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.
49.105 skill-uri din 2.358 de depozite · actualizat acum 26 de minute
49.103 skill-uri
- inbox-placement-monitoraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "track where my emails are actually landing after I send", "read my seed-list inbox vs spam vs promotions results", "trend my Gmail Postmaster / Microsoft SNDS reputation", or "did placement drop after my last send"; produces a per-provider inbox/spam/promotions placement read, a domain/IP reputation trend from Postmaster + SNDS, a send-over-send delta with named regressions, and a reusable SEND-S placement snapshot on your own exported telemetry. Not for the pre-send SPF/DKIM/DMARC auth pre-flight — use deliverability-qa; not for computing the EQS or running the vetoes — use email-quality-auditor. 邮件收件箱落点监测/收件箱vs垃圾邮件/Postmaster声誉趋势TestareFără avertismente★ 3,1 K↓ —
- paperclip-task-bridgepaperclipai/paperclipCreate, comment on, update, and list Paperclip tasks from Hermes using scoped Paperclip API credentials.ProductivitateFără avertismente★ 110,2 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↓ —
- tao-train-nvpanoptix3dNVIDIA/skillsNVPanoptix3D for panoptic 3D scene reconstruction from posed RGB images. Produces 3D panoptic segmentation (semantic, instance, and panoptic masks) with occupancy completion. Built on a VGGT backbone with a Mask2Former-style head and 3D frustum reconstruction. Use when training, evaluating, exporting, or running inference for a TAO NVPanoptix3D model. Trigger phrases include "train NVPanoptix3D", "panoptic 3D reconstruction", "3D scene segmentation", "occupancy completion".AlteleFără avertismente★ 3,8 K↓ —
- report-regressionstrailofbits/skillsUse when assembling or refreshing an evidence-linked regression report from saved campaign decisions.MarketingFără avertismente★ 8 K↓ —
- golang-error-handlingsamber/cc-skills-golangIdiomatic Golang error handling — creation, wrapping with %w, errors.Is/As, errors.Join, custom error types, sentinel errors, panic/recover, the single handling rule, structured logging with slog, HTTP request logging middleware, and samber/oops for production errors. Built to make logs usable at scale with log aggregation 3rd-party tools. Apply when creating, wrapping, inspecting, or logging errors in Go code. For samber/oops specifics → See `samber/cc-skills-golang@golang-samber-oops` skill; for slog handler ecosystem → See `samber/cc-skills-golang@golang-samber-slog` skill.PlanificareFără avertismente★ 3,8 K↓ —
- tao-train-pointpillarsNVIDIA/skillsPointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".MediaFără avertismente★ 3,8 K↓ —
- performing-causal-analysisforyourhealth111-pixel/Vibe-SkillsEstimate causal effects from existing data. Use when fitting or interpreting DiD, ITS, synthetic control, regression discontinuity, or other treatment-effect analyses, including robustness checks and counterfactual plots. For choosing a study design before analysis, use designing-experiments instead.DesignFără avertismente★ 3,8 K↓ —
- principle-build-the-levermichael-denyer/pstack-claudeApply to any non-trivial work, not just bulk work: edits, migrations, analyses, checks. Build the tool that does it or proves it (codemod, script, generator, or a skill your subagents follow) instead of working by hand. The tool is the artifact a reviewer can rerun.RedactareFără avertismente★ 3,8 K↓ —
- tao-train-oneformerNVIDIA/skillsOneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries. Use when training, evaluating, exporting, quantizing, or running inference for a TAO OneFormer model. Trigger phrases include "train OneFormer", "universal segmentation", "task-conditioned segmentation", "panoptic / instance / semantic in one model".MediaFără avertismente★ 3,8 K↓ —
- kiro-spec-designgotalab/cc-sddCreate comprehensive technical design for a specificationDesignFără avertismente★ 3,7 K↓ —
- principle-type-system-disciplinemichael-denyer/pstack-claudeApply when designing types, reviewing a function signature, or writing code in any statically-typed language. Make illegal states unrepresentable, brand semantic primitives, parse external data at boundaries, exhaust variants, derive from authoritative schemas.RedactareFără avertismente★ 3,8 K↓ —
- principle-exhaust-the-design-spacemichael-denyer/pstack-claudeApply when facing a novel UI interaction or architectural decision with no precedent in the codebase. Build 2-3 competing prototypes and compare side by side before committing.DesignFără avertismente★ 3,8 K↓ —
- torchdrugforyourhealth111-pixel/Vibe-SkillsGraph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.ȘtiințăFără avertismente★ 3,8 K↓ —
- create-verification-skillmichael-denyer/pstack-claudeGenerate a project-local verification skill that drives your app the way a user does — any language, framework, or platform. Use for /create-verification-skill, "make a control skill for this repo", "make a driver skill for this repo", or when a project has no scripted way to prove UI/CLI/service behavior.DesignFără avertismente★ 3,8 K↓ —
- make-pr-easy-to-reviewmichael-denyer/pstack-claudePrepare PRs for review by cleaning noisy history, improving PR descriptions, and adding reviewer guidance without changing code behavior. Use for "make this easy to review", "tidy this PR", "clean up commits", or "annotate the diff".InginerieFără avertismente★ 3,8 K↓ —
- create-formal-verification-skillmichael-denyer/pstack-claudeGenerate a project-local skill that formally verifies the code where a bug costs the most and tests reach the least, in any language, with whichever verification tool fits. Use for /create-formal-verification-skill, "model-check this race", "prove this invariant", or when concurrency, retries, state machines, parsers, or unsafe code need more than tests.TestareFără avertismente★ 3,8 K↓ —
- story-bank-builderaaron-he-zhu/aaron-marketing-skillsUse when the user asks to "build a story bank", "collect our origin and customer stories", or "assemble reusable proof stories for the message"; assembles reusable narrative units — origin, founder, customer, transformation, and proof stories — each tagged to a claims-ledger ID and a message-house pillar, with every proof labeled Measured / User-provided / [needs source]. Not for authoring the message house or pillars — use message-system-architect; not for brand voice or naming rules — use brand-language-codifier; not for finished long-form prose — use content-writer; not for adjudicating whether a proof is true — use offer-claims-registry. 品牌故事库/起源客户转化/证据故事单元RedactareFără avertismente★ 3,1 K↓ —
- correctmichael-denyer/pstack-claudeFind the mistakes agents keep repeating in this repo and make each one impossible. Try architecture first, then types, then a lint whose error names the fix, then a test, and write docs last. Prove each check fails on a real past mistake. Repeat this each time the operator corrects you. Use for /correct.TestareFără avertismente★ 3,8 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★ 3,8 K↓ —
- jetson-video-pipelineNVIDIA/skillsUse when planning, executing, and independently validating Jetson Video Codec SDK or PyNvVideoCodec encode/decode, transcode, segmentation, container decode, AV1, or concise acceptance workflows.MediaFără avertismente★ 3,8 K↓ —
- benchmark-checklistmichael-denyer/pstack-claudeVet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it. Use when you run a benchmark or report a speedup or regression you measured.AlteleFără avertismente★ 3,8 K↓ —
- narrative-registryaaron-he-zhu/aaron-marketing-skillsUse when the user asks to record/query the brand narrative canon, tagline, message hierarchy, voice/naming rules, or a canon re-version; curates complete versioned canon events through the append-only narrative stream and derived views. Not for TALE scoring — use narrative-quality-auditor; not for authoring the system — use message-system-architect. 品牌叙事台账/canon 记录/语气与命名规范PlanificareFără avertismente★ 3,1 K↓ —
- kiro-spec-designgotalab/cc-sddCreate comprehensive technical design for a specificationDesignFără avertismente★ 3,7 K↓ —Apare și în 4 alte depozite
offensive-wpa-enterprise
SnailSploit/Claude-Red
MarketingActualizat 12 oct. 2026
De la autor
WPA/WPA2/WPA3-Enterprise (802.1X / EAP) attack methodology — EAP method identification (PEAP-MSCHAPv2, EAP-TTLS, EAP-TLS, EAP-GTC, EAP-PWD, EAP-FAST), evil-twin RADIUS attacks with eaphammer for credential capture, MSCHAPv2 challenge-response cracking, EAP-TLS client certificate theft paths (DPAPI, NDES, AD CS auto-enrollment), supplicant validation bypass (missing server cert validation, missing CN pinning, BYOD misconfigurations), and post-capture pivots into AD via cracked domain credentials. Use for corporate Wi-Fi engagements where the network is 802.1X authenticated.
Instalare
npx skills add SnailSploit/Claude-Red --skill offensive-wpa-enterprise -a claude-code
Se instalează în .claude/skills/offensive-wpa-enterprise/ · 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 instrucțiuniFolosește rețeauaLicență: MIT
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- SKILL.md