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 39 de minute
49.409 skill-uri
- writing-skillsGanyuanRan/AegisUse when creating new skills, editing existing skills, or verifying skills work before deploymentRedactareFără avertismente★ 1,4 K↓ —
- run-organic-social-platform-researchgooseworks-ai/goose-skillsResearches how one social platform works right now from dated sources (what gets reach, formats rising and fading, how small accounts get seen, recent changes) and finds what is getting watched in a given niche there, with linked examples and engagement read against each author's baseline. Use alone when you already have the platform and niche; otherwise run run-organic-social.ȘtiințăFără avertismente★ 1,3 K↓ —
- onboarding-croalirezarezvani/claude-skillsUse when activation, time-to-value or a first-run experience after signup needs work, before redesigning it. Finds the activation drop-off with activation_funnel_analyzer.py.MarketingFără avertismente★ 29,2 K↓ —
- research-audience-account-sourcinggooseworks-ai/goose-skillsStep of the research-audience playbook: finds candidate accounts matching the fit definition, confirms gates, applies exclusions and dedupes. Run research-audience instead; not for direct use.ȘtiințăFără avertismente★ 1,3 K↓ —
- research-competitors-category-passgooseworks-ai/goose-skillsStep of the research-competitors playbook: the worker brief covering the whole category, including searches, AI answers, community threads and category ad winners. Run research-competitors instead; not for direct use.ȘtiințăFără avertismente★ 1,3 K↓ —
- product-researchalirezarezvani/claude-skillsUse when planning or synthesizing user research: choosing the method, deciding how many participants, or turning coded notes into insights. Runs study_designer.py, saturation_planner.py and insight_synthesizer.py, which refuses single-source insights.ȘtiințăFără avertismente★ 29,2 K↓ —
- analyze-performance-call-and-learngooseworks-ai/goose-skillsStep of the analyze-performance playbook: calls ended tests, scores last week's calls, writes this week's kill/scale/hold calls and drafts learnings for the brand brain. Run analyze-performance instead; not for direct use.TestareFără avertismente★ 1,3 K↓ —
- analyze-performance-rank-and-readgooseworks-ai/goose-skillsStep of the analyze-performance playbook: ranks creative by angle, hook and format with spend gates, writes short per-channel reads and drafts what to make next. Run analyze-performance instead; not for direct use.RedactareFără avertismente★ 1,3 K↓ —
- run-organic-social-plan-calendargooseworks-ai/goose-skillsStep of the run-organic-social playbook: turns the audit, research and dated moments into a two-week grid of empty post slots. Run run-organic-social instead; not for direct use.PlanificareFără avertismente★ 1,3 K↓ —
- run-paid-campaigns-apply-and-loggooseworks-ai/goose-skillsStep of the run-paid-campaigns playbook: stages the week's approval items, applies only what the marketer approves and keeps the change log. Run run-paid-campaigns instead; not for direct use.AlteleFără avertismente★ 1,3 K↓ —
- research-audience-fit-definitiongooseworks-ai/goose-skillsStep 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.ȘtiințăFără avertismente★ 1,3 K↓ —
- analyze-performance-revenue-joingooseworks-ai/goose-skillsStep of the analyze-performance playbook: joins cleaned store or CRM numbers with ad spend to build the business-truth table, MER, new-customer cost and the overclaim ratio. Run analyze-performance instead; not for direct use.MarketingFără avertismente★ 1,3 K↓ —
- run-paid-campaigns-weekly-readgooseworks-ai/goose-skillsStep of the run-paid-campaigns playbook: reads each platform's last mature results window against the allowable cost, as evidence for the week's moves. Run run-paid-campaigns instead; not for direct use.AlteleFără avertismente★ 1,3 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; agent instructions read selected project planning context when invoked. 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. This adapter registers no lifecycle or Stop hook, never requests continuation, 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↓ —
- second-brain-publishundefined-ui/second-brain-osPrepare a subset of the vault for publishing: check opt-in flags, find private material, and report what would leak through links before anything is exported. Use this skill when the user wants to publish notes as a site or digital garden, asks what is safe to make public, or is setting up an export. Do NOT use for exporting a single document, or for running the publishing tool itself.ProductivitateFără avertismente★ 1,2 K↓ —
- bamadaveebbelaar/bamaBuild any Mac app. Start here to pick the next skill for a native macOS app.AlteleFără avertismente★ 1,5 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↓ —
- 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↓ —
- second-brain-projectundefined-ui/second-brain-osSet up or update a project in the vault: the four-stage folder pipeline, a project-scoped CLAUDE.md with one goal, and links to the concept pages it depends on. Use this skill when the user starts something new they will work on over time, says "create a project", "set up a folder for X", or asks to define the goal and structure of ongoing work. Do NOT use for one-off tasks, for wiki pages about a topic, or for scoping an existing project down to work in it.ProductivitateFără avertismente★ 1,2 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↓ —
- gentle-ai-chained-prGentleman-Programming/gentle-shellTrigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.InginerieFără avertismente★ 1,5 K↓ —
- research-audiencegooseworks-ai/goose-skillsAudience research: who the buyers are, in their own words, where they gather and how to reach them — plus named prospect lists when asked. Use when the marketer says "research our audience", "who should we target", "mine our reviews", "why do people buy us or leave", "where does our audience hang out"; or for lists: "find 50 right-fit leads with emails", "find retailers or accounts to pitch", "score these leads / who do we call first", "who's looking for an alternative to X", "tell me when a past champion changes jobs". Reads the brand's own customer data first and delivers a readable report saved to the brand. Never contacts anyone. Not for market size or trends — use research-market; not for writing the messages — use write-outreach.ȘtiințăFără avertismente★ 1,3 K↓ —
icml-experiments
brycewang-stanford/Awesome-Journal-Skills
TestareActualizat 27 sept. 2026
De la autor
Use when stress-testing ICML experimental evidence before submission or rebuttal, including strong tuned baselines, mechanism-isolating ablations, seed variance and confidence intervals, compute disclosure, data leakage and split construction, reproducibility, negative results, and fit to ICML soundness, originality, and significance scoring.
Instalare
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icml-experiments -a claude-code
Se instalează în .claude/skills/icml-experiments/ · 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: MIT
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 88
Securitate100
Proveniență77
Întreținere100
Licență100
Adopție50
Fișiere (1)
- SKILL.md