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 3 ore
49.492 de skill-uri
- cluelesshashgraph-online/awesome-codex-pluginsUse when the user explicitly cannot review the output in the current domain, says they do not understand it or will copy-paste without checking, or requests clueless mode. Examples: "I know nothing about this", "не разбираюсь", "сделай за меня". Brevity, "make it nice", and delegation alone do not establish a knowledge gap.InginerieFără avertismente★ 1,5 K↓ —
- senior-architectalirezarezvani/claude-skillsMake system architecture decisions and draw architecture diagrams: monolith vs microservices, database choice, scalability, ADRs, design reviews, Mermaid or PlantUML. Use whenever the user asks how to structure a system, which database to pick, whether it will scale, or wants an ADR or diagram.PlanificareFără avertismente★ 29,3 K↓ —
- experiment-designeralirezarezvani/claude-skillsPlan A/B tests and product experiments: hypotheses, sample size, priority, reading results. Use whenever the user asks if a test won, how long to run it or what to test.TestareFără avertismente★ 29,3 K↓ —
- jira-expertalirezarezvani/claude-skillsJira setup and queries: JQL, workflows, custom fields, automation, dashboards. Use whenever the user needs a Jira search, filter, dashboard or rule set up, or a workflow fixed.ProductivitateFără avertismente★ 29,3 K↓ —
- product-strategistalirezarezvani/claude-skillsHead of Product: quarterly OKRs cascaded from company to team, product vision, roadmap, team structure. Use whenever the user asks to set OKRs, a vision or roadmap, or align teams on strategy.PlanificareFără avertismente★ 29,3 K↓ —
- parallelhashgraph-online/awesome-codex-pluginsBuild a planned game with several agents at once — game logic and netcode, levels, art, sound, the landing page — each in its own folders, then one merge, a two-browser check, a playtest and a blind review. Use only when parallel work is requested and the host supports it. Use after the plan step, or when someone asks to "build it in parallel", "use more agents", "split the work" or "go faster".DesignFără avertismente★ 1,5 K↓ —
- oma-architecturefirst-fluke/oh-my-agentArchitecture specialist for software/system design, module and service boundaries, tradeoff analysis, and stakeholder synthesis. Uses context-aware methods such as diagnostic routing, design-twice comparison, ATAM-style risk analysis, CBAM-style prioritization, and ADR-style decision records.PlanificareFără avertismente★ 1,4 K↓ —
- extract-atomic-memorysno-ai/sno-stationRead one conversation window and return every independently mutable claim it states, one record each, with who or what it is about, whether it happened or stands, and the words that carry its time. Used by the memory extraction model on every conversation window; the engine resolves dates, validates keys, and repairs format.ProductivitateFără avertismente★ 1,1 K↓ —
- changelog-generatoralirezarezvani/claude-skillsWrite release notes and CHANGELOG.md from commits and pick the next semver version. Use whenever the user is cutting a release, asks what changed since the last one or what version comes next, or wants commits linted first.RedactareFără avertismente★ 29,3 K↓ —
- oma-skill-creationNoufirst-fluke/oh-my-agentCreate or revise OMA skills and their references. Use for skill routing, execution contracts, conditional loading, and authoring validation.AlteleFără avertismente★ 1,4 K↓ —
- senior-devopsalirezarezvani/claude-skillsSet up CI/CD pipelines, infrastructure as code, containers and deployments on AWS, GCP or Azure. Use whenever the user needs a build or deploy pipeline, Terraform, a Dockerfile, or wants to manage a release to the cloud.DevOpsFără avertismente★ 29,3 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↓ —Apare și în 1 alt depozit
- judge-rem-memory-updatessno-ai/sno-stationJudge REM memory relations, rewrites, verification, and clause carry by meaning. Use for REM update model calls that decide which older facts are superseded, which facts remain current, and whether a proposed rewrite preserves all surviving facts.ProductivitateFără avertismente★ 1,1 K↓ —
- oma-coordinationfirst-fluke/oh-my-agentCoordinate assigned specialist tasks and handoffs manually. Use when supervising a multi-agent project step by step.PlanificareFără avertismente★ 1,4 K↓ —
- research-marketgooseworks-ai/goose-skillsMarket research and brand watch: which market the brand is in, how big the reachable part is, what's changing, how buyers buy and what they pay, what people are saying now, and what it means for positioning. Use when the marketer asks for market research, "how big is my market", "what's changing in my category", "what do others charge", "what are people saying about us", "is there demand for <idea>", or "watch my brand / tell me if something blows up" (alerts only, risk first). Also writes positioning choices and finished messages ("position my product", "write our positioning"). Researches first, asks only decisions at the end, and saves the output to the brand. Not for who the buyers are and their own words — use research-audience; not for a deep look at rivals — use research-competitors.ȘtiințăFără avertismente★ 1,3 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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- cmo-advisoralirezarezvani/claude-skillsMarketing leadership: positioning, product-led vs sales-led vs community-led growth, budget split across channels, marketing team design. Use whenever the user asks how to grow, which go-to-market fits or where to spend.DesignFără avertismente★ 29,3 K↓ —
- fse-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning an ESEC/FSE submission against the software-engineering literature across ICSE, FSE, ASE, ISSTA, MSR, and the SE journals (EMSE, TSE, TOSEM), writing delta-first contrast rather than a citation catalog, keeping self-citations double-anonymous, and handling concurrent, preprint, and prior-version overlap.RedactareFără avertismente★ 1,4 K↓ —
using-agent-relay
AgentWorkforce/relay
AlteleActualizat acum 8 ore
De la autor
Use when you are a registered relay agent (a spawned worker, or a lead that called register_agent) coordinating with peers in real time over current Agent Relay MCP tools - messaging, channels, threads, reactions, search, inbox, actions, and worker spawn/release. For role selection and orchestrator startup instructions, use https://agentrelay.com/skill and the orchestrating-agent-relay skill.
Instalare
npx skills add AgentWorkforce/relay --skill using-agent-relay -a claude-code
Se instalează în .claude/skills/using-agent-relay/ · 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: APACHE-2.0
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