Skill UI

This skill provides integration with Grammarly's Writing Score API, enabling applications to automatically score documents. It evaluates writing quality across four dimensions: engagement, correctness, clarity, and tone. Use this when building content quality assurance features, implementing quality gates, or providing detailed, multi-dimensional feedback on written content.

A guide and toolkit for optimizing Grammarly API costs in large-scale applications. It addresses common cost overruns associated with high text volume by implementing strategies such as result caching, chunking long documents, sample-based scoring, and setting usage budget alerts. Use this when integrating Grammarly into enterprise workflows or managing billing for high-volume content analysis.

Implements a robust data pipeline for handling large documents with the Grammarly API. This utility manages text chunking to comply with API character limits (max 100k), processes text in manageable segments, and aggregates multiple scoring metrics (like correctness, clarity, and tone) into a single, comprehensive report. Ideal for large-scale content analysis and data ingestion.

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.

A comprehensive guide and implementation pattern for handling rate limits, backoff, and idempotency when integrating with the Grammarly Text API. It provides a custom rate limiter and robust retry logic to manage API throughput, ensuring reliable processing of high volumes of documents and stable interaction with various endpoints (e.g., writing score, plagiarism checks).

A comprehensive runbook for systematically handling Intercom API outages and integration failures. It guides technical teams through rapid triage (checking status codes, rate limits, and service status), implementing mitigation strategies like graceful degradation, and documenting post-incident reports (postmortem). Essential for maintaining service reliability during Intercom service interruptions.

This tool guides the transformation of a raw, rough invention idea into a formal, patent-ready disclosure document. It employs established patent frameworks, such as the Problem-Solution-Advantage model, and systematically deconstructs the invention into core, supporting, and optional features. It also assists in identifying appropriate claim types (method, system, product) and planning necessary supporting figures, ensuring comprehensive intellectual property protection.

This structured skill guides users through root-cause-first debugging when an implementer is blocked, verification fails, or repeated attempts at fixing do not converge. It mandates a systematic approach combining local evidence inspection, runtime analysis, and external documentation research to accurately classify the failure's true source (e.g., missing dependency, spec conflict). It prevents speculative patching and generates a clear, actionable fix plan.

This utility analyzes a codebase (product, technology, and structure) to automatically extract core architectural patterns, guiding principles, and engineering standards. It manages a persistent 'Steering' repository, performing initial bootstrapping and continuous synchronization. It detects 'code drift' when the code deviates from established patterns and suggests additive updates, ensuring project documentation remains a comprehensive source of truth.

This skill helps users create specialized 'steering documents' or project memory for highly specific domains (e.g., API standards, testing strategies, security patterns). By analyzing the existing codebase and following predefined architectural principles, it synthesizes concise, actionable guides that capture technical patterns, best practices, and domain-specific rules, ensuring project consistency and knowledge retention.

A deep dive into handling typed content blocks (text, image, tool_use, thinking, document) in LangChain 1.0. This skill standardizes multi-modal message composition, tool-call iteration, and complex content handling across providers like Claude, GPT-4o, and Gemini, solving key API discrepancies.

This comprehensive guide details common errors encountered when integrating with the Linktree API. It covers various HTTP status codes, such as 400 (Invalid URL), 401 (Authentication Failed), and 429 (Rate Limit). The document provides specific causes (e.g., expired keys, malformed data, plan restrictions) and actionable fixes, helping developers build stable and reliable link-in-bio services.