Loading...
Loading...
Found 532 Skills
Guide for adding new AI provider packages to the AI SDK. Use when creating a new @ai-sdk/<provider> package to integrate an AI service into the SDK.
Implement dependency injection in Angular v20+ using inject(), injection tokens, and provider configuration. Use for service architecture, providing dependencies at different levels, creating injectable tokens, and managing singleton vs scoped services. Triggers on service creation, configuring providers, using injection tokens, or understanding DI hierarchy.
Provisions and manages Neo4j Aura instances via CLI (aura-cli v1.7+) or REST API. Use when creating, pausing, resuming, resizing, or deleting AuraDB Free/Professional/Business Critical/VDC instances; downloading credentials; scripting CI/CD pipelines; polling async status; or using the Terraform neo4j/neo4j-aura provider. Covers auth setup (client credentials OAuth2), credential lifecycle (download once — never recoverable), instance type selection, region codes, and Python provisioning scripts. Does NOT handle Cypher queries — use neo4j-cypher-skill. Does NOT cover Graph Data Science algorithms — use neo4j-gds-skill or neo4j-aura-graph-analytics-skill. Does NOT cover neo4j-admin/cypher-shell — use neo4j-cli-tools-skill.
Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, or tools, (2) Want to build AI agents, chatbots, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, etc.), streaming, tool calling, or structured output.
Updates the "Prowler at a Glance" table in README.md with accurate provider statistics. Trigger: When updating README.md provider stats, checks count, services count, compliance frameworks, or categories.
Migrate Exa, Tavily, Perplexity, or Firecrawl web-data integrations completely to the appropriate Parallel products while preserving application behavior. Use when replacing these providers' SDKs or REST calls, dependencies, environment variables, request parameters, response parsing, model tools, search-plus-scrape paths, full-content or answer-synthesis paths, tests, and documentation; separating unsupported research-index, crawl, browser, file-parse, monitor, or other non-search capabilities; auditing for leftover provider usage; or finishing and verifying an in-progress provider migration.
Develop examples for AI SDK functions. Use when creating, running, or modifying examples under examples/ai-functions/src to validate provider support, demonstrate features, or create test fixtures.
Terraform provider acceptance test patterns using terraform-plugin-testing with the Plugin Framework. Covers test structure, TestCase/TestStep fields, ConfigStateChecks with custom statecheck.StateCheck implementations, plan checks, CompareValue for cross-step assertions, config helpers, import testing with ImportStateKind, sweepers, and scenario patterns (basic, update, disappears, validation, regression), and ephemeral resource testing with the echoprovider package. Use when writing, reviewing, or debugging provider acceptance tests, including questions about statecheck, plancheck, TestCheckFunc, CheckDestroy, ExpectError, import state verification, ephemeral resources, or how to structure test files.
Build a new API connector or provider by matching the target repo's existing integration pattern exactly. Use when adding one more integration without inventing a second architecture.
Use when generating a Terraform provider from an OpenAPI spec with Speakeasy. Covers entity annotations, CRUD mapping, type inference, workflow configuration, and publishing. Triggers on "terraform provider", "generate terraform", "create terraform provider", "CRUD mapping", "x-speakeasy-entity", "terraform resource", "terraform registry".
Configure LLM models and providers for Letta agents and servers. Use when setting model handles, adjusting temperature/tokens, configuring provider-specific settings, setting up BYOK providers, or configuring self-hosted deployments with environment variables.
Debugs and fixes Terraform errors systematically. Use when encountering Terraform failures, state lock issues, provider errors, syntax problems, or unexpected infrastructure changes. Includes debugging workflows, error categorization, common GCP-specific issues, and recovery procedures.