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.
49,418 skills from 2,407 repositories · updated 7 minutes ago
49,416 skills
- build-flowmicrosoft/power-platform-skillsAutonomously build a complete Power Automate flow from a description. Use when you need to generate a full flow definition and create it. Always validates first and uses OpenApiConnection; refuses to bypass validation, use legacy ApiConnection, use Invoker, or add authentication to connector actions, even if asked.OtherNo warnings★ 1.1K↓ —
- rag-architectalirezarezvani/claude-skillsDesign a RAG pipeline: chunk size, embedding model, vector database and retrieval quality metrics. Use whenever the user builds search over their docs, picks a vector store or finds answers miss the right context.PlanningNo warnings★ 29.3K↓ —
- designing-testsCloudAI-X/claude-workflow-v2Designs and implements testing strategies for any codebase. Use when adding tests, improving coverage, setting up testing infrastructure, debugging test failures, or when asked about unit tests, integration tests, or E2E testing.TestingNo warnings★ 1.4K↓ —
- research-competitors-category-passgooseworks-ai/goose-skillsStep of the research-competitors playbook: the worker brief covering the whole category, including searches, AI answers, community threads and category ad winners. Run research-competitors instead; not for direct use.ScienceNo warnings★ 1.3K↓ —
- research-audience-account-sourcinggooseworks-ai/goose-skillsStep of the research-audience playbook: finds candidate accounts matching the fit definition, confirms gates, applies exclusions and dedupes. Run research-audience instead; not for direct use.ScienceNo warnings★ 1.3K↓ —
- 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.OfficialProductivityNo warnings★ 11.3K↓ —
- 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.OfficialScienceNo warnings★ 11.3K↓ —
- analyze-performance-call-and-learngooseworks-ai/goose-skillsStep of the analyze-performance playbook: calls ended tests, scores last week's calls, writes this week's kill/scale/hold calls and drafts learnings for the brand brain. Run analyze-performance instead; not for direct use.TestingNo warnings★ 1.3K↓ —
- analyze-performance-rank-and-readgooseworks-ai/goose-skillsStep of the analyze-performance playbook: ranks creative by angle, hook and format with spend gates, writes short per-channel reads and drafts what to make next. Run analyze-performance instead; not for direct use.WritingNo warnings★ 1.3K↓ —
- archivehashgraph-online/awesome-codex-pluginsUse at ship time to merge the spec into the living documentation, delete the staging spec and plan, and ask how to finish.PlanningNo warnings★ 1.5K↓ —
- interviewalirezarezvani/claude-skillsUse when someone has an agent idea to scope before launch ('help me scope an agent'). Interviews them about the one job and writes a build sheet with build_sheet_builder.py, checked by primitives_validator.py; no API key needed.PlanningNo warnings★ 29.3K↓ —
- 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.OfficialOtherNo warnings★ 11.3K↓ —
- 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.OfficialMediaNo warnings★ 11.3K↓ —
- data-warehouse-experimentationrampstackco/claude-skillsRunning experiments out of the data warehouse instead of via dedicated experiment platforms. SQL-based assignment, exposure logging discipline, metric definitions in dbt models, statistical analysis in SQL or Python, variance reduction with CUPED, sequential testing, and the operational tradeoffs vs platforms like Statsig and Optimizely. Triggers on warehouse-native experimentation, run experiments in BigQuery, run experiments in Snowflake, dbt experiments, SQL t-test, CUPED variance reduction, exposure log, sample ratio mismatch, sequential testing, mSPRT, doubly robust estimation, build vs buy experimentation. Also triggers when the team is choosing between platform and warehouse, building warehouse-native experiment infrastructure, auditing one, or running an experiment with a custom metric the platform cannot handle.TestingNo warnings★ 1K↓ —
- designing-apisCloudAI-X/claude-workflow-v2Designs REST and GraphQL APIs including endpoints, error handling, versioning, and documentation. Use when creating new APIs, designing endpoints, reviewing API contracts, or when asked about REST, GraphQL, or API patterns.EngineeringNo warnings★ 1.4K↓ —
- access-lifecyclealirezarezvani/claude-skillsUse when preparing or running a user access review, checking that leavers lost their access, finding orphaned or ownerless service accounts, answering an auditor's access-control request for SOC 2, ISO 27001, PCI DSS, HIPAA or NIST 800-53, or checking whether a finished review campaign will hold up. Diffs the HR roster against account exports, tests the campaign for coverage, self-review, unremoved revokes and rubber-stamping, and maps every exception to the controls it breaks.TestingNo warnings★ 29.3K↓ —
- feature-dochuytieu/COG-second-brainSelf-evolving second brain with 35 AI skills, 10 agents, and people CRM. Closed-loop harness: a V-model verification lifecycle where the worker never grades its own homework. Plus paired anti-slop design skills for marketing and product UI. Works with Claude Code, Cursor, Kiro, Gemini CLI, Codex.DesignNo warnings★ 1.3K↓ —
- 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.OfficialEngineeringNo warnings★ 11.3K↓ —
- folded-desc-skillfirst-fluke/oh-my-agentA fixture whose description uses a YAML folded scalar, which parses with an embedded trailing newline unless normalized before use in Markdown tables.OtherNo warnings★ 1.4K↓ —
- run-paid-campaigns-apply-and-loggooseworks-ai/goose-skillsStep of the run-paid-campaigns playbook: stages the week's approval items, applies only what the marketer approves and keeps the change log. Run run-paid-campaigns instead; not for direct use.OtherNo warnings★ 1.3K↓ —
- nopua-litewuji-labs/nopuaNoPUA Lite — core wisdom in ~1.5k tokens. Drives AI with trust and inner motivation instead of fear. Same Daoist philosophy, minimal footprint. For personal use and small-context models.ProductivityNo warnings★ 1.4K↓ —
- research-marketgooseworks-ai/goose-skillsMarket research and brand watch: which market the brand is in, how big the reachable part is, what's changing, how buyers buy and what they pay, what people are saying now, and what it means for positioning. Use when the marketer asks for market research, "how big is my market", "what's changing in my category", "what do others charge", "what are people saying about us", "is there demand for <idea>", or "watch my brand / tell me if something blows up" (alerts only, risk first). Also writes positioning choices and finished messages ("position my product", "write our positioning"). Researches first, asks only decisions at the end, and saves the output to the brand. Not for who the buyers are and their own words — use research-audience; not for a deep look at rivals — use research-competitors.ScienceNo warnings★ 1.3K↓ —
- research-audience-fit-definitiongooseworks-ai/goose-skillsStep of the research-audience playbook: drafts the searchable fit definition, exclusions and list size that the list run then searches on. Run research-audience instead; not for direct use.ScienceNo warnings★ 1.3K↓ —
- analyze-performance-revenue-joingooseworks-ai/goose-skillsStep of the analyze-performance playbook: joins cleaned store or CRM numbers with ad spend to build the business-truth table, MER, new-customer cost and the overclaim ratio. Run analyze-performance instead; not for direct use.MarketingNo warnings★ 1.3K↓ —
scheduler-and-booking-design
rampstackco/claude-skills
DesignUpdated Oct 27, 2026
From the author
Designing meeting schedulers and booking experiences that qualify leads, set up calls well, and convert at higher rates than a generic Calendly link. Availability logic, qualification gating, prep automation, follow-up sequencing. Honest about any-time-friction (no qualification, just a booking link), interrogation-gate (so much qualification it scares users off), and qualified-fast-path (just enough qualification to set up the call well) patterns. Triggers on scheduler design, meeting booking, demo scheduling, sales call scheduling, calendar tool, booking page, qualification flow. Also triggers when sales team complains about cold demos, when booking conversion is poor, or when scheduler is being scoped for the first time.
Install
npx skills add rampstackco/claude-skills --skill scheduler-and-booking-design -a claude-code
Installs to .claude/skills/scheduler-and-booking-design/ · 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
Instructions onlyNo network use seenLicence: MIT
Safety checks on SKILL.md
No warnings.
Why 88
Security100
Provenance76
Maintenance100
Licence100
Adoption49
Files (11)
- README.md
- SKILL.md
- references/availability-logic-patterns.md
- references/common-scheduler-failures.md
- references/prep-automation-patterns.md
- references/qualification-field-design.md
- references/reminder-sequence-patterns.md
- references/reschedule-and-no-show-handling.md
- references/routing-patterns.md
- references/scheduler-anti-patterns.md
- references/scheduler-decision-criteria.md