Skill UI

A comprehensive guide to production-ready patterns for integrating with Adobe services (Firefly, PDF, etc.). This includes robust authentication with token caching, typed API wrappers with advanced error classification, exponential backoff retry mechanisms, and job polling for asynchronous tasks. Essential for building reliable and maintainable Adobe API integrations in TypeScript or Python.

A comprehensive guide to production-ready patterns for Web3 development using the Alchemy SDK. Covers essential architectural components such as multi-chain client factories, response caching mechanisms, type-safe NFT query builders, and robust error classification, ensuring highly scalable and reliable blockchain applications.

A comprehensive guide for rapid incident response when Algolia search functionality fails. This runbook provides structured procedures for triage, differentiating between infrastructure outages and internal configuration errors (e.g., API keys, indexing failures). It includes severity classification, diagnosis steps, and code examples for immediate remediation, such as key rotation or implementing circuit breakers.

This internal agent skill processes raw X/Twitter posts into structured bug candidates. It systematically performs parsing, content deduplication, PII redaction, reliability scoring, and classification. Finally, it clusters related reports using deterministic signatures, providing a highly organized output for efficient bug triage and analysis from large-scale social media streams.

Implements robust data governance for Canva Connect API interactions. This skill covers data classification (PII, Secrets, Business), token redaction, temporary URL expiry, and enforces strict data retention policies. It is essential for developers building integrations that must adhere to global privacy standards like GDPR and CCPA, ensuring secure data handling from ingestion to deletion.

A comprehensive guide to production-ready patterns for ElevenLabs' TypeScript and Python SDKs. This resource covers crucial best practices including singleton client implementation, type-safe TTS service wrappers, robust error classification (rate limiting, quota), and concurrency management using request queues. Essential for building scalable and reliable voice AI applications.

A comprehensive runbook for responding to critical incidents involving Flexport API integrations. It covers various failure scenarios, including complete API outages, webhook delivery loss, and complex supply chain data synchronization issues. The guide provides severity classification (P1-P4), diagnostic commands, and step-by-step playbooks for rapid triage and mitigation.

This specialized skill reviews contracts from a freelancer's perspective. It evaluates agreements using 14 detailed lenses—covering misclassification risk, IP ownership, payment terms, and non-compete clauses—to flag structural imbalances that often favor the client. It helps independent contractors understand potential legal and financial risks within client agreements.

This comprehensive runbook provides structured procedures for diagnosing and responding to critical failures when integrating with the Grammarly API. It covers various incident types, including full API outages, OAuth token expiration, rate limit storms, and suggestion quality degradation. The guide includes severity classification, diagnostic `curl` commands, detailed playbooks, and post-incident documentation steps to ensure service resilience and minimal downtime.

This collection provides production-ready, idiomatic patterns for the @hubspot/api-client SDK, specifically tailored for TypeScript. It addresses critical development concerns including creating typed wrappers, implementing robust, structured error classification (handling rate limits, authentication issues, etc.), and managing efficient batch operations (create, read, upsert) for HubSpot CRM data. Use this when building scalable, reliable, and maintainable HubSpot integrations.

This guide provides advanced patterns for composing robust, multi-step Large Language Model (LLM) workflows using LangChain 1.0 core runnables. Learn to implement parallel retrievals (RunnableParallel), conditional routing (RunnableBranch), and state management. It also addresses common pitfalls like silent KeyErrors due to mismatched dictionary shapes, providing solutions using debug probes and type annotations for reliable RAG, classification, and extraction pipelines.

A structured playbook for diagnosing and resolving critical disruptions within the Navan travel platform. It guides users through severity classification (P1-P4), utilizing built-in AI assistants (Ava), and performing essential API health checks using tools like curl and jq. This runbook ensures a systematic approach to handling failures related to bookings, OAuth tokens, and expense syncing, minimizing downtime and providing clear escalation paths.