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.
48.168 de skill-uri din 2.325 de depozite · actualizat acum 4 ore
48.168 de skill-uri
- baoyu-wechat-summaryJimLiu/baoyu-skillsSummarizes WeChat group chat highlights into a structured digest using the local wx-cli binary (https://github.com/jackwener/wx-cli). Generates a normal digest by default; a roast (毒舌) version is opt-in. Maintains per-group history (history.json + history-digests.jsonl), per-user profiles, and per-group fact memory (memory.md) across runs, with privacy guardrails baked in. Use when the user asks to "总结群聊", "群聊精华", "群聊摘要", "summarize group chat", "group chat digest", mentions a WeChat group name with a time range, says "帮我看看 XX 群最近聊了什么", "XX 群有什么值得看的", or asks to "回溯画像" / "初始化画像" / "backfill profiles". Adds the roast version when the user says "毒舌版", "roast 版", "再来个毒舌的", or similar.ProductivitateFără avertismente★ 27,1 K↓ —
- unmergeNoudavepoon/buildwithclaudeSplit a flat image (PNG, JPG or WebP) into separate transparent PNG layers with Unmerge, with the hidden parts behind objects filled in. Use when the user wants to separate an image into layers, pull a subject or text off its background as its own layer, make an editable layered version of a poster, illustration or screenshot, or "unflatten" an image. Needs an Unmerge API key in UNMERGE_API_KEY.MediaFără avertismente★ 3,7 K↓ —
- apify-cost-tuningjeremylongshore/tons-of-skills-marketplaceOptimize Apify platform costs through memory tuning, compute unit management, and proxy budgeting. Use when analyzing Apify billing, reducing Actor run costs, or implementing usage monitoring and budget alerts. Trigger with "apify cost", "apify billing", "reduce apify costs", "apify pricing", "apify expensive", "apify budget", "compute units".ProductivitateFără avertismente★ 2,9 K↓ —
- provider-test-patternshashicorp/agent-skillsTerraform provider acceptance test patterns using terraform-plugin-testing with the Plugin Framework. Covers test structure, TestCase/TestStep fields, ConfigStateChecks with custom statecheck.StateCheck implementations, plan checks, CompareValue for cross-step assertions, config helpers, import testing with ImportStateKind, sweepers, and scenario patterns (basic, update, disappears, validation, regression), and ephemeral resource testing with the echoprovider package. Use when writing, reviewing, or debugging provider acceptance tests, including questions about statecheck, plancheck, TestCheckFunc, CheckDestroy, ExpectError, import state verification, ephemeral resources, or how to structure test files.OficialTestareFără avertismente★ 910↓ —
- terraform-testhashicorp/agent-skillsComprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.OficialTestareFără avertismente★ 910↓ —
- attio-rate-limitsjeremylongshore/tons-of-skills-marketplaceAnalyze and design an Attio request governor with separate read and write budgets, query-score awareness, bounded retries, and observable backpressure. Use when an Attio integration receives 429 responses or needs safe concurrency controls. Trigger with "Attio rate limits", "Attio 429", or "throttle Attio requests".DesignFără avertismente★ 2,9 K↓ —
- adobe-hello-worldjeremylongshore/tons-of-skills-marketplaceProve one Adobe API connection with a current, read-only or synthetic operation and a content-safe receipt. Use during onboarding before any production workflow. Use when the task requires adobe minimal access proof. Trigger with "Adobe hello world", "test Adobe connection", or "verify Adobe entitlement".TestareFără avertismente★ 2,9 K↓ —
- rust-reviewtrailofbits/skillsPerforms comprehensive Rust security review for safe/unsafe boundary issues, memory safety in unsafe blocks, concurrency hazards, panic-induced DoS, FFI safety, and async runtime mistakes. Use when auditing Rust crates, services, or libraries — particularly those with `unsafe`, FFI, or concurrent code.InginerieFără avertismente★ 7,9 K↓ —
- freshie-inventoryjeremylongshore/tons-of-skills-marketplaceManage the freshie ecosystem inventory database — a CMDB tracking all plugins, skills, packs, and compliance grades across 51 SQLite tables. Use when checking ecosystem health, running discovery scans, validating compliance, remediating issues, querying inventory data, comparing runs, exporting data, or generating status reports. Trigger with "freshie status", "inventory scan", "ecosystem audit", "grade report", "compliance check", "remediate skills", "query freshie", "compare runs", "export grades", or "freshie report".DateFără avertismente★ 2,9 K↓ —
- hex-debug-bundlejeremylongshore/tons-of-skills-marketplaceCollect Hex debug evidence for support tickets and troubleshooting. Use when encountering persistent issues, preparing support tickets, or collecting diagnostic information for Hex problems. Trigger with phrases like "hex debug", "hex support bundle", "collect hex logs", "hex diagnostic".InginerieFără avertismente★ 2,9 K↓ —
- vercel-rate-limitsjeremylongshore/tons-of-skills-marketplaceHandle Vercel API rate limits, implement retry logic, and configure WAF rate limiting. Use when hitting 429 errors, implementing retry logic, or setting up rate limiting for your Vercel-deployed API endpoints. Trigger with phrases like "vercel rate limit", "vercel throttling", "vercel 429", "vercel retry", "vercel backoff", "vercel WAF rate limit".DevOpsFără avertismente★ 2,9 K↓ —
- image-enhanceZJU-REAL/Easel图片增强 / 放大 / 变清晰：高质量放大（Lanczos 2x/4x）+ 去噪 + 锐化 + 自动对比度/饱和度，改善偏糊、偏暗、噪点多的图片。当用户说 图片放大、图片变清晰、提高清晰度、图片增强、去噪点、锐化、图片太糊了、放大到高清、提升画质、优化图片、图片调亮调色 时使用。基于 shared/scripts/img_enhance.py（Pillow+OpenCV）。注意：这是传统增强非 AI 超分，凭空生成细节请用 ai-image-gen 图生图。与 image-editing 区别：那个做缩放/裁切/水印等常规操作，本 SKILL 专做画质提升。MediaFără avertismente★ 4,2 K↓ —
- principle-minimize-reader-loadmichael-denyer/pstack-claudeApply when reviewing or shaping code that's hard to trace. Count layers between question and answer, and hidden state in the reader's head; collapse one-caller wrappers and shrink mutable scope.InginerieFără avertismente★ 3,7 K↓ —
- ad-creative-builderaaron-he-zhu/aaron-marketing-skillsUse when the user asks to "write ad copy", "generate RSA headlines", or "build ad creative at volume"; produces ad units — RSA headlines/descriptions, hooks, and an angle matrix — message-matched to the destination landing page. Not for scoring an ad account — use ad-account-auditor; not for the post-click page — use landing-optimizer; not for organic articles — use content-writer. 广告创意/广告文案/RSA标题MarketingFără avertismente★ 3 K↓ —
- brief-generatoraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "create an influencer brief" or "write a campaign brief"; produces a structured creator brief with deliverables, key messages, creative direction, timeline, disclosure rules, and compensation terms. Not for choosing how to split spend across creators — use budget-optimizer. 达人合作简报/创作者BFMarketingFără avertismente★ 3 K↓ —
- reasoningjeremylongshore/tons-of-skills-marketplaceUse BEFORE answering analytical, diagnostic, planning, or multi-step reasoning questions. Trigger phrases include "should I X or Y", "why is X happening", "what's the best approach", "what are the tradeoffs", "help me think through", "diagnose", "root cause", "plan/design X", "what are the implications of", "compare these approaches". Also fires on cross-domain analysis, strategy questions, architecture decisions, or anything requiring multiple factors to be weighed before responding. The skill calls the reasoning MCP tool to retrieve a cognitive scaffold (named failure pattern, executable procedure, suppression vectors, falsification test) the model absorbs internally before generating its response. Catches causal shortcuts, premature conclusions, generic templates, and surface pattern matching that produce confidently-wrong answers. Do NOT trigger for simple factual lookups, syntax questions, file reads, code execution, or restating the user's input.TestareFără avertismente★ 2,9 K↓ —
- principle-foundational-thinkingbacknotprop/pstackApply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.RedactareFără avertismente★ 3,3 K↓ —Apare și în 2 alte depozite
- ai-image-genZJU-REAL/Easel通用 AI 生图：文生图 / 图生图 / 图像变体。当用户说 AI 生图、AI 画图、文生图、图生图、生成图片、生成配图、图像生成、AI 出图、AI 作图、换图、改图、图像编辑、给我画一张、生成一张图 时使用。支持 OpenAI 兼容 API 与 apimart 异步 API，用户自备 API key。MediaFără avertismente★ 4,2 K↓ —
- skill-profile-managerZJU-REAL/Easel管理账号画像全生命周期：创建空白画像、编辑六维字段、更新记忆、切换、导出和对比。 当用户说“新建/编辑/更新/切换/导出/对比画像、写进画像记忆”时使用。 首次从社媒数据生成画像用 skill-profile-builder；只提炼语言风格用 skill-voice-builder；品牌首次入驻引导用 skill-brand-onboarding。AlteleFără avertismente★ 4,2 K↓ —
- datamodel-code-generatorActualizatdatamodel-code-generator/datamodel-code-generatorUse this skill when the user wants Python data models, Pydantic models, dataclasses, TypedDicts, msgspec structs, or type-safe Python classes generated from OpenAPI, AsyncAPI, JSON Schema, GraphQL, JSON/YAML/CSV sample data, MCP tool schemas, Protocol Buffers, XML Schema, Apache Avro, or existing Python model objects. Use it for requests such as "Pydantic models from this schema", "types for this API", "parse this JSON into classes", or "convert this spec into Python models". Prefer the datamodel-codegen CLI over hand-written model code whenever an input schema, API spec, sample data file, or Python model object exists.InginerieFără avertismente★ 4 K↓ —
- hypothesis-testingforyourhealth111-pixel/Vibe-SkillsProperty-based testing with Hypothesis for discovering edge cases and validating invariants. Use when implementing comprehensive test coverage, testing complex logic with many inputs, or validating mathematical properties and invariants across input domains. Triggered by: hypothesis, property-based testing, @given, strategies, generative testing.TestareFără avertismente★ 3,8 K↓ —
- jetson-print-bsp-infoNVIDIA/skillsUse when you need to print Jetson BSP info (L4T version, board configs, rootfs state) from a Linux_for_Tegra root on the host PC. This is an example skill.AlteleFără avertismente★ 3,8 K↓ —
- doca-dmaNVIDIA/skillsUse this skill when the user is doing hands-on DOCA DMA programming — bringing up a doca_dma context, configuring the single doca_dma_task_memcpy task type, sizing buffers via the doca_dma_cap_task_memcpy_* queries, setting LOCAL_READ_ONLY / LOCAL_READ_WRITE permissions on source / destination doca_mmap regions (plus doca_mmap_export_* for cross-peer copies), driving the progress engine, or debugging DOCA_ERROR_* returns. Trigger even when the user does not explicitly mention "DOCA DMA" or "doca_mmap" — typical implicit phrasings include "memcpy host buffer to BlueField without using the CPU", "offload a bulk copy to the DPU", "copy returns NOT_PERMITTED on first submit", "buffer too big for one DMA task", "task submitted but no completion", or "scatter-gather copy between two memory regions". Refuse and route elsewhere for cross-network copies (DOCA RDMA), producer/consumer messaging (DOCA Comch), DOCA Core / progress-engine internals, or DOCA install — those belong to other skills.InginerieFără avertismente★ 3,8 K↓ —
- doca-gpunetioNVIDIA/skillsUse this skill when the user is doing hands-on DOCA GPUNetIO programming — wiring a CUDA kernel on an NVIDIA GPU to a doca-eth queue via doca_gpu_eth_rxq / doca_gpu_eth_txq, standing up the per-CUDA-device doca_gpu context, designing the persistent CUDA kernel that drains the GPU-visible queue, running the dual capability check (DOCA cap-query plus cudaGetDeviceProperties), registering cudaMalloc pools via doca_buf_arr_create_*, or debugging DOCA_ERROR_* returns from the GPUNetIO API. Trigger even when the user does not explicitly mention "DOCA GPUNetIO" or "persistent kernel" — typical implicit phrasings include "CUDA kernel reading packets directly from the NIC", "GPU-initiated networking on BlueField", "DOCA_ERROR_DRIVER on doca_gpu_create", "nvidia_peermem not loaded", "kernel-per-packet is too slow", or "which GPU supports GPU-side packet I/O". Refuse and route elsewhere for general CUDA programming, DOCA Ethernet queue bring-up, DOCA DPA, or DOCA install — those belong to other skills.InginerieFără avertismente★ 3,8 K↓ —
jetson-set-target
NVIDIA/skills
AlteleActualizat ieri
De la autor
Switch the active Jetson target-platform pointer to an existing profile YAML. Use before customize/build/flash to change target; not for authoring profiles — use jetson-init-target instead.
Instalare
npx skills add NVIDIA/skills --skill jetson-set-target -a claude-code
Se instalează în .claude/skills/jetson-set-target/ · 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
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 90
Securitate100
Proveniență83
Întreținere100
Licență100
Adopție57
Fișiere (5)
- BENCHMARK.md
- SKILL.md
- evals/evals.json
- skill-card.md
- skill.oms.sig