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 1 oră
49.409 skill-uri
- productivity-scorehoangsonww/Claude-Code-Agent-MonitorCalculate a productivity score using actual Agent Monitor metrics — session completion rates, cache efficiency (cache_read vs input), compaction pressure (baseline tokens), turn velocity (turn_count / total_turn_duration_ms), tool success ratio (PreToolUse vs PostToolUse), and the workflow intelligence API's complexity and effectiveness scores.InginerieFără avertismente★ 1,1 K↓ —
- history-portabilityhoangsonww/Claude-Code-Agent-MonitorImport Claude Code or Codex history and move complete CCAM datasets between machines. Use when rescanning provider history, importing a copied directory, uploading JSONL or archives, exporting a backup, restoring it idempotently, or verifying that tokens, workflows, runs, rules, and pricing survived.InginerieFără avertismente★ 1,1 K↓ —
- sprint-summaryhoangsonww/Claude-Code-Agent-MonitorSummarize a sprint's worth of Claude Code activity — sessions grouped by project (cwd), per-model cost breakdown, token efficiency (cache hit rate, compaction baselines), subagent effectiveness from workflow API, velocity metrics (turn_count, turn_duration_ms), and tool diversity across the sprint.ProductivitateFără avertismente★ 1,1 K↓ —
- azure-usagefcakyon/claude-codex-settingsThis skill should be used when user asks to "query Azure resources", "list storage accounts", "manage Key Vault secrets", "work with Cosmos DB", "check AKS clusters", "use Azure MCP", or interact with any Azure service.DevOpsFără avertismente★ 1,2 K↓ —
- judge-group-closuresno-ai/sno-stationJudge which offered rows one nominated statement retires or replaces.AlteleFără avertismente★ 1,1 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★ 11,3 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↓ —
- 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↓ —
- ad-campaign-analyzergooseworks-ai/goose-skillsAnalyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.MarketingFără 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★ 11,3 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↓ —
- research-competitors-edge-casesgooseworks-ai/goose-skillsStep of the research-competitors playbook: rules for run edge cases such as no browser, stalled workers, earlier reports and late reads. Run research-competitors instead; not for direct use.ȘtiințăFără avertismente★ 1,3 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↓ —
- email-lifecycle-lifecycle-auditgooseworks-ai/goose-skillsStep of the email-lifecycle playbook: audits list, consent, live flows, recent sends and sending setup, marking every item verified, from-you or unknown. Run email-lifecycle instead; not for direct use.ProductivitateFără avertismente★ 1,3 K↓ —
- dashboard-statushoangsonww/Claude-Code-Agent-MonitorQuick dashboard health and status overview — checks the Agent Monitor API (port 4820), reports session/agent/event counts from /api/stats, confirms WebSocket connectivity, reads the redacted hook status returned by /api/settings/info, and shows data freshness (last event timestamp). Use to verify the monitoring system is operational.InginerieFără avertismente★ 1,1 K↓ —
- goose-product-photosgooseworks-ai/goose-skillsMake product photos (studio, lifestyle or on a model) of a brand's real products with GooseWorks in this chat. Start brand work with brand_knowledge_browse and follow the next_step in every answer.MediaFără avertismente★ 1,3 K↓ —
- doca-ethNVIDIA/skillsUse this skill for hands-on DOCA Ethernet packet-queue work on a BlueField DPU or ConnectX NIC — bringing up a `doca_eth_rxq` or `doca_eth_txq` on a port / representor / SF, picking among the four `enum doca_eth_rxq_type` values (`_REGULAR` / `_CYCLIC` / `_MANAGED_MEMPOOL` / `_SHARED_MEMPOOL`), sizing burst or scatter-gather length against the `_cap_*` queries, submitting `doca_eth_txq_task_send` / `_lso_send` (carrying packet `doca_buf`s — no `doca_eth_frame` struct exists), or debugging DOCA_ERROR_* from an Ethernet call. `doca_eth_rxq` and `doca_eth_txq` are two Core contexts; one `doca_ctx_start()` does not cover both. Trigger on implicit phrasings: "my RX queue is up but no packets arrive", "send-task returns AGAIN at line rate", "which queue type for fixed-MTU ingress", "device open fails without sudo", or "is L3 checksum offload available here". Refuse and route elsewhere for installing DOCA, flow-rule / steering programming, host↔DPU control messaging, or RDMA data movement.InginerieFără avertismente★ 3,8 K↓ —
- session-timelinehoangsonww/Claude-Code-Agent-MonitorRender an ordered timeline of one Claude Code session's events (every event type) with per-event durations and tool names, reconstructed from Agent Monitor data. Pairs PreToolUse with PostToolUse to compute tool durations and surfaces gaps, errors, and compaction points. Use when reconstructing what happened in a session step by step.MediaFără avertismente★ 1,1 K↓ —
- write-docsdzhng/skillsWrite and edit project docs (README/markdown) as a glossary of principles, not a mirror of the code. Use when creating or revising a README; when a doc enumerates exact scenes, scenarios, helpers, class ids, file lists, or command/flag matrices the code already holds; when trimming narrative or changelog out of a doc; or when deduplicating overlapping docs and wiring a root doc to its sub-docs.RedactareFără avertismente★ 1,4 K↓ —
- oma-dbfirst-fluke/oh-my-agentDesign schemas and migrations, tune queries, or plan vector retrieval and database operations. Application API implementation uses oma-backend.DateFără avertismente★ 1,4 K↓ —
- cache-efficiencyhoangsonww/Claude-Code-Agent-MonitorAnalyze prompt-cache effectiveness for Claude Code usage from the Agent Monitor dashboard — cache hit rate (total_cache_read / (total_cache_read + total_input)), cache_write vs cache_read reuse, cache-read vs cache-write spend, and the sessions with the poorest reuse. Pulls token totals from /api/analytics, per-session detail from /api/sessions, and dollar splits from /api/pricing/cost. Use when diagnosing cache spend or deciding whether prompt caching is paying off.DateFără avertismente★ 1,1 K↓ —
- design-fixhashgraph-online/awesome-codex-pluginsCompare one already-implemented screen or component against its Figma source and fix the deviations you pick -- reads the node live through the figma-bridge MCP, or from the Node Specs of an existing /design plan, then diffs box, layout, typography, fill, stroke, radius, effects, and content against the code that renders it. Reports first, fixes only what you select, and never touches Figma.DesignFără avertismente★ 1,5 K↓ —
- budget-sethoangsonww/Claude-Code-Agent-MonitorDefine a spend budget for Claude Code and, optionally, create a cost alert rule that fires when usage crosses the limit, via POST /api/alerts/rules on the Agent Monitor dashboard. Reads current spend from /api/pricing/cost to size the budget sensibly and explains every rule field before writing. Use when setting a spend limit or wiring up a budget guardrail.RedactareFără avertismente★ 1,1 K↓ —
- data-exporthoangsonww/Claude-Code-Agent-MonitorExport Claude Code session and analytics data in JSON, CSV, or Markdown formats. Supports exporting sessions, events, costs, and analytics for external analysis or reporting. Use for data backup or integration.DateFără avertismente★ 1,1 K↓ —
hri-writing-style
brycewang-stanford/Awesome-Journal-Skills
De la autor
Use 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.
Instalare
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill hri-writing-style -a claude-code
Se instalează în .claude/skills/hri-writing-style/ · 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
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- SKILL.md