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 3 ore
49.409 skill-uri
- cost-breakdownhoangsonww/Claude-Code-Agent-MonitorBreak down Claude Code costs using the Agent Monitor pricing engine. Shows per-model costs (input, output, cache_read, cache_write at $/Mtok rates), per-session costs, daily trends, and compaction baseline token recovery. Use when analyzing spending, comparing model costs, or planning budgets.PlanificareFără avertismente★ 1,1 K↓ —
- endpoint-probehoangsonww/Claude-Code-Agent-MonitorProbes each major Agent Monitor API route — /api/stats, /api/analytics, /api/sessions, /api/pricing/cost, /api/workflows/runs, /api/cc-config/overview — and reports each one's HTTP status, latency, and response shape, flagging which are reachable. Use to verify a dashboard install is wired up correctly.DateFără avertismente★ 1,1 K↓ —
- redis-semantic-cacheredis/agent-skillsRedis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.OficialInginerieFără avertismente★ 172↓ —Apare și în 1 alt depozit
- dag-maphoangsonww/Claude-Code-Agent-MonitorRender the multi-agent orchestration DAG for a session — parent→child subagent edges, tree depth, and fan-out — from the Agent Monitor workflow intelligence API. Cross-checks the orchestration dataset against the raw agent records and session detail. Use when visualizing how a session's agent structure was organized.MediaFără 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↓ —
- add-pdf-viewermicrosoft/power-platform-skillsInternal implementation skill invoked by /add-native for native PDF control workflows. Handles HTTPS and file URI PDF viewing with @microsoft/power-apps-native-pdf-viewer 0.2.9+.DocumenteFără avertismente★ 1,1 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↓ —
- error-scanhoangsonww/Claude-Code-Agent-MonitorScan recent Claude Code activity for errors and failure signals across all sessions using Agent Monitor data — APIError events and PreToolUse→PostToolUse gaps (tools that started but never completed) — then group failures by tool and model and rank them by frequency. Use when checking for errors or asking "what's failing right now".InginerieFără avertismente★ 1,1 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↓ —
- run-historyhoangsonww/Claude-Code-Agent-MonitorInspect CCAM dashboard-run history and relate live run handles to persisted Claude Code or Codex sessions. Use when finding a prior launched task, checking whether a run is still attached, reviewing start/end status, or deciding whether to resume, view, or relaunch work.InginerieFără avertismente★ 1,1 K↓ —
- cost-reporthoangsonww/Claude-Code-Agent-MonitorProduce a scoped CCAM cost and token report by model, provider, source, and session. Use for spend reviews, model-mix analysis, unpriced usage detection, or export-friendly cost summaries.ProductivitateFără avertismente★ 1,1 K↓ —
- model-mixhoangsonww/Claude-Code-Agent-MonitorBreak down Claude Code usage by model family (Opus / Sonnet / Haiku) from the Agent Monitor dashboard — each family's share of tokens, share of cost, and the spots where an expensive model is doing cheap work. Pulls per-model token and cost splits from /api/pricing/cost, current rates from /api/pricing, fleet token totals from /api/analytics, and per-session model assignment from /api/sessions. Use when deciding model routing or whether to downshift work to a cheaper tier.DateFără avertismente★ 1,1 K↓ —
- cav-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a CAV (Computer Aided Verification) submission against the verification literature across CAV, TACAS, FMCAD, VMCAI, POPL/PLDI, and the journals (FMSD, JAR, TOCL, STTT), writing delta-first contrast rather than a citation catalog, crediting the right benchmark and tool lineages, keeping self-citations double-anonymous for the anonymized categories, and handling concurrent and prior-version overlap.RedactareFără avertismente★ 1,4 K↓ —
- handbook-pagemohitagw15856/pm-claude-skillsWrite the handbook page that ends the repeated explanation — the answer-shaped structure (task-first, context second), the ownership and freshness header, and the write-once-point-forever discipline that turns tribal knowledge into infrastructure. Use when asked document how we do X, write the wiki page for this process, I explain this every month, or make this knowledge survive me. Produces the page with task-first structure, the header block, the worked example, and the pointer habit.DevOpsFără avertismente★ 1,5 K↓ —
- stoc-submissionbrycewang-stanford/Awesome-Journal-SkillsUse when auditing a STOC (ACM Symposium on Theory of Computing) submission for HotCRP readiness — the abstract + table-of-contents + first-12-pages reading rule, single-column 11-point format, double-blind hygiene, the SIGACT prior/simultaneous-publication policy, and deadline-week sequencing before the November cutoff.AlteleFără avertismente★ 1,4 K↓ —
- form-explainermohitagw15856/pm-claude-skillsExplain an official form field by field (tax, benefits, immigration, employment, school, health, vehicle or court forms) from a photo, PDF, pasted text or just its name and number: what it is for, what each field means and what to put, the documents needed, the deadline, and where to send it. Use when someone says 'what is this form', 'help me understand form P45 / W-4 / Form 16', 'what do I write in this box', or 'I got this form in the post'. Produces a one-line purpose, a field-by-field guide, a documents checklist, common mistakes, and what happens next.DocumenteFără avertismente★ 1,5 K↓ —
- graphifyhashgraph-online/awesome-codex-plugins将 Graphify 作为可选知识图谱能力接入，用于 brownfield 结构扫描、依赖路径分析与架构问答。 不替代 `/team-*` 主链；输出统一回落到 handoff 与 artifacts 证据。AlteleFără avertismente★ 1,5 K↓ —
- reflectalirezarezvani/claude-skillsUse when the user says 'step back', 'zoom out', 'are we on track' or 'sanity check this', or work has gone deep into details without a check on direction. Reassesses direction, assumptions and bias across five dimensions.AlteleFără avertismente★ 29,2 K↓ —Apare și în 1 alt depozit
- i18n-parityhoangsonww/Claude-Code-Agent-MonitorMANDATORY for every coding agent and contributor touching localized content — keep all five localization surfaces (dashboard UI keys, wiki page, full mirrored guides, locale-aware formatting, language switchers) in parity across every supported language. Use automatically (without being asked) whenever you add or change user-visible UI copy, add an i18n key, edit README-EN.md or a localized guide, edit wiki/index.html, or add a language surface.DesignFără avertismente★ 1,1 K↓ —Apare și în 1 alt depozit
- masking-budgetmohitagw15856/pm-claude-skillsTreat neurodivergent masking as a daily energy budget — audit what passing as neurotypical actually costs you, where the spend is worth it, where you can safely drop the mask, and how to plan a heavy-masking day so you don't crash after. Use when someone says 'I'm exhausted from masking', 'work drains me and I don't know why', 'how do I unmask safely', or is autistic/AuDHD/ADHD and burning out socially. Produces a mask-cost audit, a spend/drop map, and a recovery plan. A self-knowledge tool, not a diagnosis or therapy.PlanificareFără avertismente★ 1,5 K↓ —
- teamhashgraph-online/awesome-codex-pluginsOrg-level agent team designer via `epic team` CLI (cross-project, append-merge). Subcommands: list, show, sync, link, unlink, history. Use when setting up agents, designing teams, or /spec yields 3+ requirements.PlanificareFără avertismente★ 1,5 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↓ —
- implementing-command-palettesAgentWorkforce/relayUse when building Cmd+K command palettes in React - covers keyboard navigation with arrow keys, keeping selected items in view with scrollIntoView, filtering with shortcut matching, and preventing infinite re-renders from reference instabilityMediaFără avertismente★ 1,1 K↓ —
cell-writing
brycewang-stanford/Awesome-Journal-Skills
RedactareActualizat 27 sept. 2026
De la autor
Use to structure a Cell Article and hold its length — Summary, Introduction, Results, Discussion, STAR Methods, figure legends, references — with main-text length and display-item budgets, and Results subheadings driving the single arc.
Instalare
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cell-writing -a claude-code
Se instalează în .claude/skills/cell-writing/ · 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: MIT
Verificări de siguranță pe SKILL.md
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De ce 88
Securitate100
Proveniență77
Întreținere100
Licență100
Adopție50
Fișiere (1)
- SKILL.md