Pre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.

TAO Execution SDK for submitting and monitoring GPU training jobs on supported platforms (Brev, SLURM, local Docker, Kubernetes). Use when the user wants to run TAO jobs through the SDK, get job tracking, S3 I/O wrapping, multi-node distributed training, or platform-specific features that docker-run can't provide. Trigger phrases include "use the TAO SDK", "call tao_sdk", "AutoMLRunner", "ActionWorkflow", "Job handles", "S3 I/O wrapping", "TAO platform run".

Load a sharded, on-disk dataset (sharded .npy, Parquet/Arrow, raw binary, sharded HDF5, custom layouts) into a distributed cuPyNumeric ndarray via a manual partition + leaf @task launch with CPU/OMP/GPU variants. Use when no single-call loader fits, including when per-shard row counts differ across files. Prefer cupynumeric.load or legate.io.hdf5.from_file when they apply.

Full PAIDF AnomalyGen pipeline — fine-tune on a new anomaly dataset, generate synthetic anomaly images (SDG), evaluate quality (nn_score), and search per-sample (guidance, crop_ratio) parameters. Three modes: full (Phase 0→7: finetune then generate), finetune_only (Phase 0→1: train only), inference_only (Phase 0, 2→7: generate from an existing checkpoint). Use when the user asks to "fine-tune AnomalyGen", "generate anomaly images", "run PAIDF SDG", "evaluate SDG output quality", "run per-sample search", or run any part of the AnomalyGen pipeline, even if they only mention one phase.

Install and verify cuPyNumeric for Python — requirements, commands, verification. Source builds are out of scope.

This skill should be used when the user asks to notify other session, requests a session handoff, says tell other agent, or needs a cross-session message.

This skill should be used when the user asks to notify other session, requests a session handoff, says tell other agent, or needs a cross-session message.

Launch new CLI coding agents through Corral Design 1, or correctly reopen existing agent sessions inside a Corral-active Herdr repository. Use when the user asks to launch, spawn, batch-start, reopen, relaunch, or resume agents. New launches create Corral-owned tasks; resumptions reuse existing worktrees and sessions.

Distill colleague, relationship, or celebrity source material into reusable Person Profiles for agents.

Stands in for a public repo the customer merely scanned

Synthetic purge-rehearsal skill t5-delta

Synthetic purge-rehearsal skill t5-gamma

Synthetic purge-rehearsal skill t5-beta

A review checklist deliberately shared between two inventories

Synthetic purge-rehearsal skill t5-alpha

Synthetic purge-rehearsal skill ctl-beta

Synthetic purge-rehearsal skill ctl-alpha

A review checklist deliberately shared between two inventories