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
- aaai-camera-readybrycewang-stanford/Awesome-Journal-SkillsUse when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.ȘtiințăFără avertismente★ 1,4 K↓ —
- wacv-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing WACV experiments, covering Applications-track systems evidence (latency, power, robustness under real constraints) versus Algorithms-track matched-baseline novelty, comparative assessment under the deployed condition, uncertainty over seeds and sessions, ablations, and evidence that survives the two-round review.DevOpsFără avertismente★ 1,4 K↓ —
- vldb-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of a VLDB paper, covering workload and dataset realism at scale, competitor tuning fairness, scalability curves versus single points, tail-latency and throughput reporting, ablations that isolate the mechanism, and the loss-case disclosure PVLDB reviewers look for first.ȘtiințăFără avertismente★ 1,4 K↓ —
- vis-writing-stylebrycewang-stanford/Awesome-Journal-SkillsUse when revising an IEEE VIS paper for a task-grounded visualization contribution on the first page, a design rationale that ties each visual encoding and interaction to a task, evaluation matched to the contribution type, honest limitations, and disciplined use of the VGTC/TVCG 9+2 page budget for a paper that will be read as an IEEE TVCG journal article.RedactareFără avertismente★ 1,4 K↓ —
- ase-review-processbrycewang-stanford/Awesome-Journal-SkillsUse when reasoning about how an ASE (IEEE/ACM Automated Software Engineering) research submission is evaluated, covering double-anonymous review, the early-rejection stage before rebuttal, the Accept / Revision / Reject outcomes, the criteria-bound revision round, and how ASE's process differs from FSE's PACMSE Major Revision, ICSE's cycles, and ISSTA's rounds.InginerieFără avertismente★ 1,4 K↓ —
- cav-review-processbrycewang-stanford/Awesome-Journal-SkillsUse when reasoning about how a CAV (Computer Aided Verification) submission is evaluated, covering the two-stage reviewing process (two reviews then an early-reject filter, then two more reviews with a rebuttal), the partial double-anonymity by category, the accept/reject outcome, the optional non-conditional artifact evaluation, and how CAV differs from TACAS and FMCAD.InginerieFără avertismente★ 1,4 K↓ —
- atc-review-processbrycewang-stanford/Awesome-Journal-SkillsUse when reasoning about how an ATC (ACM SIGOPS Annual Technical Conference, formerly USENIX ATC) submission is evaluated — the two-round extended-abstract model, the round-one gate by two reviewers, the round-two read by 3-4 reviewers, double-blind reviewing, rebuttal, conditional acceptance with shepherding, and how ATC differs from OSDI/SOSP/NSDI.InginerieFără avertismente★ 1,4 K↓ —
- asplos-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning an ASPLOS campaign across the two-deadline cycle — sequencing evidence building, the September 9, 2026 submission gate, author-response windows, the December 21 notification, Major Revision resubmission six weeks later, artifact evaluation, and the April 2027 conference in Crete, with owners per risk.ProductivitateFără avertismente★ 1,4 K↓ —
- cikm-camera-readybrycewang-stanford/Awesome-Journal-SkillsUse when turning an accepted CIKM paper into its ACM proceedings version inside the short notification-to-camera-ready window, covering de-anonymization, the e-rights and TAPS pipeline into the ACM Digital Library, CCS concepts and metadata, GenAI-disclosure retention, artifact link publication, and Rome presentation logistics.ȘtiințăFără avertismente★ 1,4 K↓ —
- cell-star-methodsbrycewang-stanford/Awesome-Journal-SkillsUse to build Cell's mandatory STAR Methods — the Key Resources Table, the three Resource Availability subsections, Experimental Model and Subject Details, Method Details, and Quantification and Statistical Analysis, in the exact required order.AlteleFără avertismente★ 1,4 K↓ —
- senior-fullstackalirezarezvani/claude-skillsStart a fullstack project or audit a codebase: pick a stack (Next.js, FastAPI, MERN, Django), scaffold it and score code quality. Use whenever the user asks which stack to use, wants a new web app set up, or asks how good or messy their codebase is.InginerieFără avertismente★ 29,3 K↓ —
- colm-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a COLM paper inside the fastest-moving literature in ML — triaging arXiv-heavy citations, handling concurrent work fairly, citing model and dataset artifacts correctly, distinguishing COLM's three-edition archive from adjacent venues' archives, and keeping self-citation double-blind safe.ȘtiințăFără avertismente★ 1,4 K↓ —
- colm-camera-readybrycewang-stanford/Awesome-Journal-SkillsUse when converting a COLM acceptance into the final paper — the August 7 camera-ready deadline in 2026, de-anonymization and the one-page acknowledgments allowance, folding rebuttal commitments into the text, publishing on OpenReview, releasing artifacts publicly, and planning the October conference in San Francisco.ȘtiințăFără avertismente★ 1,4 K↓ —
- cikm-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a CIKM submission against three literatures at once — retrieval, mining, and knowledge management/databases — building the boundary-work paragraph, guarding against misattributing SIGIR/KDD/ICDM classics to CIKM, and handling preprints under the arXiv-declaration and dual-submission rules.ȘtiințăFără avertismente★ 1,4 K↓ —
- colt-camera-readybrycewang-stanford/Awesome-Journal-SkillsUse when converting an accepted COLT (Conference on Learning Theory) paper into its PMLR proceedings version, covering de-anonymization, acknowledgements and funding restoration, appendix consolidation into the archival PDF, PMLR volume metadata and BibTeX hygiene, rebuttal-promised edits, and presentation logistics.DocumenteFără avertismente★ 1,4 K↓ —
- conext-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning an ACM CoNEXT campaign backward from a deadline, covering the choice between the December and June submission cycles, the mandatory registration step, the one-shot major-revision window, the reproducibility badge opt-in due at submission, PACMNET camera-ready, and presentation — all on CoNEXT's distinctive two-cycles-per-year calendar.ProductivitateFără avertismente★ 1,4 K↓ —
- colt-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a COLT (Conference on Learning Theory) submission against prior bounds and models — building the known-versus-new comparison across COLT/ALT lineage, STOC/FOCS, NeurIPS-and-ICML theory tracks, statistics journals, and arXiv concurrency, while respecting anonymity and the parallel-submission rules.ȘtiințăFără avertismente★ 1,4 K↓ —
- fizz-convertpashov/skillsConvert English-language properties in PROPERTIES.md (produced by the Fizz skill) into Solidity assertions inside the existing fuzz harness, then flip their checkboxes. Trigger on "fizz-convert", "convert properties", "implement properties from PROPERTIES.md", "convert PROPERTIES.md to Solidity".AlteleFără avertismente★ 1,3 K↓ —
- openspec-apply-changeMemeMeow-Studio/MemeMeowImplement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.ProductivitateFără avertismente★ 1,3 K↓ —Apare și în 1 alt depozit
- openspec-exploreMemeMeow-Studio/MemeMeowEnter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.FinanțeFără avertismente★ 1,3 K↓ —Apare și în 1 alt depozit
- openspec-archive-changeMemeMeow-Studio/MemeMeowArchive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.ProductivitateFără avertismente★ 1,3 K↓ —
- openspec-apply-changeMemeMeow-Studio/MemeMeowImplement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.ProductivitateFără avertismente★ 1,3 K↓ —
- openspec-update-changeMemeMeow-Studio/MemeMeowUpdate an OpenSpec change by revising its existing planning artifacts and keeping them coherent with one another. Use when the user wants to revise a change's plan, fold new decisions into it, or reconcile its artifacts after an edit. Never edits code.RedactareFără avertismente★ 1,3 K↓ —
- openspec-update-changeMemeMeow-Studio/MemeMeowUpdate an OpenSpec change by revising its existing planning artifacts and keeping them coherent with one another. Use when the user wants to revise a change's plan, fold new decisions into it, or reconcile its artifacts after an edit. Never edits code.RedactareFără avertismente★ 1,3 K↓ —
huggingface-vision-trainer
huggingface/skills
OficialMediaActualizat acum 6 zile
De la autor
Trains 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.
Instalare
npx skills add huggingface/skills --skill huggingface-vision-trainer -a claude-code
Se instalează în .claude/skills/huggingface-vision-trainer/ · 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
Rulează scripturile incluseNu am văzut acces la rețeaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
- Include scripturi pe care nu le-am verificatScăzut
De ce 88
Securitate85
Proveniență100
Întreținere100
Licență100
Adopție63
Fișiere (12)
- SKILL.md
- references/finetune_sam2_trainer.md
- references/hub_saving.md
- references/image_classification_training_notebook.md
- references/object_detection_training_notebook.md
- references/reliability_principles.md
- references/timm_trainer.md
- scripts/dataset_inspector.py
- scripts/estimate_cost.py
- scripts/image_classification_training.py
- scripts/object_detection_training.py
- scripts/sam_segmentation_training.py