查找技能

Review an explicitly identified Marin pull request as a whole change, asking whether it fits repository patterns, whether a better abstraction exists, and what breaks outside the diff; use for large or agent-authored PRs, after or alongside review-pr.

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Triage a failed canary ferry run only when invoked by CI with the required CANARY context.

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Archive explicitly named legacy experiment files by publishing a dated tag and canonical issue breadcrumbs.

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Review an explicitly identified Marin pull request against the repository's correctness and maintainability expectations.

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Run the docs/code-parity scrub only from its scheduler or an explicit request for that scrub.

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Launch, resume, monitor, hand off, or seal an explicitly requested production-critical Marin run, normally at least 1e22 FLOPs.

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Research an explicitly requested Marin question or coordinate a multi-session experiment; find prior work, assess evidence, and record results in the task's existing durable surface.

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Apply Marin house style when producing or revising commit, pull-request, issue, comment, documentation, report, or blog prose.

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Harvest experiment issue reports and curate docs/reports/index.md only when explicitly requested.

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Use Marin's fsutil CLI for local object-storage operations across GCS, CoreWeave S3, R2, and local paths. Use whenever a task needs to list, inspect, read, size, find, copy, move, synchronize, hash, browse, or remove data at gs:// or s3:// URLs from a checkout. Do not launch an Iris job solely to access object storage.

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Define, validate, submit, or restart a Marin SkyRL experiment through its artifact main. Use for RL launch files, SkyRLRolePlan or SkyRLTopology changes, MarinSkyRL configuration, RL smoke tests, and requests to launch or relaunch RL on Iris.

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Query Finelog logs and telemetry for Iris tasks, workers, profiles, training, vLLM, and cross-cluster forwarding. Use for schema discovery, SQL, memory or CPU summaries, hub-versus-regional comparisons, counter semantics, and query-performance diagnosis.

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Use only when a change is ready to commit, push, or open or update its pull request; do not activate during implementation.

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Use Iris to submit, inspect, debug, monitor, or recover jobs and tasks; diagnose scheduling and federation; deploy controllers; or reserve dev GPUs and TPUs. Use for ordinary Iris operations, including babysitting a job, controller rollouts, accelerator sessions, and stuck CoreWeave pods. Use a narrower production-run or Zephyr skill when that workflow is explicitly requested.

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Modify or upstream behavior in a named Grug/Grugformer experiment variant.

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Use scripts/logscan.py only when explicitly requested to scan an oversized log or to perform Gemini-backed log analysis.

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Design or revise a Marin experiment pipeline that binds reusable work into an artifact graph. Use for new workflow entrypoints, stage wiring, and pipeline placement decisions; use a narrower domain skill when it owns the launch.

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Build, validate, release, inspect, query, roll back, or archive a Marina application. Maintained source apps and uploaded applets use Postgres packages and marina release, independently of Marina runtime deployment.

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Launch or continuously monitor a specified Zephyr pipeline on Iris only when asked to babysit it; restart only after explicit approval.

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Diagnose a stated code, JAX, Marin, Iris, Zephyr, or TPU fault or startup/performance regression; do not activate for ordinary implementation or optimization without a symptom.

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Run the read-only infra/lint PR reporter only when invoked by CI or explicitly requested; do not select it for the commit workflow's fix-and-respond review.

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Deslop, simplify, or review low-value tests and prose only when explicitly requested for a branch or diff.

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Register a named Hugging Face dataset for Marin by inspecting its schema and adding the appropriate experiments/datasets module.

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Refresh a named Marin external fork pin onto a newer upstream base using its configured descriptor and required end-to-end test.

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