Discover and install skills to enhance your AI agent's capabilities.
| Name | Contains | Score |
|---|---|---|
synthetic-sciences/openscience Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities. | Skills | — |
TanStack/ai LockStore, InMemoryLockStore, LocksCapability and withLocks for multi-instance coordination in TanStack AI. Ships in @tanstack/ai — NOT in @tanstack/ai-persistence. Separate from AIPersistence state stores — not a stores key, not composable. InMemoryLockStore vs a distributed (e.g. Cloudflare Durable Object) lock, lease recovery, AbortSignal in critical sections. Use when sandbox or other middleware needs cross-worker mutual exclusion — NOT for storing messages/runs (use withPersistence). | Skills | — |
TanStack/ai Server chat state with withPersistence from @tanstack/ai-persistence. Authoritative transcript, run lifecycle, durable interrupts/approvals, chatParamsFromRequest, reconstructChat, snapshotStreaming. Use when the server owns history, multi-device, or durable tool approvals. NOT client localStorage (see ai-core/client-persistence in @tanstack/ai) and NOT stream reconnect alone. | Skills | — |
TanStack/ai Durability and state persistence for TanStack AI chats with @tanstack/ai-persistence. Routes to server chat persistence (withPersistence), client persistence (localStorage/IndexedDB), the store contracts, and adapter recipes. Distinguishes delivery durability (resumable streams) from conversation state. Use when conversations must survive reloads, multi-device, approvals, or server restarts — NOT for stream reconnect alone. | Skills | — |
Azure/azure-rest-api-specs Conversational agent that guides developers through creating complete Azure PowerShell cmdlet design specifications. Walks through an interactive interview covering service release details, contacts, scenarios, cmdlet syntax, parameter sets, piping, test cases, and spec links. Validates against PowerShell design guidelines, pre-populates fields from TypeSpec, and files the design as a GitHub Issue in Azure/azure-powershell-cmdlet-review-pr. USE FOR: 'create PowerShell design', 'PS design review', 'cmdlet design', 'PowerShell cmdlet review', 'submit PS design'. DO NOT USE FOR: SDK generation, TypeSpec authoring, releasing packages. | Skills | — |
microsoft/agent-academy Turn a mission or lab idea into a fully researched GitHub issue spec on microsoft/agent-academy, then post it with the GitHub CLI. Use this skill whenever the user wants to propose new Agent Academy content before writing it — course missions (Recruit, Operative, Commander), standalone Special Ops, or Cowork Collective missions. Trigger whenever the user says "write a spec for a mission", "create an issue for a new lab", "I want to propose a Special Ops", "file a mission proposal", "spec out a lab", "open an issue for a new module", or hands over Microsoft Learn URLs and asks to turn them into an Agent Academy lab. This skill handles: mining source documentation, interviewing for scope, repo reconnaissance and duplicate detection across both docs and existing issues, frontmatter and tag validation, writing-style conformance, drafting the issue body, title conventions, milestone and assignee metadata, and posting plus verifying the issue via `gh`. | Skills | — |
MengTo/Skills Apply a prompt-agnostic execution and verification loop to any substantial task while preserving the original request. Use when the user asks to fan out work, use subagents or independent reviewers, loop until done, benchmark against references, apply a harsh critic, compare candidates blind, improve an existing prompt with verification, or continue until explicit quality gates pass. | Skills | — |
Hmbown/CodeWhale Route a "how do I use Codewhale" question to the installed help, config, and doctor surfaces instead of reciting a manual from memory. Explicit-only. | Skills | — |
Hmbown/CodeWhale Help a new contributor get productive on this checkout - inspect sync state against main, build, run the repository's exact verification gate, and produce a local what's-new digest. Never fetches, pulls, or modifies a dirty tree on its own. Explicit-only. | Skills | — |
zhxc372/cpp-ai-constitution Load when modernizing, migrating, or upgrading C++ code from older standards (C++98/03/11/14) to modern C++ (17/20/23), or when applying systematic code improvements that preserve behavior. | Skills | — |
zhxc372/cpp-ai-constitution Load when debugging crashes, memory errors, data races, undefined behavior, or performance issues in C++ code, or when performing a systematic safety audit. | Skills | — |
zhxc372/cpp-ai-constitution Load when reviewing, refactoring, modernizing, debugging, or designing non-trivial C++ code where ownership, lifetime, RAII, concurrency, templates, interfaces, exceptions, or Core Guidelines compliance may affect correctness, safety, maintainability, or performance. | Skills | — |
zhxc372/cpp-ai-constitution Load when reviewing, refactoring, modernizing, debugging, or designing non-trivial C++ code where ownership, lifetime, RAII, concurrency, templates, interfaces, exceptions, or Core Guidelines compliance may affect correctness, safety, maintainability, or performance. | Skills | — |
aws/agent-toolkit-for-aws Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore (including the Harness managed agent loop). Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, migrating/porting/converting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching setup and debugging, quota health checks and throttling diagnosis, cost attribution and tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. Also covers AgentCore Payments setup (x402, microtransactions, Payment Manager, Connector, Instrument, Coinbase CDP, Stripe Privy, 402 Payment Required, pay for content, paid endpoint, agent payments). NOT for custom model training, Rekognition, or Comprehend. | Skills | — |
aws/agent-toolkit-for-aws Deploys and operates containerized workloads on ECS, Fargate, and ECR. Covers task definitions, Fargate services, ECR repository setup and lifecycle policies, ECS Exec debugging, service scaling, deployment strategies, load balancer integration, and logging configuration. Use when deploying, debugging, or optimizing containers on AWS. ALSO USE for container deployment options (ECS vs ECS Express Mode), networking modes, health check troubleshooting, OOM errors, secrets injection, blue/green deployments, ECR image management, and App Runner sunset guidance and migration. NOT for Kubernetes, EKS, or CI/CD pipelines. | Skills | — |
aws/agent-toolkit-for-aws Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore. Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, migrating/porting/converting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching setup and debugging, quota health checks and throttling diagnosis, cost attribution and tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. Also covers AgentCore Payments setup (x402, microtransactions, Payment Manager, Connector, Instrument, Coinbase CDP, Stripe Privy, 402 Payment Required, pay for content, paid endpoint, agent payments). NOT for custom model training, Rekognition, or Comprehend. | Skills | — |
aws/agent-toolkit-for-aws Use when adding capabilities to an existing agent project — memory, app integration, VPC, multi-agent, migration, model changes, browser, code interpreter, or resource removal. Triggers on: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "auth to call agent", "streaming responses", "VPC", "VPC connectivity", "VPC error", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "after import", "migration issue", "framework for migration", "change model", "browser tool", "code interpreter", "delete agent", "tear down", "agentcore remove", "cross-account memory", "resource-based policy on memory", "pay for x402 content", "402 Payment Required", "microtransactions", "paid API or tool". Not for connecting to external APIs via Gateway — use agents-connect. Not for scaffolding a new project — use agents-get-started. Not for CLI/dev server errors — use agents-debug. Strands vs LangGraph in a migration context routes here. | Skills | — |
Project-N-E-K-O/N.E.K.O Dealing with delayed DOM generation, lazy loading, and optimistic state synchronization in vanilla JavaScript without a reactive framework. | Skills | — |
Project-N-E-K-O/N.E.K.O Project N.E.K.O. 胶囊化 UI、品牌蓝视觉系统规范 | Skills | — |
Project-N-E-K-O/N.E.K.O **重要提醒**: 每次完成复杂调试或开发任务后,主动执行此流程! 将学到的经验归档为 skill,供以后参考。不要等用户提醒。 | Skills | — |
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