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.
49.492 de skill-uri din 2.391 de depozite · actualizat acum 17 ore
49.492 de skill-uri
- make-static-ads-copy-variantsgooseworks-ai/goose-skillsStep of the make-static-ads playbook: after an image is approved, makes more versions of the same picture with different hooks, headlines or fonts by a quoted re-render with the approved render attached as the brand's own image, so copy can be tested without new visuals. Offered, never default. Run make-static-ads instead; not for direct use.MarketingFără avertismente★ 1,3 K↓ —
- hf-cloud-serving-image-selectionhuggingface/skillsPick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.OficialMediaFără avertismente★ 11,3 K↓ —
- make-static-ads-claims-extractgooseworks-ai/goose-skillsStep of the make-static-ads playbook: pulls every claim-bearing span out of an ad — the copy around the image, the on-image words in the prompt, badges, and what the picture implies — and keeps or cuts each by the brand-brain rule. Runs before spend on the finished prompt (Pass A) and on every render (Pass B). Run make-static-ads instead; not for direct use.MarketingFără avertismente★ 1,3 K↓ —
- 00-arena-routeragentscope-ai/OpenJudgeUse when the user wants to compare or benchmark multiple LLMs/agents arena-style but it's unclear which specific workflow fits — a general-purpose win-rate comparison on a custom task, or a benchmark specifically about reference/citation hallucination rate. Also use when the user mentions model arena, agent arena, pairwise model comparison, win-rate ranking, or comparing models on a task and hasn't specified whether that task is generic or about citation accuracy. This skill is the entry router for the arena-eval suite: it asks one diagnostic question when needed, then recommends the workflow or workflows needed to cover the request.PlanificareFără avertismente★ 1 K↓ —
- planning-with-filesOthmanAdi/planning-with-filesPersistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. Optional gated mode can request continuation only when the host supports it and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.PlanificareFără avertismente★ 27,9 K↓ —
- cn-fupanmohitagw15856/pm-claude-skillsRun a 复盘 (fupan), the structured project review widely used in Chinese companies: review the goal, assess the result, analyse why, and draw rules for next time, with a blame-free tone and owned actions. Use when asked 帮我做复盘, 项目复盘, 活动复盘, 复盘会怎么开, or a fupan or retrospective in Chinese. Produces the 复盘 document in Chinese with goal versus result, root causes split into controllable and uncontrollable, lessons stated as reusable rules, and an action list with owners and dates, plus a meeting agenda.RedactareFără avertismente★ 1,5 K↓ —
- coding-agent-rolloutalirezarezvani/claude-skillsRoll out Claude Code to a team: shared or managed settings, MCP and plugin approval, layered CLAUDE.md, adoption. Use whenever the user sets up Claude Code for their team or org, or asks if a rollout or settings file is right.InginerieFără avertismente★ 29,3 K↓ —
- make-content-source-to-unitsgooseworks-ai/goose-skillsStep of the make-content playbook: mines one finished asset into scored quotable units and maps a different lead unit to each platform. Run make-content instead; not for direct use.AlteleFără avertismente★ 1,3 K↓ —
- readme-writermohitagw15856/pm-claude-skillsWrite a clear, well-structured README for a software project or open-source repo. Use when asked to write or improve a README, document a project, or make a repo approachable. Produces a complete README — one-line pitch, badges, quickstart, usage, install, contributing, license — that gets someone from landing to running fast.RedactareFără avertismente★ 1,5 K↓ —
- pricing-strategistalirezarezvani/claude-skillsUse when choosing or revisiting pricing: seat, usage, value-based, freemium or hybrid, Van Westendorp willingness-to-pay analysis, or Good/Better/Best tiers. Runs pricing_model_picker.py, wtp_analyzer.py and packaging_designer.py and returns a range, not one number.AlteleFără avertismente★ 29,3 K↓ —
- plan-campaign-goal-chaingooseworks-ai/goose-skillsChecks whether a stated goal is reachable on a given budget: fills an economics box with a source on every number, subtracts the baseline, works out the implied cost per customer against history or labelled base rates, and flags when the goal needs renegotiating. Use alone when you already have the goal (metric, number, date), budget, order value, margin and baseline; otherwise run plan-campaign.MarketingFără avertismente★ 1,3 K↓ —
- 01-auto-arenaagentscope-ai/OpenJudgeAutomatically evaluate and compare multiple AI models or agents without pre-existing test data. Generates test queries from a task description, collects responses from all target endpoints, auto-generates evaluation rubrics, runs pairwise comparisons via a judge model, and produces win-rate rankings with reports and charts. Supports checkpoint resume, incremental endpoint addition, and judge model hot-swap. Use when the user asks to compare, benchmark, or rank multiple models or agents on a custom task, or run an arena-style evaluation.TestareFără avertismente★ 1 K↓ —
- render-flat-vector-explainergooseworks-ai/goose-skillsAssemble the FREE steps of the flat-vector-explainer video format — a flat-illustration host character (who, where, tone, voice and music come from the recipe choices) walks a countable N-step product routine, one step per beat, and Remotion composites every chip/numeral/tagline/slate/CTA as an animated DOM overlay ON TOP of the Kling i2v character clips (text is NEVER baked into a keyframe — i2v warps type), the closing 'N products' grid is a PIL composite of the REAL product photos (not AI), full-sentence VO drives word-by-word burned captions over a VO-forward music bed, and the ~50s animated silent master is re-cut to a 30s deliverable FROM the animated master (never a static intermediate). Documentation-grade — ships config.example.json + PIPELINE.md + a README of the free assembly; the paid gen steps (keyframes, Kling i2v, VO, music) are separate capabilities the recipe orchestrates. Use for the flat-vector-explainer format.MediaFără avertismente★ 1,3 K↓ —
- render-editorial-motion-podcastgooseworks-ai/goose-skillsAssemble an editorial-motion podcast-clip ad from a config — a real clipped podcast MP3 carries the narrative while N flat limited-palette editorial-illustration keyframes (one look pack) are animated NOT by generative i2v but by DETERMINISTIC ffmpeg ken-burns (zoompan) + hard cuts (no crossfades, which expose geometric drift), each beat snapped to its spoken line, the real audio muxed, Whisper-driven captions burned only mid-sentence, and closed on a PIL brand end card — never AI-rendered text. This is the FREE deterministic assembly stage (ffmpeg ken-burns + hard concat + audio mux + captions + end card); the real audio is clipped from source and the keyframes come from create-image-fal. Use for the editorial-motion-podcast format.MediaFără avertismente★ 1,3 K↓ —
- render-split-screen-creatorgooseworks-ai/goose-skillsAssemble a split-screen creator ad from a config: an AI-creator lip-sync take fills the bottom half while real 16:9 product or demo clips play uncropped in the top half over a blurred fill of the same clip (never black bars), with a brand-colour divider between them. Scenes follow the voiceover timing and are joined hard, an end card holds about 3 seconds, then the finished cut is transcribed and word-level captions are burned in the chosen style. Free, deterministic assembly and captions; the voiceover comes from create-vo-elevenlabs, the creator anchor from create-image-gpt-image-fal, and the lip-sync take is supplied as an input. Use for the split-screen-creator format.MediaFără avertismente★ 1,3 K↓ —
- cn-shuzhi-deckmohitagw15856/pm-claude-skillsUse when asked 帮我做述职 PPT, 述职 PPT 大纲, 年终述职怎么讲, 10 分钟述职讲稿, 述职 PPT 每页写什么, or turn a written year-end review into a 述职 presentation. Produces a slide-by-slide 述职 PPT outline with a conclusion-first headline per slide (结论先行), the chart or visual for each, a timed speaking script (讲稿) that fits the slot, a one-slide version for a short slot, and a rehearsal and Q&A checklist. For writing the review itself use cn-year-end-review; for a promotion to the next level use cn-promotion-defence.DocumenteFără avertismente★ 1,5 K↓ —
- mmx-cliagentscope-ai/OpenJudgeGenerate text, images, video, speech, and music via the MiniMax AI platform. Covers text generation (MiniMax-M3 model), image generation (image-01), video generation (Hailuo-2.3), speech synthesis (speech-2.8-hd, 300+ voices), music generation (music-2.6 with lyrics, cover, and instrumental), and web search. Use when the user needs to create AI-generated multimedia content, produce narrated audio from text, compose music, or search the web through MiniMax AI services.InginerieFără avertismente★ 1 K↓ —
- add-cursornanocoai/nanoclawUse Cursor (local Agent SDK) as a full agent provider — planning, tool orchestration, MCP tools, session resume — alongside or instead of Claude. Cursor-account sign-in or API key, held by the credential gateway. Per-group via `ncl groups config update --provider cursor`. Distinct from using Cursor as a cloud agent (those run on Cursor VMs and are not this provider).PlanificareFără avertismente★ 31,1 K↓ —
- competitor-ad-intelligencegooseworks-ai/goose-skillsScrape competitor ads from Meta, TikTok, Google, and LinkedIn ad libraries, analyze creative patterns (hooks, formats, CTAs), reverse-engineer landing page funnels, and produce a strategic teardown with vulnerability analysis and counter-play recommendations. Use when you need to understand the competitive ad landscape, find new creative directions, or identify weaknesses in a competitor's paid strategy.MarketingFără avertismente★ 1,3 K↓ —
- paid-adsalirezarezvani/claude-skillsUse for paid campaign strategy on Google, Meta, LinkedIn or X: structure, targeting, bids, retargeting and budgets. Scores account health with ad_health_scorer.py and models ROAS with roas_calculator.py. Ad copy only: ad-creative.MarketingFără avertismente★ 29,3 K↓ —
- code-explainermohitagw15856/pm-claude-skillsExplain what a piece of code does in plain English, at the depth the reader needs. Use when asked to explain code, walk through a function, understand an unfamiliar snippet, or onboard to a file. Produces a one-line summary, a step-by-step walkthrough, the non-obvious parts called out, and any bugs or smells spotted along the way.InginerieFără avertismente★ 1,5 K↓ —
- rpihashgraph-online/awesome-codex-pluginsDrive one accepted change through implementation and checks to done, with one fresh review only where a mistake is costly. Use when: asked to run or orchestrate work through RPI.InginerieFără avertismente★ 1,5 K↓ —Apare și în 2 alte depozite
- ai-tool-pickermohitagw15856/pm-claude-skillsFigure out which AI tool actually fits the task in front of you — chatbot, coding assistant, image model, agent, or none — instead of forcing one tool onto everything. Use when asked which AI tool should I use for, what's the best AI for, do I even need AI for this, or should I use ChatGPT or something else. Produces a match between your task and the right kind of AI tool (with why), the trade-offs that matter for your case, when the answer is a non-AI tool or plain human effort, and how to try it cheaply before committing — so you pick by fit, not by hype or habit.MediaFără avertismente★ 1,5 K↓ —
- decision-panelmohitagw15856/pm-claude-skillsRun a decision past a panel of clashing advisors — an optimist, a pessimist, a numbers person, an ethicist, and future-you — then get a chair's verdict. Use when asked to help me decide, weigh this decision, what should I do about, or run this by different advisors. Produces each advisor's honest take on the decision (each committed to their lens), where they disagree most, the question that would break the tie, and a chair's recommendation that weighs the panel — turning a lonely choice into a structured board meeting.AlteleFără avertismente★ 1,5 K↓ —
research-audience-fit-definition
gooseworks-ai/goose-skills
De la autor
Step of the research-audience playbook: drafts the searchable fit definition, exclusions and list size that the list run then searches on. Run research-audience instead; not for direct use.
Instalare
npx skills add gooseworks-ai/goose-skills --skill research-audience-fit-definition -a claude-code
Se instalează în .claude/skills/research-audience-fit-definition/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Fișiere (2)
- SKILL.md
- skill.meta.json