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
- 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
- electronfcakyon/claude-codex-settingsAutomate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include "automate Slack app", "control VS Code", "interact with Discord app", "test this Electron app", "connect to desktop app", or any task requiring automation of a native Electron application.TestareFără avertismente★ 1,2 K↓ —
- retrodzhng/skillsConduct a retrospective on a coding session.InginerieFără avertismente★ 1,4 K↓ —
- asc-id-resolverrorkai/app-store-connect-cli-skillsResolve App Store Connect IDs (apps, builds, app and digital-goods versions, groups, testers) from human-friendly names using asc. Use when commands require IDs.AlteleFără avertismente★ 1,1 K↓ —
- searchtaishi-i/awesome-japanese-nlp-resourcesSearch all Japanese NLP resources (libraries, models, datasets, tutorials, dictionaries, Hugging Face). Accepts keywords or natural language questions in any language. Use whenever the user asks which Japanese NLP resource to use, or wants to find one: tokenizers / morphological analyzers, BERT or LLM models, embeddings, NER, text classification, datasets / corpora, dictionaries, tutorials, or Hugging Face models. Trigger phrases include '日本語の形態素解析ライブラリ', 'おすすめの日本語tokenizer', '日本語BERTモデル', '日本語の感情分析データセット', '日本語LLM 一覧', 'which Japanese embedding model', 'Japanese NER library'.AlteleFără avertismente★ 1 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↓ —
- jetson-init-imageNVIDIA/skillsExtract Jetson Linux + sample-rootfs tarballs and run apply_binaries.sh for the active target, then record bsp_image in the profile. Use after jetson-init-target; not for source-tree setup.MediaFără avertismente★ 3,9 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↓ —
- 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↓ —
- tddhashgraph-online/awesome-codex-pluginsTest-first cycle and red-step evidence rule for skills that implement behavior a test can assert. Binds when the verification skill resolves a test command; defines what the red run must quote and when the cycle is skipped with a reason.TestareFără avertismente★ 1,5 K↓ —
- build-and-verifydaveebbelaar/bamaBuild a SwiftUI macOS app from the command line, install it, and check light and dark window snapshots of every page before calling a change done. Use after any UI code change, when a build fails, or when the user asks to run, screenshot, or check the app.DesignFără avertismente★ 1,5 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↓ —
- recording-architecture-decisionsGanyuanRan/AegisUse when the user asks to create, write, update, amend, supersede, or evaluate an ADR, architecture decision record, durable architecture decision, decision log, or baseline sync after architecture-changing work.PlanificareFără avertismente★ 1,4 K↓ —
- minutes-video-reviewsilverstein/minutesAnalyze a product walkthrough, bug report video, Loom, or ScreenPal using Minutes transcription plus visual review. Use when the user wants a recorded demo or bug clip turned into a durable brief with transcript, key frames, issues, and next steps.MediaFără avertismente★ 1,6 K↓ —Apare și în 1 alt depozit
- ap-independent-checkerSpielewoy/autoprompt-skillIndependently review the exact result and run its real checks in one context, using isolated resources and without changing the deliverable.InginerieFără avertismente★ 1,2 K↓ —
- design-routerhashgraph-online/awesome-codex-pluginsUse when the user asks to build, design, mock up, scaffold, audit, translate, or improve any interface, flow, screen, page, component, app, UX, onboarding, checkout, dashboard workflow, product flow, design system, asset plan, motion plan, or non-generic UI and the target platform or flow is ambiguous. Routes to ux-design, web, Windows, Apple, Android, cross-platform, design-token, originality, asset/reference, and platform skills. SKIP when the request explicitly names one platform and no UX flow work is implied.DesignFără avertismente★ 1,5 K↓ —
- book-drafthashgraph-online/awesome-codex-pluginsPhase 3: Drafting. Voice lock on a sample chapter, then sequential full-context chapter drafting with draft-critique-revise, bible ledger updates, and periodic continuity checks.ProductivitateFără avertismente★ 1,5 K↓ —
- triggershashgraph-online/awesome-codex-pluginsCreate and manage triggers that watch for something (a job that finishes, a service that goes down, a failing CI run, a new release, a price crossing a threshold) and hand a task to Codex when it happens. Use when the user wants to be told, or wants something done, "when X happens", and when handling a message that starts with [self-starter].ProductivitateFără avertismente★ 1,5 K↓ —
- dispatching-parallel-agentsGanyuanRan/AegisUse when facing 2+ independent tasks without a written plan, with no conflicting shared mutable state or sequential dependencies, where parallel delegation beats inline cost; otherwise inline. Planned tasks use subagent-driven-development.RedactareFără avertismente★ 1,4 K↓ —
- stoc-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning a STOC (ACM Symposium on Theory of Computing) project calendar — backward planning to the early-November deadline, the STOC/FOCS alternating two-deadline year that theory groups schedule around, full-version and camera-ready milestones, and the June TheoryFest endpoint.ProductivitateFără avertismente★ 1,4 K↓ —
- evalhashgraph-online/awesome-codex-pluginsEval-Driven Development (EDD) for AI workflows. pass@k metrics, capability evals, regression evals. Triggers: eval, edd, pass@k, capability, regression, benchmark.AlteleFără avertismente★ 1,5 K↓ —
- minutes-release-notessilverstein/minutesDraft user-facing Minutes release notes for a version from the commit range, recent GitHub releases, and the repository release checks. Use when the user asks to write, generate, prepare, revise, or review release notes or a changelog for a Minutes version.ProductivitateFără avertismente★ 1,6 K↓ —Apare și în 1 alt depozit
slo-check
hoangsonww/Claude-Code-Agent-Monitor
InginerieActualizat acum 18 ore
De la autor
Define and check simple service-level objectives for Claude Code from Agent Monitor data — session completion rate, tool success rate (PostToolUse/PreToolUse), and error rate (APIError/total) — then compare each to its target and report the error budget remaining. Use when reporting reliability or when someone asks "are we meeting our SLOs?".
Instalare
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill slo-check -a claude-code
Se instalează în .claude/skills/slo-check/ · 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 instrucțiuniFolosește rețeauaLicență: MIT
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 88
Securitate100
Proveniență77
Întreținere100
Licență100
Adopție49
Fișiere (2)
- SKILL.md
- agents/openai.yaml