Skill UI

A comprehensive guide for rapid incident response and troubleshooting of Miro API v2 integration failures. It covers defining severity levels, quick triage steps, detailed error handling for 4xx/5xx status codes (e.g., token expiration, rate limiting), mitigation strategies, and postmortem evidence collection.

This comprehensive bundle collects all necessary diagnostic artifacts for troubleshooting Palantir Foundry issues. It gathers SDK versions, environment variables (with secrets automatically redacted), API connectivity status, and recent application error logs. This structured output is essential for creating detailed, actionable support tickets when reporting persistent platform malfunctions.

Zero-context verification system that checks every number, comparison, and scope claim in research papers against raw result files. Uses a fresh cross-model reviewer with no prior context to prevent confirmation bias. Ideal for academic integrity, paper submission, and ensuring paper-to-evidence fidelity before publication.

Use the Parallel CLI for web search, URL/PDF extraction, deep research, data enrichment, entity discovery, and recurring web monitoring. Best when requests need current web evidence, academic sources, or change tracking.

This internal agent skill defines a systematic, multi-step procedure for scanning GitHub repositories to gather comprehensive evidence supporting or explaining bug clusters. The process covers searching open issues, inspecting recent commits, analyzing code paths, and checking deployment history. It assigns evidence confidence tiers (Exact, Strong, Moderate, Weak) to provide a deep, actionable understanding of potential software defects.

A comprehensive utility designed to collect all necessary diagnostic evidence from a Salesforce organization. This debug bundle aggregates API limits, detailed debug logs, organization identity, API usage logs, and current Salesforce system status. It is crucial for preparing thorough support tickets or troubleshooting persistent, hard-to-reproduce issues.

A comprehensive bash script designed to collect critical diagnostic evidence for troubleshooting SalesLoft API issues. It checks authentication status, current rate limit headers, and the operational health of key endpoints. This bundle is ideal for preparing detailed, reproducible support tickets when encountering persistent API connectivity or authorization problems.

This script collects comprehensive diagnostic evidence necessary for resolving persistent Shopify issues. It gathers critical data points such as API version compatibility, access scopes, GraphQL and REST rate limit status, and environment details, packaging everything into a single, redacted archive for easy submission to technical support. Use this when troubleshooting complex platform errors or preparing a detailed support ticket.

Collects comprehensive diagnostic evidence from Snowflake's ACCOUNT_USAGE views, QUERY_HISTORY, and environment details. This tool is essential for troubleshooting persistent performance issues, connection failures, or preparing detailed support cases for Snowflake support, ensuring all necessary logs, query metrics, and resource usage data are collected in one package.

This internal agent skill defines the structured procedure for displaying bug triage results in terminal markdown format. It generates comprehensive summaries of bug clusters, provides detailed views of evidence and reports, and handles the parsing and execution flow for user review commands (e.g., `details`, `file`, `dismiss`, `escalate`). It is a core component for automated bug triage and defect management workflows.

This utility collects comprehensive diagnostic evidence necessary for troubleshooting Webflow integrations and API usage. It automatically gathers crucial data points into a single, support-ready diagnostic bundle. Key metrics include the Webflow SDK version, API token validation status, rate limit headers, site connectivity reports, CMS health checks, and recent error logs, significantly streamlining the technical support process.

This skill ingests public complaints from X/Twitter, automatically detecting, classifying, and clustering reported bugs. It cross-references symptoms with repository evidence (commits, deploys) and assigns ownership using defined routing rules. It is essential for product teams needing to monitor product health and gather early bug signals from social media channels.