Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
49,495 skills from 2,391 repositories · updated 26 minutes ago
48,455 skills
- make-static-ads-claims-extractgooseworks-ai/goose-skillsStep of the make-static-ads playbook: pulls every claim-bearing span out of an ad — the copy around the image, the on-image words in the prompt, badges, and what the picture implies — and keeps or cuts each by the brand-brain rule. Runs before spend on the finished prompt (Pass A) and on every render (Pass B). Run make-static-ads instead; not for direct use.MarketingNo warnings★ 1.3K↓ —
- video-skillsNewhashgraph-online/awesome-codex-pluginsFinds the right agent skill for an AI video, image, voice or music job on varg how to (varg.ai/how-to, 2,000+ checked skills and how-to tutorials: UGC ads, ad variants, product videos, music and lyric videos, captions, talking avatars, podcast videos, faceless channels, explainers, launch and changelog videos, slideshows, chat-story and Notes ads, logo stings, dubbing, thumbnails, shorts from long videos) and shows the person the visual options before anything is generated. Use when someone asks to make, edit, caption, voice, dub or animate a video, asks "which skill should I use", "find a skill for", "how do I make a ... video", or wants images, voiceover or music for a video, and no installed skill already covers that format; use it before writing a pipeline from scratch or searching registries. Not for running a generation itself (use varg-ai), not for formats with their own varg skill (varg-music-video, varg-character-keynote, varg-consistent-characters, varg-character-design, varg-podcast-video, varg-proMediaNo warnings★ 1.5K↓ —
- make-content-source-to-unitsgooseworks-ai/goose-skillsStep of the make-content playbook: mines one finished asset into scored quotable units and maps a different lead unit to each platform. Run make-content instead; not for direct use.OtherNo warnings★ 1.3K↓ —
- cloudbase-cliTencentCloudBase/CloudBase-AI-ToolkitCloudBase CLI (tcb, 云开发CLI, Tencent CloudBase命令行) resource management skill. Use when deploying cloud functions, CloudRun, storage, NoSQL/MySQL, static hosting, permissions, CORS/domains via tcb; for CI/CD and batch ops; when the user prefers CLI; or as the first-session fallback when CloudBase MCP tools are not loaded yet (after install/config, before IDE restart). Also covers tcb login and site switching (国内站/国际站 via --intl or config isIntl), environment lifecycle (env create/modify/renew/delete/apikey/login/domain), tcb config and cloudbaserc.json sync, log search (logs search, CLS), metric monitoring (monitor), data model and PostgreSQL migrations (db model, db pg migration), sandbox/agent/integration management — do not default to tcb deploy.EngineeringNo warnings★ 1.2K↓ —Also in 5 other repos
- cohort-analysismohitagw15856/pm-claude-skillsStructure a cohort analysis for retention, LTV, or behavioural patterns. Use when asked to run a cohort analysis, analyse retention by cohort, segment users by behaviour over time, or calculate lifetime value by acquisition period. Produces a complete cohort analysis framework with methodology, cohort definitions, retention curves, and prioritised interventions.OtherNo warnings★ 1.5K↓ —
- jetson-llm-serveNVIDIA/skillsStand up vLLM or SGLang serving on Jetson, using upstream vLLM on Thor and Orin JetPack 7.2+, and NVIDIA-AI-IOT vLLM on older Orin.OtherNo warnings★ 3.9K↓ —
- cn-level-mappermohitagw15856/pm-claude-skillsCompare job levels (职级) across Chinese technology companies and against international ladders, to judge an offer, a job move or a promotion target: what a level usually means in scope and expectations, how levels roughly line up, and what to ask the recruiter. Use when asked P7 相当于什么级别, 跳槽职级怎么对标, 字节 2-2 对应阿里什么, 这个 offer 的职级合理吗, compare Chinese tech levels, or how does Alibaba P-level map to Google levels. Produces a level comparison built from the person's own ladders and offer details, a scope-and-expectation profile for each level, the negotiation questions to ask, and a clear note on what is approximate.ProductivityNo warnings★ 1.5K↓ —
- brief-from-pilemohitagw15856/pm-claude-skillsTurn a folder of accumulated documents into one decision-ready brief — the skim-map pass over the pile, the extraction against the brief's actual questions, the conflict reconciliation when documents disagree, and the provenance trail back to sources. Use when asked read all this and tell me what matters, synthesize this folder for the new lead, turn these 20 docs into a brief, or what does all this material actually say. Produces the pile map, the question-driven extraction, the reconciled brief with per-claim sources, and the didn't-read honesty ledger.OtherNo warnings★ 1.5K↓ —
- bom-cost-reviewmohitagw15856/pm-claude-skillsReview a bill of materials for cost, risk, and supply exposure — cost rollup, top-10 cost drivers, single-source and EOL risk, MOQ vs forecast mismatch, cost-down candidates, and tariff/logistics sensitivity. Use when asked to review a BOM, find cost-down opportunities, check component sourcing risk, or sanity-check BOM cost against target. Produces a structured BOM review with a cost driver Pareto, risk flags per line, and a prioritised cost-down list.EngineeringNo warnings★ 1.5K↓ —
- bank-fee-refundmohitagw15856/pm-claude-skillsGet a bank fee waived or refunded — overdraft, late, maintenance, ATM, or foreign-transaction — with the ask written and the leverage that works. Use when asked to get a bank fee refunded, waive my overdraft fee, the bank charged me a fee, or how to get charges reversed. Produces a read on which fees are commonly reversible, the script to request a refund (in person, chat, or call), the loyalty/first-time/error leverage to use, and how to prevent the fee recurring — plus when to escalate or switch banks.WritingNo warnings★ 1.5K↓ —
- attention-resetmohitagw15856/pm-claude-skillsGet your attention back with a 30-day protocol that assumes you'll break it — a screen-time ledger without moralizing, friction engineering (what to delete, grayscale, where the phone sleeps), planned relapses, and honest replacement activities for the boredom that shows up on day 3. Use when someone says 'my screen time is 7 hours', 'I want a dumbphone', 'digital detox', 'I can't read books anymore', or 'my attention span is gone'. Produces the ledger, a personal friction plan, and the 30-day protocol with expected failure points.PlanningNo warnings★ 1.5K↓ —
- plan-campaign-goal-chaingooseworks-ai/goose-skillsChecks whether a stated goal is reachable on a given budget: fills an economics box with a source on every number, subtracts the baseline, works out the implied cost per customer against history or labelled base rates, and flags when the goal needs renegotiating. Use alone when you already have the goal (metric, number, date), budget, order value, margin and baseline; otherwise run plan-campaign.MarketingNo warnings★ 1.3K↓ —
- render-flat-vector-explainergooseworks-ai/goose-skillsAssemble the FREE steps of the flat-vector-explainer video format — a flat-illustration host character (who, where, tone, voice and music come from the recipe choices) walks a countable N-step product routine, one step per beat, and Remotion composites every chip/numeral/tagline/slate/CTA as an animated DOM overlay ON TOP of the Kling i2v character clips (text is NEVER baked into a keyframe — i2v warps type), the closing 'N products' grid is a PIL composite of the REAL product photos (not AI), full-sentence VO drives word-by-word burned captions over a VO-forward music bed, and the ~50s animated silent master is re-cut to a 30s deliverable FROM the animated master (never a static intermediate). Documentation-grade — ships config.example.json + PIPELINE.md + a README of the free assembly; the paid gen steps (keyframes, Kling i2v, VO, music) are separate capabilities the recipe orchestrates. Use for the flat-vector-explainer format.MediaNo warnings★ 1.3K↓ —
- render-editorial-motion-podcastgooseworks-ai/goose-skillsAssemble an editorial-motion podcast-clip ad from a config — a real clipped podcast MP3 carries the narrative while N flat limited-palette editorial-illustration keyframes (one look pack) are animated NOT by generative i2v but by DETERMINISTIC ffmpeg ken-burns (zoompan) + hard cuts (no crossfades, which expose geometric drift), each beat snapped to its spoken line, the real audio muxed, Whisper-driven captions burned only mid-sentence, and closed on a PIL brand end card — never AI-rendered text. This is the FREE deterministic assembly stage (ffmpeg ken-burns + hard concat + audio mux + captions + end card); the real audio is clipped from source and the keyframes come from create-image-fal. Use for the editorial-motion-podcast format.MediaNo warnings★ 1.3K↓ —
- render-split-screen-creatorgooseworks-ai/goose-skillsAssemble a split-screen creator ad from a config: an AI-creator lip-sync take fills the bottom half while real 16:9 product or demo clips play uncropped in the top half over a blurred fill of the same clip (never black bars), with a brand-colour divider between them. Scenes follow the voiceover timing and are joined hard, an end card holds about 3 seconds, then the finished cut is transcribed and word-level captions are burned in the chosen style. Free, deterministic assembly and captions; the voiceover comes from create-vo-elevenlabs, the creator anchor from create-image-gpt-image-fal, and the lip-sync take is supplied as an input. Use for the split-screen-creator format.MediaNo warnings★ 1.3K↓ —
- aws-ami-builderhashicorp/agent-skillsBuild Amazon Machine Images (AMIs) with Packer using the amazon-ebs builder. Use when creating custom AMIs for EC2 instances.OfficialDevOpsNo warnings★ 911↓ —
- competitor-ad-intelligencegooseworks-ai/goose-skillsScrape competitor ads from Meta, TikTok, Google, and LinkedIn ad libraries, analyze creative patterns (hooks, formats, CTAs), reverse-engineer landing page funnels, and produce a strategic teardown with vulnerability analysis and counter-play recommendations. Use when you need to understand the competitive ad landscape, find new creative directions, or identify weaknesses in a competitor's paid strategy.MarketingNo warnings★ 1.3K↓ —
- oma-marketfirst-fluke/oh-my-agentResearch customer pain points, trends, and competitors through the OMA market engine. Use for market discovery or voice-of-customer analysis.ScienceNo warnings★ 1.4K↓ —Also in 2 other repos
- ecsitsmostafa/aws-agent-skillsAWS ECS container orchestration for running Docker containers. Use when deploying containerized applications, configuring task definitions, setting up services, managing clusters, or troubleshooting container issues.DevOpsNo warnings★ 1.2K↓ —
- eksitsmostafa/aws-agent-skillsAWS EKS Kubernetes management for clusters, node groups, and workloads. Use when creating clusters, configuring IRSA, managing node groups, deploying applications, or integrating with AWS services.DevOpsNo warnings★ 1.2K↓ —
- the-open-housemohitagw15856/pm-claude-skillsSimulate the open house and the listing agent's read of you — the questions that profile your budget and urgency, the staging that hides what inspection finds, and the offer-pressure choreography, run before you fall in love with anything. Use when asked what is the listing agent thinking, practice viewing a house, what should I not say at an open house, or simulate the offer pressure. Produces the walkthrough transcript with the agent's private profile of you, the what-the-staging-hides checklist, and a debrief on information discipline — what to ask, what to never volunteer.OtherNo warnings★ 1.5K↓ —
- ecai-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evidence in an ECAI paper — choosing proof versus experiment by claim shape across ECAI's breadth (theory/KR, planning/search, ML, multi-agent, applied), fair baselines, seeds and spread, honest ablations, and provenance, all supporting a claim inside a 7-page body.ScienceNo warnings★ 1.4K↓ —
- imc-supplementarybrycewang-stanford/Awesome-Journal-SkillsUse when deciding what belongs in an ACM IMC paper body versus its appendix and released artifact, covering the acmart page limits, the rule that decision-critical evidence and the Ethics discussion stay in the reviewed pages, double-blind supplementary material, and how to split a measurement paper between body, appendix, and dataset.ScienceNo warnings★ 1.4K↓ —
- acl-review-processbrycewang-stanford/Awesome-Journal-SkillsUse when reasoning about how an ACL paper travels through ACL Rolling Review and conference commitment, covering reviewer and area-chair roles, meta-reviews, the commitment decision by senior area chairs and program chairs, Findings versus main-conference outcomes, ethics review escalation, and resubmission strategy across cycles.EngineeringNo warnings★ 1.4K↓ —
huggingface-vision-trainer
huggingface/skills
OfficialMediaUpdated 5 days ago
From the author
Trains 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.
Install
npx skills add huggingface/skills --skill huggingface-vision-trainer -a claude-code
Installs to .claude/skills/huggingface-vision-trainer/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Runs bundled scriptsNo network use seenLicence: APACHE-2.0
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Security85
Provenance100
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Files (12)
- SKILL.md
- references/finetune_sam2_trainer.md
- references/hub_saving.md
- references/image_classification_training_notebook.md
- references/object_detection_training_notebook.md
- references/reliability_principles.md
- references/timm_trainer.md
- scripts/dataset_inspector.py
- scripts/estimate_cost.py
- scripts/image_classification_training.py
- scripts/object_detection_training.py
- scripts/sam_segmentation_training.py