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 16 ore
49.492 de skill-uri
- content-factoryhuytieu/COG-second-brainAutonomous content pipeline - scout announcements in your field, triage by trend momentum and personal angle, produce posts/blogs/videos in your voice with ledger-based dedup, hard volume caps, and screenshot-verified publishingAlteleFără avertismente★ 1,3 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↓ —
- shopify-productsjezweb/claude-skillsCreate and manage Shopify products via the Admin GraphQL API or CSV import. Workflow: gather data, choose method, execute, verify. Use whenever the user wants to add products to Shopify, bulk-import a catalog from CSV/spreadsheet/URL, update variants or prices, manage inventory quantities, upload product images, or assign products to collections.DateFără avertismente★ 1,1 K↓ —
- codex-reviewjezweb/claude-skillsRun an independent code review using the OpenAI Codex CLI in headless mode. Gets a second opinion from a different model family (the current Codex models) on recent changes, a PR, a commit, or the whole app — covering bugs, regressions, security, data consistency, UX/state bugs, performance risks, and testing gaps. Saves a severity-prioritised report to .jez/reviews/. Triggers: 'codex review', 'review with codex', 'independent code review', 'what does codex think', 'get codex to review'.InginerieFără avertismente★ 1,1 K↓ —
- goose-video-localgooseworks-ai/goose-skillsMake an approved GooseWorks video when an answer's next_step gives its command.MediaFără avertismente★ 1,3 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↓ —
- 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↓ —
- sdd-riperalibaba/skill-upSDD-RIPER workflow executor with phase gatingProductivitateFără avertismente★ 1,4 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↓ —
- 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↓ —
- 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; Gemini 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. The session-end hook reports status only; it does not request continuation or run 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↓ —
- 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↓ —
- nanoresearch-experimentOpenRaiser/NanoResearchGenerate a Python code skeleton from an experiment blueprintInginerieFără avertismente★ 1,3 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↓ —
- designhashgraph-online/awesome-codex-pluginsUse for standard or complex new work before coding or planning. Also handles vague goals — clarifies before designing.DesignFără avertismente★ 1,5 K↓ —
- honest-reviewgooseworks-ai/goose-skillsShared step of the marketing playbooks (make-static-ads, run-organic-social): how to review generated images and video honestly. Covers what was seen by eye versus read automatically, findings framed as things for the human to confirm, remakes only after a yes to the price, and at most two tries per item. Loaded by those playbooks; not for direct use.InginerieFără avertismente★ 1,3 K↓ —
- fixing-flaky-testsamplifthq/openmeldGuides an agent through reproducing, root-causing, fixing, and validating flaky tests in the PostHog monorepo. Use when a test fails intermittently in CI but passes on rerun or locally, when `hogli ci:insights` or the debugging-ci-failures skill classifies a failure as a flaky test, when given a GitHub Actions URL for a flaky job, when asked to check Trunk Flaky Tests for a test, PR, or master, or when asked to deflake, stabilize, or fix a flaky Jest, pytest, or Playwright test. Core discipline: reproduce locally before changing anything, fix the root cause (never mask it with sleeps, retries, or bigger timeouts), and prove the fix with an N-run validation loop sized to the observed failure rate. Stabilizing is not the only valid outcome — the skill also gates whether the test should exist, so deleting a test that catches nothing real, or re-leveling one that flakes because of the level it runs at, are first-class endings.TestareFără 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↓ —
- 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↓ —
- ad-creativealirezarezvani/claude-skillsUse for any ad copy request (RSA headlines, Meta, LinkedIn or TikTok ads, bulk variations), before writing. Checks every line against platform character limits and policy with ad_copy_validator.py. Campaign strategy and budgets: paid-ads.MarketingFără avertismente★ 29,3 K↓ —
- 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↓ —
- slo-checkhoangsonww/Claude-Code-Agent-MonitorDefine 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?".InginerieFără avertismente★ 1,1 K↓ —
- run-agenthoangsonww/Claude-Code-Agent-MonitorLaunch and supervise Claude Code or Codex through the CCAM Run API. Use when the user wants to start a monitored agent, select a model, approval policy, sandbox, or working directory, send a follow-up, inspect live output, resume a native session, or stop a dashboard-launched run.InginerieFără avertismente★ 1,1 K↓ —
- mcp-mocked-markeralibaba/skill-upMCP mocked marker smoke skill used by skill-up e2e tests.TestareFără avertismente★ 1,4 K↓ —
jama-scope-fit
brycewang-stanford/Awesome-Journal-Skills
DesignActualizat 27 sept. 2026
De la autor
Use when judging whether a clinical study clears JAMA's general-medical-importance bar before investing in a full submission. Assesses fit and article-type match; it does NOT design the study or write the paper.
Instalare
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jama-scope-fit -a claude-code
Se instalează în .claude/skills/jama-scope-fit/ · 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
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Proveniență77
Întreținere100
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Fișiere (1)
- SKILL.md