Skill UI

A comprehensive operational runbook for managing outages and errors related to Mistral AI integrations. It provides structured procedures, including severity classification, quick API health checks, decision trees for common errors (401, 429, 5xx), immediate mitigation steps, and post-incident evidence collection and reporting.

This tool collects comprehensive diagnostic evidence for troubleshooting Miro REST API v2 integration problems. It gathers environment details, performs connectivity tests (DNS, HTTPS), checks rate limits, and aggregates recent application logs into a single, structured bundle. Use this when preparing a detailed support ticket or diagnosing persistent API issues.

A comprehensive pre-submission tool designed to guide authors targeting ACS Nano. It assesses whether a nanoscience or nanotechnology manuscript meets the journal's high standards across scope, method rigor, structural presentation, and conceptual framing. Use this skill to re-frame your work, understand the required evidence (e.g., single-molecule studies, quantitative benchmarks), and ensure optimal fit before official submission.

This comprehensive guide serves as a venue selection and content re-framing tool for research at the intersection of energy and environmental science. It details the high quantitative standards, required evidence (e.g., LCA, full-cell data, techno-economic analysis), and specific scope areas (solar, batteries, CO₂ capture) expected by Energy & Environmental Science (EES). Use this before submission to ensure your manuscript meets EES's broad, interdisciplinary impact criteria.

A comprehensive guide for structuring the evidence bundle required for robotics research submissions. It details the critical components—including hardware ledgers, time-stamped logs, configuration files, code, and data—necessary to ensure that scientific claims are fully auditable and reproducible, addressing the needs of skeptical reviewers.

A skill for designing evidence and validation strategies for academic manuscripts submitted to the Journal of Systems Engineering. It covers standards for numerical experiments, simulations, real data, case studies, and empirical research, ensuring claims are supported by appropriate evidence rather than generic robustness checks.