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Found 10,461 Skills
Query and retrieve protein/nucleic acid structures from RCSB PDB. Use when you need to search the PDB database for structures or metadata. Supports text, sequence, and structure-based searches, coordinate downloads, and metadata retrieval for structural biology workflows.
INVOKE THIS SKILL when adding Arize AX tracing to an application. Follow the Agent-Assisted Tracing two-phase flow: analyze the codebase (read-only), then implement instrumentation after user confirmation. When the app uses LLM tool/function calling, add manual CHAIN + TOOL spans so traces show each tool's input and output. Leverages https://arize.com/docs/ax/alyx/tracing-assistant and https://arize.com/docs/PROMPT.md.
Assist developers in writing clean, maintainable code following software engineering best practices. Use when conducting code reviews, refactoring code, enforcing coding standards, seeking guidance on clean code principles, or integrating automated quality checks into development workflows.
Build and optimize sales funnels — strategy, structure, conversion optimization, A/B testing, and analytics. Use when building a funnel, optimizing conversion rates, designing upsell/downsell flows, choosing a funnel builder, or planning a launch funnel. Do NOT use for email marketing sequences (use /sales-email-marketing), checkout-specific optimization (use /sales-checkout), or webinar funnels (use /sales-webinar). For Groove-specific help, use /sales-groove.
Track CJ대한통운 and 우체국 parcels by invoice number with official carrier endpoints, and structure the workflow around a carrier adapter that can grow to more couriers later.
Authentication bypass testing playbook. Use when assessing login flows, password reset logic, account recovery, MFA bypass, token predictability, brute-force resistance, and session boundary flaws.
JWT and OAuth token attack playbook. Use when validating token trust, signing algorithms, key handling, claim abuse, bearer flows, and OAuth account-binding weaknesses.
Hydrogen storefront implementation cookbooks. Some of the available recipes are: B2B Commerce, Bundles, Combined Listings, Custom Cart Method, Dynamic Content with Metaobjects, Express Server, Google Tag Manager Integration, Infinite Scroll, Legacy Customer Account Flow, Markets, Partytown + Google Tag Manager, Subscriptions, Third-party API Queries and Caching. MANDATORY: Use this API for ANY Hydrogen storefront question - do NOT use Storefront GraphQL when 'Hydrogen' is mentioned.
Reference skill for Zoom Team Chat. Use after routing to a chat workflow when building user-scoped messaging integrations, chatbot experiences, rich cards, buttons, slash commands, or chat webhooks.
Executes full-project QA like a real user by discovering the repository verification and E2E contracts, running build, lint, test, and startup commands, exercising core workflows end-to-end through CLI, HTTP, and browser interfaces, requiring automated regression coverage for supported critical flows, fixing root-cause regressions, and rerunning the full gate. Uses the agent-browser companion skill for Web UI validation when a web surface exists. Use when validating a branch, release candidate, migration, refactor, or risky commit. Do not use for static code review only, one-off unit test edits, planning test cases, or architecture brainstorming without execution — use qa-report for planning and documentation.
Emulated Microsoft Entra ID (Azure AD) OAuth 2.0 / OpenID Connect for local development and testing. Use when the user needs to test Microsoft sign-in locally, emulate Entra ID OIDC discovery, handle Microsoft token exchange, configure Azure AD OAuth clients, work with Microsoft Graph /me, or test PKCE/client credentials flows without hitting real Microsoft APIs. Triggers include "Microsoft OAuth", "Entra ID", "Azure AD", "emulate Microsoft", "mock Microsoft login", "test Microsoft sign-in", "Microsoft OIDC", "local Microsoft auth", or any task requiring a local Microsoft OAuth/OIDC provider.
Pre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.