Understudy Labs
Official@understudylabs
Offers infrastructure for local-first model distillation, trajectory curation, and deterministic evaluation of production-grade inference workloads.
Agent Skills by Understudy Labs
Showing 22 vetted skills indexed across 1 GitHub repositories.
understudylabsprepare-verifier-handoff
Determine hosted RL necessity and guide staged handoff packaging with conformance checks.
understudylabsmanage-local-models
Acquire, cache, and organize local open-weight models with SHA256 verification.
understudylabsingest-traces
Ingest production LLM traces into redacted eval sets and cost profiles.
understudylabsdesign-simulated-environment
Create deterministic simulated environments with seeded state and oracle-based scoring for agent workloads.
understudylabscompare-model-sweep
Evaluate candidate models across a fixed evaluation to identify the Pareto frontier.
understudylabscurate-trajectories
Curate trajectories into a decontaminated, provenance-tracked training dataset.
understudylabsunderstand-workload
Identify workload purpose and success criteria from traces and prompts.
understudylabscapture-evidence
Generate harness, metric, splits, and baseline artifacts from workloads.
understudylabsdistill-classifier
Distill frontier classifiers into lightweight open-weight students using teacher-labeler hard-label distillation.
understudylabsladder
Compare local and frontier models side-by-side on fixture-driven tasks.
understudylabsonboard
Automate developer onboarding by profiling environments and writing ~/.understudy/profile.json.
understudylabscompare-trajectories
Compare trajectory exports to classify per-task behavioral gaps between model runs.
understudylabsinstall-plugin
Install, update, and verify the Understudy Claude Code plugin from a local repository.
understudylabsrecursive-language-model
Decompose complex agentic tasks into bounded steps with a small local model.
understudylabsramp-and-verify
Orchestrate staged live-traffic ramps with safety gates and rollback triggers.
understudylabsrun-local-model-lab
Compare local MLX models against frontier gateways on latency, cost, and quality.
understudylabsoptimize-agentic-workload
Optimize multi-turn tool-calling agent loops for cost and latency.
understudylabsplan-hosted-run
Estimates time and cost for hosted ML jobs to select optimal provider.
understudylabslocal-distillation-lab
Compare weight-update training methods for local on-device model distillation.
understudylabsuse-understudy-gateway
Route developer workloads through the Understudy gateway or manage local keys.
understudylabsoptimize-workload
Automate GEPA-driven prompt and routing optimization with holdout protection.
understudylabsunderstudy
Orchestrate local-first agent improvement workflows using traces, evals, and route decisions.
Frequently Asked Questions About Understudy Labs
FAQPage SchemaWhat specific tasks can I perform using Understudy Labs?▼
You can curate provenance-tracked training datasets, distill frontier classifiers into lightweight students, and perform side-by-side comparisons of local versus frontier models. The system enables deterministic environment simulation, production trace ingestion, and staged traffic ramping with integrated safety gates.
Which personas benefit most from these capabilities?▼
Machine learning engineers and infrastructure developers focused on model optimization, cost reduction, and quality assurance benefit most. These capabilities are designed for teams managing complex inference loops who require rigorous evaluation, provenance tracking, and local-first model management.
What are the prerequisites for running these model labs?▼
Users require a local environment capable of supporting MLX-based model execution and the Understudy plugin. Configuration involves initializing a local profile via the provided onboarding utility, which maps environment variables and establishes the necessary gateway keys for routing and trace ingestion.