Use when working with MLflow traces: debugging via MCP tools, analyzing performance, logging feedback, writing custom scorers/evaluations, or cleaning up trace data
How to install mlflow-traces?
galbaz1/video-research-mcp/mlflow-traces
$npx -y skills add galbaz1/video-research-mcp --skill mlflow-tracesInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/galbaz1/video-research-mcp" --skill "galbaz1/video-research-mcp/mlflow-traces"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/galbaz1/video-research-mcp" that are relevant to the current task. Run `npx skills add "https://github.com/galbaz1/video-research-mcp"` and select the relevant skills, then follow their instructions.
Related
6 picksType
- researchInvestigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo.Jul 2026
- analyze-projectRigor Analyze / Rigor Audit read-only skill for deep learning research repositories.Jul 2026
- paper-context-resolverRigor Paper Context helper for README-first deep learning repo reproduction.Jul 2026
- repo-intake-and-planRigor Intake helper for README-first deep learning repo reproduction.Jul 2026
- firecrawl-searchWeb search with full page content extraction. Use this skill whenever the user asks to search the web, find articles, research a topic, look something up, find…Jul 2026
- customer-researchWhen the user wants to conduct, analyze, or synthesize customer research.Jul 2026
