AI/ML · Global library
Build evaluation loops for AI systems with benchmark sets, rubric design, judge calibration, and human-review anchors.
Best use case
Use AI Evaluation Framework Builder when you need to build evaluation loops for AI systems with benchmark sets, rubric design, judge calibration, and human-review anchors, especially when the work is driven by ai evaluation and benchmark suite.
Trigger signals
Validation hooks
Install surface
Inspect
pip install "orchestrator-mcp[dashboard]"
orchestrator-mcp skills show ai-evaluation-framework-builderUse
orchestrator-mcp skills export ai-evaluation-framework-builder --to ./skillforge-packs
# copy the exported pack into your preferred agent environmentExport
cp -R skills/ai-evaluation-framework-builder ./your-agent-skills/ai-evaluation-framework-builder
# or open skills/ai-evaluation-framework-builder/SKILL.md in a markdown-first clientFile patterns
Model preferences
Related skills
Design robust communication protocols for agent systems with message schemas, serialization, and delivery guarantees
Manage complete agent lifecycles from initialization through graceful shutdown with health monitoring, scaling, and resource optimization
Design short-term, long-term, and episodic memory layers for agents without turning retrieval into an unbounded context leak.