Claude Code plugins
4 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
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ML pipeline design, experiment tracking, model evaluation, training debugging, and reproducibility.
developer tools
LLM and prompt evaluation with Promptfoo, DeepEval and Ragas, Giskard vulnerability scans, Langfuse tracing, and golden-dataset regression suites. Audits eval suites for methodology errors. Agents (prompt-eval-reviewer, llm-red-team-planner) review an eval suite and plan adversarial probe campaigns across the OWASP LLM Top 10.
ai-ml
Autonomous optimization loop — iterates on prompts, skills, templates, or code overnight. Two evaluation modes: deterministic (eval.py with proxy heuristics) for mechanical checks, or AI judge (LLM rubric scoring) for creative/subjective quality. Uses 4-way agent separation for unbiased evaluation.
Create new agent skills from scratch, modify and improve existing skills, and measure skill performance through evaluation and benchmarking. Use when users want to create a skill, write a skill, build a new skill, edit or optimize an existing skill, run evals to test a skill, benchmark skill performance, or optimize a skill's description for better triggering accuracy. Also triggers when users say "turn this into a skill", "make a skill for X", "skill for doing Y", or ask about skill structure, skill format, or SKILL.md files.