Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 86 961 files from 2 125 authors, of which 68 678 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Build workflows with AWS Step Functions state machines using the JSONata query language. Covers Amazon States Language (ASL) structure, state types, variables, data transformation, error handling, AWS service integration, and migrating from the JSONPath to the JSONata query language.
Migrate, modernize, and upgrade codebases to AWS. Run analysis on repos for tech debt, security vulnerabilities, and modernization opportunities. Transforms .NET Framework to .NET 8/10, mainframe COBOL to Java, VMware VMs to EC2, SQL Server to Aurora, and upgrades Java/Python/Node.js versions and AWS SDKs. Use when the user says "migrate .NET to AWS", "upgrade Java to 17/21", "modernize COBOL", "modernize mainframe", "move VMware to EC2", "convert SQL Server to Aurora", "upgrade Python version", "migrate AWS SDK", "transform this codebase", "analyze for issues", "find tech debt", "what tech debt", "security vulnerabilities", "CVEs", "what's wrong with my code", "assess my repos", "where do I start", "find what's outdated", "analyze my repos", "AWS Transform - continuous modernization", "continuous modernization" or "continuous-modernization". Don't use for infrastructure provisioning, CI/CD pipelines, or general coding tasks.
This skill should be used when the user asks to \"analyze this codebase\", \"document this service\", \"generate technical docs\", \"I inherited this code\", \"help me understand this system\", \"create docs for this project\", \"what does this system look like\", \"onboard me to this codebase\", \"this codebase has no docs\", \"visualize the architecture from code\", or any explicit request to produce structured documentation or architecture diagrams from an existing codebase. Specifically optimized for AWS workloads (CDK, CloudFormation, Terraform) with source-of-truth citations. Do NOT activate for code reviews, single-function explanations, generating new code, or general coding tasks.
Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, FK replacement code generation, OCC retry patterns, ORM migration (Django/EF Core/Hibernate/Rails), DDL operations, query plan explainability, system diagnostics via CloudWatch AAS, SQL compatibility validation, and bulk data loading. Triggers on phrases like: DSQL, Aurora DSQL, distributed SQL database, serverless PostgreSQL-compatible database, migrate to DSQL, DSQL query plan, DSQL EXPLAIN ANALYZE, DSQL ENUM, DSQL foreign key, DSQL OCC retry, DSQL multi-region, DSQL JSONB, DSQL GIN index, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader, DSQL slow, DSQL performance, DSQL wait events, DSQL AAS.
Generate validated AWS architecture diagrams as draw.io XML using official AWS4 icon libraries. Use this skill whenever the user wants to create, generate, or design AWS architecture diagrams, cloud infrastructure diagrams, or system design visuals. Also triggers for requests to visualize existing infrastructure from CloudFormation, CDK, or Terraform code. Supports two modes: analyze an existing codebase to auto-generate diagrams, or brainstorm interactively from scratch. Exports .drawio files with optional PNG/SVG/PDF export via draw.io desktop CLI.
Deploy applications to AWS. Triggers on phrases like: deploy to AWS, host on AWS, run this on AWS, AWS architecture, estimate AWS cost, generate infrastructure. Analyzes any codebase and deploys to optimal AWS services.
Deploy to AWS Elastic Beanstalk. Triggers on: elastic beanstalk, EB, managed EC2 platform, web app with managed patching, worker on EC2, Heroku alternative, don't want to manage servers or container orchestration, migrate from Heroku, managed operational lifecycle. Covers Elastic Beanstalk on EC2 for web and worker applications.
Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR). Use when the user says "is my dataset okay", "evaluate my data", "check my training data", "I have my own data", or before starting any fine-tuning job. Detects file format, checks schema compliance against the selected model and technique, and reports whether the data is ready for training or evaluation.
Generates code that transforms datasets between ML schemas for model training or evaluation. Use when the user says "transform", "convert", "reformat", "change the format", or when a dataset's schema needs to change to match the target format — always use this skill for format changes rather than writing inline transformation code. Supports OpenAI chat, SageMaker SFT/DPO/RLVR/RLAIF, HuggingFace preference, Bedrock Nova, VERL, and custom JSONL formats from local files or S3.
Manages project directory setup and artifact organization. Use when starting a new project, resuming an existing one, or when a PLAN.md needs to be associated with a project directory. Creates the project folder structure (specs/, scripts/, notebooks/, manifests/, agent_memory/) and resolves project naming.
Selects a fine-tuning technique (SFT, DPO, RLVR, or RLAIF) for the user's use case and validates it against the selected model's available recipes. Use when the user has decided to finetune and needs to choose a technique, or when the technique needs to be validated against a model. Requires a base model to already be selected (via model-selection skill).
Generates code that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, RLVR, and RLAIF trainers, including RLVR Lambda reward function and RLAIF custom prompt creation.
Diagnose and remediate cluster-wide HyperPod (EKS or Slurm) problems — creation / deployment failures (CloudFormation, EFA health check, lifecycle scripts, capacity), EKS access, node replacement, CloudFormation nested-stack errors, post-maintenance rollback state, dangling nodes, autoscaler conflicts. Includes `--validate` pre-flight. Read-only.
Generate comprehensive issue reports from HyperPod clusters (EKS and Slurm) by collecting diagnostic logs and configurations for troubleshooting and AWS Support cases. Use when users need to collect diagnostics from HyperPod cluster nodes, generate issue reports for AWS Support, investigate node failures or performance problems, document cluster state, or create diagnostic snapshots. Triggers on requests involving issue reports, diagnostic collection, support case preparation, or cluster troubleshooting that requires gathering logs and system information from multiple nodes.
Diagnose NCCL failures and adjacent training-pod failures on HyperPod GPU clusters (EKS or Slurm) — training hangs, AllReduce / collective-op timeouts, EFA or libfabric errors, rendezvous failures, EFA TCP fallback, /dev/shm or memlock issues, NCCL version mismatch across pods, container OOM / exit-137 / OOMKilled, GPU OOM (CUDA out of memory), CrashLoopBackOff / Pending pods, MASTER_ADDR DNS, NetworkPolicy blocking. Not for single-node hardware faults (→ hyperpod-node-debugger § G) or cluster-creation EFA / SSM failures (→ hyperpod-cluster-debugger § A / § F).
Diagnose and remediate per-node issues on a HyperPod cluster (EKS or Slurm) — a specific node is unhealthy, unresponsive, stuck, or needs replacing. Covers on-node EFA, GPU / accelerator hardware (XID, ECC, NVLink, row-remap, DCGM), Slurm node down/drained, disk and memory pressure, per-node lifecycle-script failures, SSM agent, container runtime, kernel panics, pod networking. Read-only. Not for cluster-wide provisioning (→ hyperpod-cluster-debugger), NCCL (→ hyperpod-nccl), or MFU (→ hyperpod-mfu-debugger).
Diagnose performance issues on Amazon SageMaker HyperPod clusters — uneven NCCL bandwidth across nodes and poor filesystem throughput. Read-only. Surfaces host-side signals (Xid, ECC, NVLink, EFA reachability, FSx saturation) and routes to the appropriate sibling skill (hyperpod-node-debugger, hyperpod-nccl, hyperpod-version-checker, hyperpod-issue-report) for any remediation. Triggers on uneven NCCL across nodes, straggler node, FSx slow, checkpoint slow, dataloader slow, filesystem bottleneck, FSx throughput, cross-AZ latency, topology mismatch.
Diagnostic-only skill for Slurm scheduler and node-daemon issues on Amazon SageMaker HyperPod Slurm clusters. Scope mirrors the HyperPod troubleshooting guide. Invoke when the user reports a Slurm node stuck in down/drain, "Node unexpectedly rebooted" after auto-repair, slurmd not running, jobs stuck PENDING with REASON=Resources while sinfo shows idle nodes, jobs stuck COMPLETING after node replacement, GRES/GPU counts wrong, scontrol ping failing, slurmctld unresponsive, an Action:Reboot/Replace request that did not trigger HyperPod auto-recovery, or auto-resume not restarting a job. Also triggers on "drain before reboot", "diagnose a Slurm node", "investigate stuck jobs.
Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM). This is the primary interface for accessing HyperPod nodes — direct SSH is not available. Use when any skill, workflow, or user request needs to execute commands on cluster nodes, upload files to nodes, read/download files from nodes, run diagnostics, install packages, or perform any operation requiring shell access to HyperPod instances. Other HyperPod skills depend on this skill for all node-level operations.
Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches across nodes, planning upgrades, documenting cluster configuration, or troubleshooting version-related issues on HyperPod. Triggers on requests about versions, compatibility, component checks, or upgrade planning for HyperPod clusters.
Generates code that deploys fine-tuned models from SageMaker Serverless Model Customization to SageMaker endpoints or Bedrock. Use when the user says "deploy my model", "create an endpoint", "make it available", or asks about deployment options. Identifies the correct deployment pathway (Nova vs OSS), generates deployment code, and handles endpoint configuration.
Generates python code that evaluates SageMaker models. Supports two evaluation types: LLM-as-Judge and Custom Scorer. Use when the user says "evaluate my model", "run a benchmark", "test model performance", "how did my model perform", "compare models", or other similar requests.
Selects a base model for the user's use case by querying SageMaker Hub. Use when the user asks which model to use, wants to select or change their base model, mentions a model name or family (e.g., "Llama", "Mistral", "Nova"), or wants to evaluate a base model — always activate even for known model names because the exact Hub model ID must be resolved. Queries available models, presents benchmarks and licenses, and confirms selection.
Discovers user intent and generates a structured, step-by-step plan for model customization workflows. This skill must always be activated alongside any other skill when the user's request relates to model customization — including fine-tuning, training, building, customizing, reviewing data, or getting advice on approach, regardless of domain. Do not skip this skill even if the immediate ask is narrow (e.g., reviewing data format or a single workflow step), because planning discovers the full scope of work needed. Also activate when the user wants to resume, continue, or modify an existing plan.
Validates the user's environment for SageMaker AI operations — checks SDK version, AWS region, and execution role. Use when the user says "set up", "getting started", "check my environment", "configure SDK", or as the first step in any plan involving SageMaker/Bedrock training, evaluation, or deployment.
Creates a reusable use case specification file that defines the business problem, stakeholders, and measurable success criteria for model customization, as recommended by the AWS Responsible AI Lens. Use as the default first step in any model customization plan. Skip only if the user explicitly declines or already has a use case specification to reuse. Captures problem statement, primary users, and LLM-as-a-Judge success tenets.
Make or edit animated, narrated, interactive web books from reference PDFs, and animated picture books (paper-puppet films) from a story, a joke or a fairy tale. Use for book planning, storyboards, chapter animation and exercises, narration, and cover and contents pages, including "make the next chapter", "turn this story into a picture book" or "fix this animation". Deliver runnable static book files; bookshelf design, bookshelf registration and hosting are separate tasks.
Use when generating sexy/NSFW or posed images with local Qwen-Image 2.1 — pose/NSFW LoRAs (tawsLoRa femaledVaginus, TheseAlpacas, posture-v3), pose transfer from an existing image, or exact pose control via VNCCS PoseStudio 3D pose library. Triggers: 性感姿势, 摆姿势, NSFW 出图, 换姿势, 姿势控制, pose transfer, pose lora, VNCCS, 人偶姿势, 姿势库. Independent of any general image-generation skill (which handles SFW text/edit/cutout work).
Use when creating, improving, finding, or auditing agent skills - the user says 'create a skill', 'do I have a skill for X', 'improve the X skill', 'which skill should I use', asks whether a skill exists for a task, or wants to validate, test, evaluate, package, or health-check skills. Also use for skill ecosystem maintenance (duplicate detection, stale skills, trigger collisions) and advisor checkpoints.
Analyzes, generates, and enhances CLAUDE.md files for any project type using best practices, modular architecture support, and tech stack customization. Use when setting up new projects, improving existing CLAUDE.md files, or establishing AI-assisted development standards.
Bridge between Claude Code and OpenAI Codex CLI - generates AGENTS.md from CLAUDE.md, provides Codex CLI execution helpers, and enables seamless interoperability between both tools
Generate production-ready Claude Code hooks with interactive Q&A, automated installation, and enhanced validation. Supports 10 templates across 7 event types for comprehensive workflow automation.
World-class prompt powerhouse that generates production-ready mega-prompts for any role, industry, and task through intelligent 7-question flow, 69 comprehensive presets across 15 professional domains (technical, business, creative, legal, finance, HR, design, customer, executive, manufacturing, R&D, regulatory, specialized-technical, research, creative-media), multiple output formats (XML/Claude/ChatGPT/Gemini), quality validation gates, and contextual best practices from OpenAI/Anthropic/Google. Supports both core and advanced modes with testing scenarios and prompt variations.
Comprehensive Scrum Master assistant for sprint planning, backlog grooming, retrospectives, capacity planning, and daily standups with intelligent context-aware reporting
Generate custom Claude Code slash commands through intelligent 5-7 question flow. Creates powerful commands for business research, content analysis, healthcare compliance, API integration, documentation automation, and workflow optimization. Outputs organized commands to generated-commands/ with validation and installation guidance.
Score a repository's agentic legibility from repo-visible evidence only. Use when Codex needs to audit how easy a codebase is for coding agents to discover, bootstrap, validate, and navigate, especially for harness-engineering reviews, developer-experience audits, repo cleanup, or before/after comparisons after improving docs, tooling, or architectural constraints.
When the user wants to analyze Google Search Console data, use the GSC API, or interpret search performance. Also use when the user mentions "GSC," "Search Console," "indexing report," "Core Web Vitals," "Enhancements," "Insights report," "search performance," "search queries," "search performance report," "URL inspection," "impressions," "CTR," "average position," "index coverage," "GSC data analysis," "Search Console API," or "searchanalytics.query." When the user wants to rewrite title tags (not only report on them), use title-tag. For meta description rewrites, use meta-description.
When the user wants to build an SEO data analysis system, monitor indexing/traffic/keywords/backlinks, or set up benchmarks. Also use when the user mentions "SEO data analysis," "SEO monitoring," "article database," "traffic benchmark," "penalty recovery," "SEO work document," "SEO dashboard," "keyword tracking," "ranking monitoring," "indexing report," or "backlink monitoring." For GSC API, use google-search-console.
When the user wants to track AI search traffic in GA4 or GSC. Also use when the user mentions "AI traffic," "ChatGPT referral," "Perplexity traffic," "AI Overviews," "GA4 AI sources," "AI search analytics," "track AI referrals," "AI search traffic," "Claude traffic," or "how to track AI traffic." For AI SEO strategy, use generative-engine-optimization.
When the user wants to analyze website traffic sources, attribution, or dark traffic. Also use when the user mentions "traffic sources," "dark traffic," "direct traffic," "UTM parameters," "traffic attribution," "channel attribution," "attribution optimization," "channel analysis," "traffic analysis," "traffic diversification," "natural traffic benchmark," or "organic vs paid traffic." For GA4 setup, use analytics-tracking.
When the user wants to set up, audit, or optimize analytics tracking (GA4, events, conversions). Also use when the user mentions "Google Analytics," "GA4," "event tracking," "conversions," "attribution model," "gtag," "data layer," "GA4 setup," "conversion tracking," "event setup," "User ID tracking," or "CTA attribution." For traffic insights, use traffic-analysis.
When the user wants to promote via forums, communities, or invite users to join a community. Also use when the user mentions "forum promotion," "Indie Hacker," "Hacker News," "community growth," "Discord promotion," "vertical community," "brand encyclopedia," "Wikipedia," "Quora," "Reddit community," "community building," "forum marketing," or "community invite." For Reddit copy, use reddit-posts. For strategy, use integrated-marketing.
When the user wants to submit a product or app to directories, curated lists, launch platforms, or app stores—and needs ready-to-paste copy per platform. Reads project-context.md when present. Also use when the user mentions "directory submission," "get listed," "app store listing," "submit to directories," "curated list," "best tools list," "Taaft," "Product Hunt," "directory ads," "newsletter feature," "directory campaign," "tailor description per platform," "Shopify App Store," "Chrome Web Store," "navigation site," or "product directory." For Product Hunt launch day tactics (hunter, first comment, timing), use product-hunt-launch. For full 0→1 channel planning, use cold-start-strategy.
When the user wants to launch on Product Hunt, prepare a PH submission, or plan launch day (hunter, first comment, timing, upvotes). Also use when the user mentions "Product Hunt," "launch on Product Hunt," "PH launch," "Product Hunt submission," "hunter," "Product of the Day," "upvotes," or "Product Hunt first comment." For multi-platform directory listings and paste-ready copy beyond PH, use directory-submission.
When the user wants to plan product distribution via marketplaces, app stores, or third-party platforms. Also use when the user mentions "distribution channels," "marketplace listing," "app store listing," "Figma plugin," "Chrome extension marketplace," "AWS Marketplace," "Shopify app," "GPTs store," "app distribution," or "third-party marketplace." For channel mix, use integrated-marketing.
When the user wants to plan email marketing, EDM, newsletter strategy, or email deliverability. Also use when the user mentions "email marketing," "EDM," "newsletter," "SPF," "DKIM," "DMARC," "email deliverability," "email content strategy," "email campaigns," "newsletter strategy," "email automation," or "cold email." For signup UI, use newsletter-signup-generator.
When the user wants to plan, implement, or optimize employee-generated content (EGC) or employee advocacy. Also use when the user mentions "EGC," "employee advocacy," "employee content," "internal brand ambassadors," "employee social media," "employee advocacy program," "staff advocacy," "LinkedIn employee posts," or "brand ambassador program." For LinkedIn, use linkedin-posts.
When the user wants to plan, implement, or optimize affiliate marketing strategy. Also use when the user mentions "affiliate marketing," "affiliate program strategy," "CPS model," "affiliate recruitment," "commission structure," "affiliate partners," "affiliate network," "affiliate tracking," "affiliate commission," or "partner marketing." For affiliate page, use affiliate-page-generator.
When the user wants to plan, implement, or optimize creator program strategy. Also use when the user mentions "creator program," "creator partnership," "content co-creation," "creator ambassador," "creator economy," "creator collaboration," "UGC program," "creator incentives," or "creator community." For influencers, use influencer-marketing.
When the user wants to plan, implement, or optimize student and education discount programs. Also use when the user mentions "student discount," "education discount," "student plan," "for students," ".edu discount," "academic pricing," "student verification," "SheerID," "UNiDAYS," or "education program." For startup pricing page, use startups-page-generator.
When the user wants to plan, implement, or optimize influencer marketing strategy. Also use when the user mentions "influencer marketing," "KOL," "creator partnership," "brand ambassador," "sponsored content," "influencer campaign," "micro-influencer," "influencer outreach," "creator collaboration," or "influencer deal." For creator programs, use creator-program.
When the user wants to plan PR, write a press release, or manage media relations. Also use when the user mentions "public relations," "PR," "press release," "media relations," "news release," "journalist," "media coverage," "product announcement," or "earned media." For on-site "As Seen In" or logos page, use press-coverage-page-generator.
When the user wants to plan, implement, or optimize referral program strategy. Also use when the user mentions "referral program," "referral marketing," "user referral," "refer-a-friend," "word-of-mouth growth," "referral rewards," "referral tracking," "referral code," "referral incentives," or "viral loop." For referral landing copy, use landing-page-generator.
When the user wants to define, audit, or apply visual identity (typography, colors, spacing, design tokens, frontend aesthetics). Also use when the user mentions "brand style guide," "visual identity," "design system," "typography," "color palette," "brand guidelines," "AI brand aesthetics," "brand colors," "font choices," "spacing system," "design tokens," "motion," "distinctive design," "frontend aesthetics," "PowerPoint theme," "Google Slides brand," or "slide master colors." For brand story, positioning, and voice, use branding.
When the user wants to implement, optimize, or audit favicon and app icons. Also use when the user mentions "favicon," "app icon," "browser icon," "touch icon," "PWA icon," "favicon sizes," "apple-touch-icon," "favicon.ico," "site icon," or "tab icon." For visual system, use brand-visual-generator.
When the user wants to design, optimize, or audit hero sections (above-the-fold main visual area). Also use when the user mentions "hero," "hero section," "hero area," "above the fold," "above the fold content," "landing hero," "main banner," "banner section," "first fold," "hero section design," "hero conversion," "split layout hero," "centered hero," or "hero alignment." For homepage, use homepage-generator.
When the user wants to optimize logo placement, linking, or branding on a website. Also use when the user mentions "logo," "brand logo," "header logo," "logo placement," "AI logo design," "logo link," "logo alt text," "logo sizing," "favicon logo," or "logo usage." For full brand visuals, use brand-visual-generator.
When the user wants to create, optimize, or audit a comparison table section—an in-page block (HTML table or responsive equivalent) comparing products, methods, or approaches, with optional supporting copy. Also use when the user mentions "comparison table," "compare table," "feature matrix," "vs table," "side-by-side comparison," "competitor comparison," "traditional vs modern," "manual vs automated," "before and after," "old way vs new way," "alternatives comparison block," or "comparison section on landing page or blog." This skill is for a section inside a page, not a full alternatives URL or blog post wireframe—use alternatives-page-generator for page-level layout, keywords, and PPC destination strategy. For full-page structured data rules, use schema-markup. For FAQ blocks paired with the table, use faq-page-generator.
When the user wants to create, optimize, or audit a HowTo section block—an in-page block of ordered steps with optional Schema.org HowTo JSON-LD. Also use when the user mentions "HowTo section," "how-to section," "steps section," "quick start," "walkthrough," "tutorial block," "3 steps," "N steps," "simple steps," "tutorial steps," "step-by-step block," "HowTo schema," "HowTo JSON-LD," "instruction steps," "numbered steps SEO," "horizontal tabs for steps," or "procedure section." This skill is for a section inside a page, not a full page template—use article-page-generator, docs-page-generator, or tools-page-generator for page-level layout. For FAQ Q&A blocks, use faq-page-generator. For structured data details beyond HowTo, use schema-markup. For article body copy only, use article-content.
Claude Skills — questions
Answers built from the skills we actually parsed.