Hands-on prompt engineering and LLM evaluation. Built around a diagnose-then-ship loop: forensic transcript critique ▎ that names the exact failure mode, paired with a fixer that produces complete, deployment-ready rewrites — not ▎ vague advice.
This skill is based on practical Power Platform delivery patterns for safely creating, reviewing, and modifying Power Automate cloud-flow JSON in Dataverse solution exports. It focuses on issues that often break real client automations: runAfter paths, renamed action references, connection references, hardcoded values, TRY/CATCH logging, import safety, validation, and rollback notes.
Analyze failed CI/CD pipelines, identify likely root causes, inspect repository configuration and code context, and produce actionable, validated remediation guidance for GitHub Actions, GitLab CI, Jenkins, and related development pipelines.
Analysez logs, diagnostics, erreurs et éléments techniques fournis afin d’identifier des causes probables, prioriser les anomalies et préparer un plan de correction.
Turn factory data into a bottleneck, capacity, and layout-risk decision.
Turn machinery specs into a structured compliance gap-analysis in seconds — find the gaps before your Notified Body or auditor does. Screens cranes, earthmoving, MEWP and manufacturing cells against ISO, OSHA and EU CE frameworks.
I've spent years building production software, designing enterprise architectures, reviewing thousands of code changes, and optimizing AI-assisted development workflows. This Skill packages proven engineering, planning, documentation, testing, and code-review practices into a lightweight workflow that helps AI understand any project before making changes, reducing mistakes, hallucinations, unnecessary token usage, and repeated context loading.
I work daily with Windows infrastructure — Active Directory, GPO, hybrid identity with Entra ID, endpoint hardening (TPM, BitLocker, WDAC), and migration planning for SMB environments. I've built this agent around the same diagnostic workflow I use on real environments: form hypotheses first, ask precise questions, and only prescribe after understanding the actual root cause. No checklists. No generic advice.
Scan AI Skills and MCP servers before installation. Detect risky scripts, permissions, dependencies, network access, credential exposure, file changes, and suspicious configurations — then generate a clear evidence-based security report.