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.
49.409 skill-uri din 2.375 de depozite · actualizat acum 5 minute
49.409 skill-uri
- add-mcscopilotmicrosoft/power-platform-skillsAdds Microsoft Copilot Studio connector to a Power Apps code app. Use when invoking Copilot Studio agents, sending prompts to agents, or integrating agent responses.InginerieFără avertismente★ 1,1 K↓ —
- roadmapjezweb/claude-skillsPlan and execute entire application builds. Generates phased delivery roadmaps, then executes them autonomously — phase by phase, committing at milestones, deploying, testing, and continuing until done or stuck. Modes: plan (generate roadmap), start (begin executing), resume (continue from where you left off), status (show progress). Triggers: 'roadmap', 'start building', 'resume the build', 'keep going', 'build the whole thing', 'execute the roadmap', 'what phase are we on'.PlanificareFără avertismente★ 1,1 K↓ —
- rss-workflowbrycewang-stanford/Awesome-Journal-SkillsJournal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的 Claude Code/Codex 期刊技能包,从选题、识别策略到表格规范与审稿回复全流程,助你快速发论文。ProductivitateFără avertismente★ 1,4 K↓ —
- nejm-writingbrycewang-stanford/Awesome-Journal-SkillsUse to structure and tighten an NEJM Original Article into terse IMRAD — short main text (~2700 words), limited references, claim-first results, and a sober discussion with explicit limitations and calibrated clinical implications. Enforces NEJM's plain, concise house style.RedactareFără avertismente★ 1,4 K↓ —
- capturealirezarezvani/claude-skillsUse whenever the user unloads a messy brain dump of ideas, tasks and plans ('capture this', 'brain dump', a long unstructured paste) and wants it organized. Sorts it with dump_classifier.py into projects, tasks and connections with nothing lost.PlanificareFără avertismente★ 29,2 K↓ —Apare și în 1 alt depozit
- report-issuemicrosoft/power-platform-skillsUse when the user wants to report a bug, file an issue, submit a bug report, or report any problem with the mobile-app plugin.AlteleFără avertismente★ 1,1 K↓ —
- refactorhashgraph-online/awesome-codex-pluginsRestructure or clean up code with no behavior change, proved by before-and-after checks. Use when: asked to clean up, extract, dedupe or simplify, even one function.InginerieFără avertismente★ 1,5 K↓ —Apare și în 2 alte depozite
- bamadaveebbelaar/bamaBuild any Mac app. Start here to pick the next skill for a native macOS app.AlteleFără avertismente★ 1,5 K↓ —
- quick-calculatoralibaba/skill-upQuickly produces accurate calculation results when a user needs arithmetic, unit conversion, or mathematical formula solving. Triggered when users say things like "help me calculate", "compute", "how much is", etc.MarketingFără avertismente★ 1,4 K↓ —
- pr-review-fixTencentCloudBase/CloudBase-AI-ToolkitPeriodically analyze open pull requests for CI failures, code review feedback, and quality issues, then fix them in batch. Use this skill when the user asks to check PR status, triage CI failures, fix review comments, analyze open PRs, or run a scheduled PR health check across the repository.InginerieFără avertismente★ 1,2 K↓ —
- uai-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning a UAI cycle end to end, from venue-fit confirmation through the winter submission deadline, the spring review and author-response phases, the June decision, the July PMLR camera-ready, and the August conference, as one backward-planned calendar with named owners for anonymity, evidence, and packaging tasks.ProductivitateFără avertismente★ 1,4 K↓ —
- planning-with-filesActualizatOthmanAdi/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↓ —
- pnas-trackbrycewang-stanford/Awesome-Journal-SkillsUse to choose the PNAS submission track — Direct Submission (standard, editor-assigned, peer reviewed) vs Contributed Submission (an NAS member communicates their own paper). Covers eligibility, the editor/member role, the discontinued and legacy tracks, and how to pick. Unique to PNAS.ȘtiințăFără avertismente★ 1,4 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↓ —
- train-sentence-transformershuggingface/skillsTrain or fine-tune sentence-transformers models across `SentenceTransformer` (bi-encoder, dense or static embedding model for retrieval, similarity, clustering, classification, paraphrase mining, dedup, multimodal), `CrossEncoder` (reranker, pair scoring for two-stage retrieval / pair classification), `SparseEncoder` (SPLADE, sparse embedding model for learned-sparse retrieval), and `MultiVectorEncoder` (ColBERT / late-interaction, per-token embeddings scored with MaxSim). Covers loss selection, hard-negative mining, evaluators, distillation, LoRA, Matryoshka, and Hugging Face Hub publishing. Use for any sentence-transformers training task.OficialProductivitateFără avertismente★ 11,3 K↓ —
- huggingface-paper-publisherhuggingface/skillsPublish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.OficialȘtiințăFără avertismente★ 11,3 K↓ —
- testing-livekit-agentsfcakyon/claude-codex-settingsWrites turn-level tests for a LiveKit agent in the user's normal test suite: pytest (Python) or Vitest (Node.js). Use when the user asks to "write tests for my agent", "add a test for this tool", "test the handoff", "pin this bug", "why does my agent test fail", or after building or changing agent behavior that needs regression coverage. Covers the SDK's test session harness, assertions on messages, tool calls and handoffs, LLM judging of a reply against an intent, mocking tools, multi-turn tests, and judging whole conversations with the built-in judges. For interactive poking use debugging-livekit-agents. For grading whole conversations at scale use running-livekit-simulations.TestareFără avertismente★ 1,2 K↓ —Apare și în 1 alt depozit
- huggingface-community-evalshuggingface/skillsRun evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.OficialAlteleFără avertismente★ 11,3 K↓ —
- huggingface-vision-trainerhuggingface/skillsTrains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.OficialMediaFără avertismente★ 11,3 K↓ —
- mcp-case-overridesalibaba/skill-upPer-case mocked MCP override smoke skill used by skill-up e2e tests.TestareFără avertismente★ 1,4 K↓ —
- aaai-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning an AAAI project timeline from topic selection through abstract, OpenReview submission, two-phase review, rebuttal, decision, camera-ready, registration, presentation, and public artifact release.ProductivitateFără avertismente★ 1,4 K↓ —
- cell-figuresbrycewang-stanford/Awesome-Journal-SkillsUse to finalize Cell Press display items — column-width sizing, minimum fonts, RGB, show-the-data with defined error bars/n/replicate type, scale bars, colorblind-safe palettes, multi-panel discipline, stand-alone legends, and image integrity.MediaFără avertismente★ 1,4 K↓ —
- hf-cloud-python-env-setuphuggingface/skillsSet up an isolated Python environment for SageMaker / AWS work, with the right Python version and current boto3. Use this skill whenever Python code will be executed for a SageMaker deployment, training job, or any AWS automation — including when about to run `pip install`, when about to invoke `boto3`, when creating or activating a virtualenv, or when the user asks to "set up the environment". Never use system Python and never `pip install` into it. Always isolate. This skill prevents the most common failure modes: wrong Python version, dependency conflicts, and stale SDKs.OficialInginerieFără avertismente★ 11,3 K↓ —
- nejm-abstractbrycewang-stanford/Awesome-Journal-SkillsUse to write the NEJM structured abstract — four headed sections (Background, Methods, Results, Conclusions), ≤250 words, with the trial registration number and funding source, leading the Results with the primary outcome reported as an effect size with a 95% CI. Late-stage polish skill.RedactareFără avertismente★ 1,4 K↓ —
cn-level-mapper
mohitagw15856/pm-claude-skills
De la autor
Compare job levels (职级) across Chinese technology companies and against international ladders, to judge an offer, a job move or a promotion target: what a level usually means in scope and expectations, how levels roughly line up, and what to ask the recruiter. Use when asked P7 相当于什么级别, 跳槽职级怎么对标, 字节 2-2 对应阿里什么, 这个 offer 的职级合理吗, compare Chinese tech levels, or how does Alibaba P-level map to Google levels. Produces a level comparison built from the person's own ladders and offer details, a scope-and-expectation profile for each level, the negotiation questions to ask, and a clear note on what is approximate.
Instalare
npx skills add mohitagw15856/pm-claude-skills --skill cn-level-mapper -a claude-code
Se instalează în .claude/skills/cn-level-mapper/ · 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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