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.
48.168 de skill-uri din 2.325 de depozite · actualizat acum 16 ore
47.055 de skill-uri
- optimizing-performanceCloudAI-X/claude-workflow-v2Analyzes and optimizes application performance across frontend, backend, and database layers. Use when diagnosing slowness, improving load times, optimizing queries, reducing bundle size, or when asked about performance issues.DateFără avertismente★ 1,4 K↓ —
- twitter-algorithm-optimizerComposioHQ/awesome-claude-skillsAnalyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.RedactareFără avertismente★ 78,4 K↓ —Apare și în 1 alt depozit
- session-comparehoangsonww/Claude-Code-Agent-MonitorCompare two sessions side-by-side using Agent Monitor data — per-model token usage (input/output/cache_read/cache_write + compaction baselines), pricing engine cost breakdowns, workflow intelligence (complexity scores, tool flow transitions, subagent effectiveness), session metadata (thinking_blocks, turn_count, turn_duration_ms, usage_extras), and full event timelines with all 10+ event types.ProductivitateFără avertismente★ 1,1 K↓ —
- inbox-setupalirezarezvani/claude-skillsUse when setting up email triage for the first time, before inbox-triage, or when priorities change. Interviews the user one question at a time and writes the knowledge base inbox-triage reads, validated with kb_validator.py.RedactareFără avertismente★ 29,1 K↓ —
- minutes-briefsilverstein/minutesFast non-interactive briefing before any meeting — auto-detects your next calendar event, pulls relationship history, surfaces open commitments, and produces a one-page brief in under 30 seconds. Use this whenever the user says "brief me", "give me a quick brief", "what's coming up", "background on my next call", "who am I meeting next", "brief me on Sarah", "I have a call in 10 min", "quick rundown", or right before walking into a meeting. Different from /minutes-prep — brief is the fast hook-fireable version that doesn't ask questions and doesn't set goals. Use brief when speed matters; use prep when the user wants to think hard about goals first.ProductivitateFără avertismente★ 1,6 K↓ —Apare și în 1 alt depozit
- 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; 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★ 27,8 K↓ —
- minutes-x1-closeoutsilverstein/minutesPrepare a sourced Minutes meeting outcome for human-governed closeout of existing X1 work. Use when the user wants a meeting decision or commitment to close, defer, escalate, or retire a specific X1 coordination thread. Never use it to infer settlement, move money, contact anyone, or close X1 work automatically.PlanificareFără avertismente★ 1,6 K↓ —Apare și în 1 alt depozit
- minutes-notesilverstein/minutesAdd a note to the current recording or annotate a past meeting. Use whenever the user says "note that", "remember this", "mark this as important", "add a note about", "annotate the meeting", or wants to capture a thought during or after a recording. Plain text input — no markdown needed.ProductivitateFără avertismente★ 1,6 K↓ —Apare și în 1 alt depozit
- minutes-recordsilverstein/minutesStart or stop recording a meeting, call, or voice memo. Use this whenever the user says "record", "start recording", "capture this meeting", "stop recording", "I'm in a meeting", "take notes on this call", or wants to transcribe live audio. Also use when they ask about recording status or want to know if something is being recorded.MediaFără avertismente★ 1,6 K↓ —Apare și în 1 alt depozit
- minutes-listsilverstein/minutesList recent meetings and voice memos. Use when the user asks "what meetings did I have", "show my recent recordings", "any meetings today", "list my voice memos", or wants an overview of their meeting history. Also use when they need to find a specific meeting by browsing rather than searching.PlanificareFără avertismente★ 1,6 K↓ —Apare și în 1 alt depozit
- 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★ 27,8 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★ 27,8 K↓ —Apare și în 1 alt depozit
- ap-intakeSpielewoy/autoprompt-skillReport the compatibility redirect to `C0`; this retired role cannot perform new work.AlteleFără avertismente★ 1,2 K↓ —
- ap-workerSpielewoy/autoprompt-skillProduce only the assigned result, protect other owners' work, run the listed checks, and report an exact conflict instead of expanding scope.AlteleFără avertismente★ 1,2 K↓ —
- cscw-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning a CSCW submission timeline end to end — the PACMHCI journal model, the retired fixed cycles versus the rolling 2027+ pathway, Revise-and-Resubmit rounds that span months, and back-planning so an acceptance lands before the conference-year presentation cutoff.ProductivitateFără avertismente★ 1,3 K↓ —
- researchNoudaveebbelaar/bamaOnline research for a macOS app before building it, run as parallel researcher subagents, saved to docs/research/. Use when the user asks what to build, which features matter, how the best apps in a category work, how a macOS API or integration works, or wants a feature comparison.ȘtiințăFără avertismente★ 1 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★ 11,2 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★ 11,2 K↓ —
- minutes-searchsilverstein/minutesSearch past meeting transcripts and voice memos for specific topics, people, decisions, or ideas. Use this whenever the user asks "what did we discuss about X", "find that meeting where we talked about Y", "what did Alex say", "did we decide on", "what was that idea about", or any question that could be answered by searching their meeting history. Also use for "do I have any notes about" or "check my meetings for".PlanificareFără avertismente★ 1,6 K↓ —Apare și în 1 alt depozit
- ap-scope-coordinatorSpielewoy/autoprompt-skillReport the compatibility redirect to `ap-run-coordinator`; this retired role cannot perform new work.AlteleFără avertismente★ 1,2 K↓ —
- cvpr-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning a CVPR submission campaign end to end, covering the November abstract/paper/supplement deadline chain, coauthor reviewer-duty scheduling, the January rebuttal sprint, February decisions, camera-ready and June conference logistics, and the resubmission ladder across ICCV, ECCV, and the next CVPR.ProductivitateFără avertismente★ 1,3 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★ 11,2 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★ 11,2 K↓ —
- bamaNoudaveebbelaar/bamaBuild any Mac app. Start here to pick the next skill for a native macOS app.AlteleFără avertismente★ 1 K↓ —