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.
49.456 de skill-uri din 2.407 depozite · actualizat acum 32 de minute
49.456 de skill-uri
- upgrade-stripefcakyon/claude-codex-settingsGuide for upgrading Stripe API versions, webhook endpoints, server-side SDKs, Stripe.js, and mobile SDKsInginerieFără avertismente★ 1,2 K↓ —
- fizz-syncpashov/skillsReconcile an existing Fizz harness with a changed source tree. Detects added/removed/changed contract functions, quarantines stale properties, regenerates drifted handler stubs, and refreshes the snapshot. Trigger on "fizz-sync", "resync fuzzing", "sync fuzz harness", "refresh fuzzing properties", "fuzzing drift check".JuridicFără avertismente★ 1,3 K↓ —
- icde-experimentsbrycewang-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。PlanificareFără avertismente★ 1,4 K↓ —
- iclr-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing ICLR experiments, including baselines, ablations, scaling laws, robustness, statistics, benchmarks, human evaluation, and compute reporting. Use when a reviewer questions whether a representation-learning or model gain is real, when you must isolate one mechanism with an ablation, or when preparing a small compute-matched control that can be posted inline during the public discussion period.AlteleFără avertismente★ 1,4 K↓ —
- cav-supplementarybrycewang-stanford/Awesome-Journal-SkillsUse when deciding what belongs in a CAV (Computer Aided Verification) paper body versus its optional appendix and artifact, covering the LNCS page limits, the rule that reviewers are not obliged to read the appendix so decision-critical content stays in the body, where full proofs and benchmark tables live, and double-anonymous supplementary material for the anonymized categories.ȘtiințăFără avertismente★ 1,4 K↓ —
- cscw-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the empirical work behind a CSCW paper — interview and ethnographic rigor, trace and log analysis, surveys, deployments, and mixed methods — matching each method's own validity standard and the ethics of studying real communities.DevOpsFără avertismente★ 1,4 K↓ —
- ndss-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of an NDSS paper — attack demonstrations, defense evaluations under adaptive adversaries, and Internet measurements — choosing between testbed, emulation, and live experiments and meeting NDSS's deployment-realism evidence bar.DevOpsFără avertismente★ 1,4 K↓ —
- edbt-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing EDBT empirical evaluations for database-systems work, covering real workloads and datasets, fair and tuned baselines, honest measurement across realistic scales, reproducible harnesses, and the higher bar of the Experiments & Analysis paper where the measurement itself is the contribution.DateFără avertismente★ 1,4 K↓ —
- soda-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when deciding whether and how experiments belong in a SODA (ACM-SIAM Symposium on Discrete Algorithms) paper — SODA's scope includes experimental validation but theorems carry the decision, so this skill designs supporting numerics honestly and routes implementation-led work to co-located ALENEX or to SEA.ȘtiințăFără avertismente★ 1,4 K↓ —
- uai-writing-stylebrycewang-stanford/Awesome-Journal-SkillsUse when revising a UAI manuscript for probabilistic-inference readers, enforcing precise notation for distributions, graphs, and interventions, explicit assumption and identifiability statements, an 8-page main part that carries the whole argument while proofs sit in the appendix, and claims calibrated to what the theory and experiments show.RedactareFără avertismente★ 1,4 K↓ —
- osdi-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of an OSDI submission — choosing mature baselines and realistic workloads, structuring the section around research questions, measuring scalability and tail behavior, quantifying the design's costs, and fitting the evidence into the 12-page reviewed body.DesignFără avertismente★ 1,4 K↓ —
- eccv-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the experimental program of an ECCV paper — benchmark selection that survives a September conference, matched-substrate baseline fairness in the foundation-model era, ablations that isolate the claimed mechanism, qualitative failure evidence, and run sequencing toward a March freeze.ȘtiințăFără avertismente★ 1,4 K↓ —
- hri-writing-stylebrycewang-stanford/Awesome-Journal-SkillsUse when drafting or revising an ACM/IEEE HRI full paper's structure and prose for an interdisciplinary audience — leading with the human-robot contribution and research questions, making hypotheses and measures explicit, describing the robot embodiment, keeping claims proportional to the study within the 8-page acmart budget, and writing so the chosen track's contribution type is unmistakable.RedactareFără avertismente★ 1,4 K↓ —
- iccv-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing the experimental program for an ICCV paper against the early-March deadline, covering benchmark-drift audits across the two-year gap, baseline fairness in the foundation-model era, ablations that isolate mechanisms, qualitative and failure evidence, and sequencing runs so the decisive result lands before the deadline, not after.ȘtiințăFără avertismente★ 1,4 K↓ —
- corl-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing experiments for a CoRL robot-learning paper — seeds and evaluation-episode counts, task-suite breadth, real-robot versus simulation evidence, sim-to-real gap measurement, baseline fairness across BC/RL/VLA families, generalization splits, and statistics for success-rate claims.ȘtiințăFără avertismente★ 1,4 K↓ —
- icdt-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when deciding what counts as evidence for an ICDT (International Conference on Database Theory) result — matching-bound complexity analysis as the primary evidence, worked examples and counterexamples that establish separations, and, only for papers with an algorithmic contribution, a proportional and honestly-scoped experimental evaluation that does not pretend to be the contribution.DateFără avertismente★ 1,4 K↓ —
- iros-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing IROS experiments — real-robot trial counts, success criteria set in advance, reset procedures, failure taxonomies, baseline fairness on matched hardware, sim-to-real gap reporting, small-n statistics, and the claim-to-evidence ladder that embodied-systems reviewers apply before they trust a demo.AlteleFără avertismente★ 1,4 K↓ —
- podc-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when building the evidence for an ACM PODC paper — where "evidence" is a proof, not a benchmark. Covers matching upper and lower bounds, tightness arguments, model and assumption stress-tests, adversary-strength calibration, and the honest, clearly-optional role of any simulation in a distributed-computing-theory paper.TestareFără avertismente★ 1,4 K↓ —
- icml-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse 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.TestareFără avertismente★ 1,4 K↓ —
- hf-cloud-sagemaker-production-defaultshuggingface/skillsCreate a SageMaker endpoint (real-time, real-time scale-to-zero, or async) with autoscaling, CloudWatch alarms, and tagging enabled by default. Use this skill whenever about to create a SageMaker endpoint, write deployment code that calls `create_endpoint`, or finalize a deployment after the image URI and IAM role are known. Provides deploy.py for real-time endpoints, deploy_ic.py for real-time endpoints that scale to zero instances via inference components, and deploy_async.py for async endpoints (also scale-to-zero). This is the last step in the SageMaker deployment workflow. Never generate a bare `create_endpoint` call without these defaults — endpoints without autoscaling or alarms are demos, not deployments.OficialDevOpsFără avertismente★ 11,3 K↓ —
- hf-cloud-sagemaker-iam-preflighthuggingface/skillsEnsure a usable SageMaker execution role exists before deploying or training. Use this skill whenever about to create a SageMaker endpoint, model, training job, or any resource that requires an execution role. Use it especially when the user has not provided a role ARN explicitly, when scripts are about to call `iam:CreateRole`, or when an AccessDenied error mentions an IAM action. Never blindly call `iam:CreateRole` — always check for existing roles first. This skill prevents the most common SageMaker deployment failure: trying to create IAM resources from an SSO principal that has no IAM write permissions.OficialDevOpsFără avertismente★ 11,3 K↓ —
- dac-supplementarybrycewang-stanford/Awesome-Journal-SkillsUse when deciding what belongs inside the six reviewed pages of an ACM/IEEE Design Automation Conference (DAC) Research Manuscript versus in an external repository, given DAC's tight 6+1 budget, its references-only seventh page, the double-blind constraint on any linked material, and the absence of a formal reviewed-appendix or artifact-badging track.DesignFără avertismente★ 1,4 K↓ —
- isca-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of an ISCA paper — pinning simulator fidelity to the claims it must carry, documenting gem5-class configurations and sampling choices, selecting workload suites that represent the claim's domain, tuning baselines in good faith, and separating architectural effect from modeling artifact.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↓ —
create-mobile-app
microsoft/power-platform-skills
De la autor
Use when the user wants to start a new Power Apps mobile app (Expo / React Native / TypeScript, targeting iOS and Android) from scratch.
Instalare
npx skills add microsoft/power-platform-skills --skill create-mobile-app -a claude-code
Se instalează în .claude/skills/create-mobile-app/ · 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.
La ce are acces
Verificări de siguranță pe SKILL.md
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De ce 88
Fișiere (2)
- SKILL.md
- references/requirements-discovery.md