Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
45.213 skill-uri din 2.196 de depozite · actualizat acum 32 de minute
45.213 skill-uri
- phaser-coregamedev-skills/awesome-gamedev-agent-skillsSet up and debug a Phaser 4 game: the Game config, the Scene lifecycle (init/preload/create/update), the asset loader, cameras, and cross-scene communication. Use when building or debugging a Phaser game — when the user mentions Phaser, Phaser.Game, Phaser.Scene, preload/create/update, this.load, this.add, or scene transitions. For Arcade Physics movement/collisions use phaser-arcade-physics.ȘtiințăFără avertismente★ 4,6 K↓ —
- performance-optimizationgamedev-skills/awesome-gamedev-agent-skillsFind and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object pooling, draw-call batching, fewer allocations/GC spikes, and asset budgets. Engine- neutral method that pairs with each engine's profiler. Use when the user mentions performance, optimize, low/dropping FPS, frame drops, stutter, lag, profiler, frame budget, draw calls, batching, garbage collection/GC spikes, object pooling, or "the game runs slow".AlteleFără avertismente★ 4,6 K↓ —
- unreal-cpp-gameplaygamedev-skills/awesome-gamedev-agent-skillsWrite Unreal Engine 5 C++ gameplay code: the UCLASS/UPROPERTY/UFUNCTION reflection macros, the Gameplay Framework (GameMode, Pawn, Character, PlayerController, Actor components), and the module Build.cs. Use when writing or debugging UE C++, deriving from AActor/ACharacter/ AGameModeBase, exposing properties to the editor or Blueprints, or when the user mentions Unreal C++, UCLASS, GENERATED_BODY, GameMode, ACharacter, or .Build.cs.RedactareFără avertismente★ 4,6 K↓ —
- skill-creatoranthropics/skillsCreate new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.OficialTestareFără avertismente★ 183,9 K↓ —Apare și în 10 alte depozite
- fleet-managementgrafana/skillsManage a fleet of Grafana Alloy collectors with Fleet Management — author Alloy pipelines once, target them via attribute matchers (`env="production"`, regex `region=~"us-.*"`), push remotely via OpAMP without restarting collectors. Covers pipeline create / update / matcher RPCs, collector attribute API, `remotecfg` bootstrap block (standalone + Helm), pre-deploy `alloy fmt` validation, the local Alloy UI at port 12345 for component health, and post-deploy `REMOTE_CONFIG_STATUS_APPLIED` verification. Use when standing up a Cloud Alloy fleet, pushing a config change to 200 collectors, hunting why one collector shows `REMOTE_CONFIG_STATUS_FAILED`, validating River syntax before saving, or wiring `discovery.kubernetes` → `prometheus.remote_write` — even when the user says "configure Alloy", "remote config the collectors", "push pipeline", "OpAMP", "collector is unhealthy", or "manage agent config centrally" without naming Fleet Management.OficialDevOpsFără avertismente★ 290↓ —
- mongodb-qe-size-estimationmongodb/agent-skillsEstimates the storage and memory impact of encrypting fields in collections with Queryable Encryption (QE) enabled. Do NOT use for collections that use Client-Side Field Level Encryption (CSFLE) instead of QE.OficialProductivitateFără avertismente★ 191↓ —Apare și în 2 alte depozite
- 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↓ —
- mirrord-db-branchingmetalbear-co/mirrordHelps users configure mirrord.json for database branching, enabling isolated database copies for safe development and testing. Use when the user wants to set up MySQL, MariaDB, PostgreSQL, MSSQL, MongoDB, Redis, DynamoDB, ClickHouse, Google Spanner, Amazon S3, turbopuffer, or generic branches, configure copy modes, connection sources, schema migrations, IAM authentication, or manage database branches.TestareFără avertismente★ 5,4 K↓ —
- k6-cloud-investigate-testgrafana/skillsInvestigate a Grafana Cloud k6 test — describe the script, list run history, identify pass/fail status, pull raw metric time-series and log lines for one or more runs, and (if asked) safely edit the test script. Use when the user asks about a specific k6 cloud test or run, gives a `/a/k6-app/tests/<id>` or `/a/k6-app/runs/<id>` URL, asks "is this test passing", "why are my k6 tests failing", "show me metrics for run X", "show me logs for run X", or wants to add thresholds / fix a failing test. Trigger this skill even when the user doesn't explicitly say "investigate" — pasted `/a/k6-app/...` URLs, "why did run X fail", "what happened with my test", "is my test healthy", "the latest run looks weird", "checks are failing but the run says passed", or any request to diagnose a Grafana Cloud k6 run all qualify.OficialTestareFără avertismente★ 290↓ —
- melonjs-mathmelonjs/melonJSUse this skill for vector and matrix maths in melonJS — Vector2d, Vector3d, their observable variants, Matrix2d, Matrix3d, and the math utility functions. Covers which methods mutate and which allocate, the vector pool and when clone() is the wrong tool, interpolation with lerp, slerp, damp and moveTowards, and the argument defaults that silently drop a component. Triggers on: Vector2d, Vector3d, ObservableVector2d, ObservableVector3d, Matrix2d, Matrix3d, vector, vector maths, dot, cross, normalize, length, distance, angle, lerp, slerp, damp, moveTowards, project, clamp, degToRad, radToDeg, clone, vector pool, vector3dPool, setMuted, setCallback, my vector is wrong, z is zero, scale ignores z., moveTowards ignores z, projectN, currentTransform, setTransform, matrix, transform matrix, column-major, val, Float32Array, basis matrix, orientation matrix, Noise, getNoise1d, flicker, wobble.AlteleFără avertismente★ 6,4 K↓ —
- statistical-distribution-and-outlier-analysisOpenSenseNova/SenseNova-Skills执行数值型数据的分布分析与异常值检测，支持通过正则表达式从文本中提取误差项并生成高分辨率的箱线图与直方图报告。AlteleFără avertismente★ 5,9 K↓ —
- anima-install-authjeremylongshore/tons-of-skills-marketplaceInstall the Anima SDK and configure authentication for Figma-to-code generation. Use when setting up design-to-code automation, configuring Figma token access, or initializing the @animaapp/anima-sdk for server-side code generation. Trigger with: "install anima", "setup anima", "anima auth", "anima figma token".DesignFără avertismente★ 2,9 K↓ —
- navan-sdk-patternsjeremylongshore/tons-of-skills-marketplaceDesign an application-owned Navan adapter pinned to the tenant's actual integration contract. Use when wrapping Booking API, Expense API, SFTP, or direct integration behavior. Trigger with "build a Navan client", "wrap Navan API", or "type Navan responses".DesignFără avertismente★ 2,9 K↓ —
- doca-staNVIDIA/skillsUse this skill when the user builds an NVMe-over-Fabrics storage target on BlueField with DOCA STA — instantiating doca_sta, declaring doca_sta_subsystem NQNs and namespaces over local NVMe disks via doca_sta_be, validating platform support with doca_sta_cap_is_supported, sizing I/O queue depth, or decoding DOCA_ERROR_* statuses such as IO_FAILED on NVMe reads. Also load it for implied asks like "Identify Controller times out over RoCE", "offload the nvmf target", "NVMe-oF Connect never completes", or "16 I/O queues at depth 1024 — supported?". Refuse and route to the proper owner for raw RDMA movement, packet I/O, steering rules, initiator-side NVMe, or SDK install.AlteleFără avertismente★ 3,7 K↓ —
- gsd:sketch-wrap-updavepoon/buildwithclaudePackage sketch design findings into a persistent project skill for future build conversationsDesignFără avertismente★ 3,7 K↓ —
- c-reviewtrailofbits/skillsPerforms comprehensive C/C++ security review for memory corruption, integer overflows, race conditions, and platform-specific vulnerabilities. Use when auditing native C/C++ applications, reviewing daemons or services for memory safety, or hunting integer overflow / use-after-free / race conditions in userspace code.InginerieFără avertismente★ 7,8 K↓ —
- property-based-testingtrailofbits/skillsWrites, reviews, and debugs property-based tests — Hypothesis, fast-check, proptest, jqwik, rapid, and Echidna or Medusa for Solidity invariants. Use whenever tests should cover a whole input domain instead of a hand-picked list of examples: encode/decode and serialize/deserialize pairs, parsers, canonicalizers and normalizers, validators, numeric and Decimal types, comparators and sort order, data structures, and smart-contract state invariants. Also use when adding cases to an existing @given, fast-check, or proptest suite, when judging whether existing property tests assert anything real, and when a generator has shrunk a counterexample and you need to tell a wrong property from a genuine bug. Not for coverage-guided binary fuzzing (libFuzzer, AFL), mutation-testing campaigns, static analysis, benchmarking, or end-to-end UI tests.TestareFără avertismente★ 7,8 K↓ —
- gitlab-automationdavepoon/buildwithclaudeAutomate GitLab project management, issues, merge requests, pipelines, branches, and user operations via Rube MCP (Composio). Always search tools first for current schemas.AlteleFără avertismente★ 3,7 K↓ —
- tao-train-codetrNVIDIA/skillsCo-DETR (CoDINO) for object detection. A DETR-family detector with collaborative hybrid assignment — auxiliary one-to-many heads supervise the encoder during training, giving strong closed-set accuracy at high inference cost. Use when training, evaluating, or running inference for a TAO Co-DETR model. Trigger phrases include "train Co-DETR", "run CoDINO", "codetr inference", "collaborative DETR", "autolabel detections with Co-DETR".AlteleFără avertismente★ 3,7 K↓ —
- offensive-cloudSnailSploit/Claude-RedCloud security attack methodology covering AWS, Azure, and GCP. Includes credential harvesting (IMDS, ~/.aws, env vars, leaked CI secrets, instance roles), enumeration with cloud-specific tools (pacu, ScoutSuite, Prowler, ROADtools, gcp_enum), privilege escalation paths (IAM PassRole, AssumeRole chains, Lambda/Functions privilege flips, Azure Owner-on-self, GCP serviceAccountTokenCreator), persistence techniques (IAM user/key creation, AAD app registration, GCP svc account key creation, EventBridge/Logic Apps backdoors), data exfiltration (S3/Blob/GCS, snapshot share, RDS/CosmosDB/Cloud SQL exfil), cloud-native lateral movement (cross-account assume, Azure AD multi-tenant, GCP project hierarchy), serverless attacks (Lambda env vars, layer hijack, Step Functions), Kubernetes-on-cloud (EKS/AKS/GKE-specific paths to node and AWS metadata), and CSPM evasion (CloudTrail blind spots, GuardDuty mute, Sentinel rule shaping). Use when the engagement scope is cloud accounts, when you've stolen cloud credentials, or wheSecuritateFără avertismente★ 9,3 K↓ —
- golang-popular-librariessamber/cc-skills-golangGolang library and framework selection — vetted production-ready options by category (web, database, testing, logging, messaging), new and experimental stdlib packages, standard-library-first tradeoffs, and maturity signals (maintenance, license, importer counts). Apply when the user asks for library suggestions, wants to compare alternatives, needs to choose a library for a specific task, or when a new dependency is being added to the project. Not for a specific library's API once chosen (→ See that library's dedicated skill, e.g. `samber/cc-skills-golang@golang-samber-lo`), nor for go.mod mechanics, upgrades, or vulnerability audits (→ See `samber/cc-skills-golang@golang-dependency-management` skill).SecuritateFără avertismente★ 3,7 K↓ —
- data-quality-frameworksforyourhealth111-pixel/Vibe-SkillsImplement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.TestareFără avertismente★ 3,8 K↓ —
- doca-argusNVIDIA/skillsUse this skill when the user is deploying or operating the DOCA Argus Service — the packaged BlueField-side runtime-security container that watches the BlueField and attached host for suspicious activity, integrity violations, and operational anomalies, and forwards findings to a SIEM (Splunk / ELK / Sentinel / syslog). Covers the four-axis config (detection policy, forwarding, sampling, host coverage), running the NGC container on BlueField Arm, and wiring the forwarder. Trigger even without "DOCA Argus" by name — typical implicit phrasings: "container green but no findings arrive", "false-positive flood in Splunk", or "runtime security on a fleet of BlueField-3s". Refuse and route elsewhere for installing DOCA, SIEM-side ingest stanzas, pre-baked detection-rule packs, and metrics observability (DOCA Telemetry). Argus is NVIDIA's currently- promoted runtime-security framework, superseding the older App Shield library; name it first for new runtime-security work.SecuritateFără avertismente★ 3,7 K↓ —
- single-cell-rna-qcanthropics/knowledge-work-pluginsPerforms quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.OficialAlteleFără avertismente★ 33,1 K↓ —
formatted-export-with-parquet
OpenSenseNova/SenseNova-Skills
DocumenteActualizat 9 oct. 2026
De la autor
从多Sheet Excel文件中识别指定条件的记录，并将筛选结果以整行标红格式导出为Excel文件，适用于数据清洗、条件筛选与可视化标记场景。
Instalare
npx skills add OpenSenseNova/SenseNova-Skills --skill formatted-export-with-parquet -a claude-code
Se instalează în .claude/skills/formatted-export-with-parquet/ · 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: MIT
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De ce 91
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Proveniență85
Întreținere100
Licență100
Adopție59
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- SKILL.md