effect-tsComprehensive Effect-TS development guide for TypeScript, focused on Effect v4 (the recommended default) with full v3 (stable) support for existing codebases...
Install via ClawdBot CLI:
clawdbot install tenequm/effect-tsGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
post → https://api.example.com/usersCalls external URL not in known-safe list
https://effect.website/docsAI Analysis
The skill definition is a pure documentation and coding guide for the Effect-TS library. The 'external endpoints' flagged are official documentation URLs (effect.website) and a placeholder example URL (api.example.com) used in illustrative code snippets, not actual data exfiltration targets. There are no instructions to send user data, override safety, harvest credentials, or obfuscate behavior.
Audited Apr 17, 2026 · audit v1.0
Generated May 9, 2026
Use Effect-TS to model financial transactions where errors like insufficient funds or account not found are typed and handled at compile time. Services can be built with retry policies for transient failures, ensuring reliability in payment processing, fund transfers, and fraud detection systems.
Build a real-time analytics pipeline using Effect Streams to process high-throughput data from IoT devices or user interactions. Structured concurrency via fibers allows parallel processing with backpressure, while retry/scheduling handles connection drops and transient errors.
Leverage Effect's ServiceMap/Context + Layers to create a multi-tenant SaaS backend where each tenant has its own database connection, configuration, and rate limits. Dependency injection makes testing easy by swapping live services with mocks.
Integrate Effect AI with OpenTelemetry to build a chatbot that calls LLMs, tracks latency and token usage, and handles errors gracefully. Use Schema validation for structured inputs/outputs and retry for API rate limits.
Offer a managed API for payment processing or data transformation built with Effect-TS. Typed errors reduce customer integration friction, and built-in observability provides usage analytics.
Provide a multi-tenant SaaS product where each tenant's resources are isolated using Effect's DI system. This model supports custom configurations per tenant without code duplication.
Sell a middleware service that standardizes LLM calls across providers (OpenAI, Anthropic, etc.) using Effect AI. It adds Schema validation, retries, and cost tracking, reducing developer overhead.
💬 Integration Tip
Start by modeling your core business logic with typed errors using Effect, then layer in dependency injection for testability. Use the provided AI guardrails to avoid common API mistakes, especially when mixing v3 and v4 patterns.
Scored Jul 7, 2026
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