.InginerieFără avertismente★ 7,2 K↓ —
- numeric-format-normalizationOpenSenseNova/SenseNova-Skills对 Excel 数据进行数值格式标准化与清洗，支持大规模数据的 Parquet 转换流程，并完成关键指标的合计核对与结果文件导出。DocumenteFără avertismente★ 5,9 K↓ —
- get-prompt-from-imagewuyoscar/GPT-Image2-SkillAnalyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts. Use when the user asks to recreate, imitate, reverse-engineer, or extract prompts from photographs, illustrations, 3D renders, products, characters, landscapes, typography, logos, posters, or other visual references. Do not use for requests that only require OCR or an ordinary image description.MediaFără avertismente★ 5,9 K↓ —
- line-chart-visualizationOpenSenseNova/SenseNova-Skills提取结构化数据并进行特征清洗与聚类分析，生成包含趋势对比、分布特征与参数敏感性的多维度综合可视化图表，适用于各类趋势预测与多维对比场景。AlteleFără avertismente★ 5,9 K↓ —
- binlog-generationdotnet/skillsGenerate MSBuild binary logs (binlogs) for build diagnostics and analysis. USE FOR: adding /bl:{} to any dotnet build, test, pack, publish, or restore command to capture a full build execution trace, prerequisite for binlog-failure-analysis and build-perf-diagnostics skills, enabling post-build investigation of errors or performance. Requires MSBuild 17.8+ / .NET 8 SDK+ for {} placeholder; PowerShell must quote the complete switch as '-bl:{}'. DO NOT USE FOR: non-MSBuild build systems (npm, Maven, CMake), analyzing an existing binlog (use binlog-failure-analysis instead), binlog MCP startup failures (use troubleshoot-binlog-mcp).TestareFără avertismente★ 5,7 K↓ —
- dotnet-aot-compatdotnet/skillsMake .NET projects compatible with Native AOT and trimming by systematically resolving IL trim/AOT analyzer warnings. USE FOR: making projects AOT-compatible, fixing trimming warnings, resolving IL warnings (IL2026, IL2070, IL2067, IL2072, IL3050), adding DynamicallyAccessedMembers annotations, enabling IsAotCompatible. DO NOT USE FOR: publishing native AOT binaries, optimizing binary size, replacing reflection-heavy libraries with alternatives. INVOKES: no tools — pure knowledge skill.AlteleFără avertismente★ 5,7 K↓ —
- mongodb-schema-designmongodb/agent-skillsMongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".OficialDesignFără avertismente★ 191↓ —Apare și în 3 alte depozite
- godot-shadersgamedev-skills/awesome-gamedev-agent-skillsWrite Godot 4.7 shaders in the Godot Shading Language: canvas_item shaders for 2D and spatial shaders for 3D, with vertex/fragment functions, uniforms (source_color, hint_range), TIME/UV animation, and screen-reading via hint_screen_texture. Use when authoring .gdshader files, writing fragment/vertex code, making 2D/3D visual effects, or porting 3.x shaders (SCREEN_TEXTURE, hint_color) to 4.x.MediaFără avertismente★ 4,6 K↓ —
doca-dpa
NVIDIA/skills
MediaActualizat acum 4 ore
De la autor
Use this skill when the user is doing hands-on DOCA DPA host-side work on a BlueField — creating the `doca_dpa` Core context, loading a DPACC-compiled DPA app image (`doca_dpa_app`), creating DPA threads, launching kernels via `doca_dpa_kernel_launch_update_*`, draining `doca_dpa_completion`, running `doca_dpa_cap_*` discovery, choosing between the DPA comm component (inter-DPA messaging) and the DPA verbs component (in-kernel RDMA), or debugging `DOCA_ERROR_*` from `doca_dpa_*`. Trigger even without "DOCA DPA" or "Data-Path Accelerator": "run compute on the DPA from my host", "DPA kernel hangs, no completion", "DOCA_ERROR_DRIVER on launch", "DOCA/DPACC version skew", or "does this BlueField expose a DPA". Route elsewhere for DPA-side kernel programming itself, DPACC compiler internals, host↔DPU messaging (doca-comch), host-side RDMA (doca-rdma), and GPU-initiated networking (doca-gpunetio).
Instalare
npx skills add NVIDIA/skills --skill doca-dpa -a claude-code
Se instalează în .claude/skills/doca-dpa/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Doar instrucțiuniNu am văzut acces la rețeaLicență: APACHE-2.0
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De ce 90
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Proveniență83
Întreținere100
Licență100
Adopție57
Fișiere (8)
- BENCHMARK.md
- CAPABILITIES.md
- SKILL.md
- SKILLCARD.yaml
- TASKS.md
- evals/evals.json
- skill-card.md
- skill.oms.sig