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.
47.928 de skill-uri din 2.309 depozite · actualizat acum 23 de minute
47.928 de skill-uri
- memoryjeremylongshore/tons-of-skills-marketplaceUse when sharpening a perception or observation you ALREADY formed about conversation state, user behavior, drift, emotional shifts, or cross-turn patterns. Trigger phrases include "what did you notice about X", "the user keeps doing Y", "I sense something has changed", "is the user X-ing", "what does this pattern suggest", "what shifted across our turns", "am I missing something here", "why did the conversation move from X to Y", or any moment requiring verification of whether a felt signal is real or projection. The skill calls the memory MCP tool to retrieve a perception scaffold (perception failure, detection procedure, suppression vectors) that SHARPENS an observation you already have. It is NOT a substitute for observing first. Do NOT trigger for fact extraction, summarization, list-making, factual lookups, or write-heavy memory tasks (storing/retrieving structured data). Memory harness is filter/perception oriented; calling on write-heavy tasks produces scaffold paralysis.ProductivitateFără avertismente★ 2,9 K↓ —
- kiro-steeringgotalab/cc-sddManage {{KIRO_DIR}}/steering/ as persistent project knowledgeAlteleFără avertismente★ 3,7 K↓ —
- newsletter-monetization-planneraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "monetize my newsletter", "build a sponsorship rate card", or "model paid-subscription revenue"; produces a revenue model (paid tiers, ad/sponsorship inventory + CPM/flat rate card, referral/boost loops), a list-growth ↔ revenue projection, and honest-offer / disclosure checks for the SEND-D lever. Not for scoring the whole program or running D1 — use email-quality-auditor; not for the return math — use roi-calculator; not for the post-click page — use landing-optimizer. 邮件newsletter变现/赞助刊例/付费订阅测算MarketingFără avertismente★ 3 K↓ —
- comparison-cardZJU-REAL/Easel对比图/一图流：生成 A vs B 参数对比图、优劣势对比表、产品参数一图流。 用 HTML+CSS 渲染成可截图的视觉卡片，适合小红书/微博等平台分享。 使用时机：用户说"做个对比图"、"A vs B"、"参数对比"、"优劣对比"、 "一图流"、"对比表"、"哪个好"、"对比一下"。 和 chart-visualization 的区别：chart 做数据图表（柱状图/折线图），comparison-card 做对比表/一图流。 和 infographic 的区别：infographic 做多维信息图，comparison-card 专注 A vs B 对比。DesignFără avertismente★ 4,2 K↓ —
- lindy-hello-worldjeremylongshore/tons-of-skills-marketplaceCreate your first Lindy AI agent with a real trigger and action. Use when starting with Lindy, testing your setup, or learning basic agent workflow patterns. Trigger with phrases like "lindy hello world", "lindy example", "lindy quick start", "simple lindy agent", "first lindy".TestareFără avertismente★ 2,9 K↓ —
- subtitle-translateZJU-REAL/Easel字幕翻译 / 双语字幕：把已有字幕（SRT/VTT/ASS）翻译成目标语言，生成双语（原文+译文）或纯译文字幕，并可软挂载 / 硬烧录进视频。当用户说 字幕翻译、翻译字幕、双语字幕、中英字幕、给视频加翻译、SRT 翻译、字幕本地化、把字幕翻成中文/英文、字幕转双语 时使用。翻译由 LLM 完成，时间轴/格式/烧录由 shared/scripts/subtitle_ops.py 确定性处理。与 auto-subtitle 区别：auto-subtitle 是语音识别生成字幕，本 SKILL 是把已有字幕翻译成双语。AlteleFără avertismente★ 4,2 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↓ —
- spec-to-code-compliancetrailofbits/skillsCheck code against the documentation that specifies it - which requirements hold, which the code contradicts, which are absent, and what the code does that no document mentions. Use when comparing an implementation against a whitepaper, protocol spec, or design document.JuridicFără avertismente★ 7,9 K↓ —
- j-rigjeremylongshore/tons-of-skills-marketplaceSkill Refiner, the eval-guided improvement loop for SKILL.md files. Runs the bootstrap, score, propose, apply, and status cycle as a thin wrapper over the published @intentsolutions/refiner CLI, proposing safe, minimal, bounded SKILL.md edits and accepting an edit only when a held-out eval score strictly improves with no regression on any other case. Ships a 3-layer cost-tiered hook architecture (sinker, line, hook) that gates skill quality at edit time, end of turn, and commit time. Use when improving an existing skill, refining a SKILL.md against measured behavior, bootstrapping an eval set for a skill, or gating skill edits before they ship. Trigger with "/j-rig", "refine this skill", "bootstrap an eval set", "propose a skill edit", "promote the candidate", or "skill refiner status".RedactareFără avertismente★ 2,9 K↓ —
- technical-writingbacknotprop/pstackLayered technical-writing standard: Diátaxis structure, Google developer style sentences, STE instruction rules, Global English syntax. Use for /technical-writing or when writing or reviewing docs, RFCs, readmes, PR descriptions, or commit messages.RedactareFără avertismente★ 3,2 K↓ —
- tao-finetune-clipNVIDIA/skillsCLIP vision-language model for image-text retrieval, zero-shot classification, embedding extraction, ONNX export, and TensorRT deployment. Use when fine-tuning or training CLIP, running zero-shot classification, computing image embeddings, or deploying CLIP to ONNX/TensorRT. This is a single-action model skill; do not use it for an iterative weak-attribute improvement loop that keeps retraining and evaluating until progress stops, which belongs to tao-run-deft-pas.DevOpsFără avertismente★ 3,8 K↓ —
- hex-install-authjeremylongshore/tons-of-skills-marketplaceInstall and configure Hex SDK/CLI authentication. Use when setting up a new Hex integration, configuring API keys, or initializing Hex in your project. Trigger with phrases like "install hex", "setup hex", "hex auth", "configure hex API key".InginerieFără avertismente★ 2,9 K↓ —
- social-contentZJU-REAL/Easel通用多平台社媒内容（单条/兜底）：钩子文案、正文、标签策略和互动引导，主打**涨粉/互动/内容运营**， 支持微博/抖音/B站/知乎/公众号/X 等；平台不确定或要多平台一次成稿时的默认选择。 当用户说"写条微博""发个帖子""社媒文案""发什么内容""帮我写个帖""涨粉内容""互动内容"时使用。 边界：**小红书整套笔记/图文/种草**找 xhs-note-creator；**带货转化/卖点/详情页**找 copywriting； **严格套 PAS/AIDA 框架排版**找 post-formatter。MarketingFără avertismente★ 4,2 K↓ —
- scientific-brainstormingforyourhealth111-pixel/Vibe-SkillsOpen-ended scientific ideation partner. Use for research gaps, mechanism exploration, interdisciplinary connections, assumptions, possible research directions, and lightweight literature matrix or A+B paper-combination idea mapping. For structured testable hypotheses and validation plans, use hypothesis-generation instead.ȘtiințăFără avertismente★ 3,8 K↓ —
- skill-voice-builderZJU-REAL/Easel通过结构化访谈和写作样本分析，构建创作者个人声音画像（语气/用词/节奏/风格），确保后续内容风格一致。 当用户说"声音画像""我的写作风格""风格一致""建立人设语气""voice/tone""我的表达习惯""统一文风"时使用。 和 skill-audience-profiler 的区别：本 SKILL 建创作者自己的声音画像；audience-profiler 建目标受众/粉丝画像。RedactareFără avertismente★ 4,2 K↓ —
- data-analystjeremylongshore/tons-of-skills-marketplaceData exploration and analysis partner for Product Managers. Use when the user needs to query data, analyze metrics, create dashboards, or extract insights. Trigger with "query", "analyze data", "metrics", "BigQuery", "SQL", "dashboard", or "what does the data say".DateFără avertismente★ 2,9 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↓ —
- principle-attack-the-premisebacknotprop/pstackApply when two or more fixes that share one premise have failed the same gate. Write the premise down and test it directly before you write another fix that assumes it.TestareFără avertismente★ 3,2 K↓ —
- complexa-targetNVIDIA/skillsAdd, edit, inspect, or validate Proteina-Complexa target definitions for protein binders, ligand binders, and AME motif scaffolding. Use for target registries, chain/residue selectors, hotspots, ligand fields, and incomplete motif inputs. Covers direct YAML edits and complexa target/validate target commands; running a campaign with an already registered target belongs to complexa-design.DesignFără 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↓ —
- ops-gtmdavepoon/buildwithclaudeGo-to-market strategy planner. Generates a complete GTM plan across paid, unpaid, marketing, sales, and AI-automation channels for any project — and hands executable campaigns off to /marketing.MarketingFără avertismente★ 3,7 K↓ —
- similarity-search-patternsforyourhealth111-pixel/Vibe-SkillsImplement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.AlteleFără avertismente★ 3,8 K↓ —
- tao-train-grounding-dinoNVIDIA/skillsGrounding DINO for open-set object detection. Combines DINO-style detection with a BERT text encoder for language-guided detection — detects objects described by text prompts without a fixed class vocabulary. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Grounding DINO model. Trigger phrases include "train Grounding DINO", "open-vocabulary detection", "text-prompted detector", "language-guided object detection".AlteleFără avertismente★ 3,8 K↓ —
- golang-structs-interfacessamber/cc-skills-golangGolang struct and interface design patterns — composition, embedding, type assertions, type switches, interface segregation, dependency injection via interfaces, struct field tags, and pointer vs value receivers. Use this skill when designing Go types, defining or implementing interfaces, embedding structs or interfaces, writing type assertions or type switches, adding struct field tags for JSON/YAML/DB serialization, or choosing between pointer and value receivers. Also use when the user asks about "accept interfaces, return structs", compile-time interface checks, or composing small interfaces into larger ones.DesignFără avertismente★ 3,7 K↓ —
trailmark-structural
trailofbits/skills
ProductivitateActualizat alaltăieri
De la autor
Runs full Trailmark structural analysis by building a graph, running `preanalysis()`, and reporting hotspots, taint, blast radius, privilege boundaries, attack surface, and version-gated Trailmark 0.4+/0.5+ data such as proxy counts, subgraph edges, type/reference summaries, and entrypoint attributes. Use when vivisect needs detailed structural data for a target. Triggers: structural analysis, blast radius, taint analysis, complexity hotspots, proxy nodes, type references.
Instalare
npx skills add trailofbits/skills --skill trailmark-structural -a claude-code
Se instalează în .claude/skills/trailmark-structural/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (CC-BY-SA-4.0) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
La ce are acces
Doar instrucțiuniFolosește rețeauaLicență: CC-BY-SA-4.0
Verificări de siguranță pe SKILL.md
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De ce 90
Securitate100
Proveniență87
Întreținere100
Licență80
Adopție61
Fișiere (3)
- SKILL.md
- agents/openai.yaml
- assets/trail-of-bits-mark.svg