Query PyTorch CI, GitHub Actions, HUD, Grafana, and infrastructure metrics. Use when users ask about CI duration, job failures, queue times, workflow trends, runner health, dashboard data, or PyTorch infrastructure metrics.
EnglishChoose 32-bit vs 64-bit index math in PyTorch CUDA kernels. Use when fixing large-tensor indexing overflows, deciding whether to use int64t, canUse32BitIndexMath, CUDAKERNELLOOPTYPE, or ATDISPATCHINDEXTYPES, and when considering binary-size or performance impact of index-type templating.
EnglishSub-triages issues in the oncall:distributed queue by assigning distributed module labels, routing to sub-oncalls, and marking triaged. Use when an issue has been routed to oncall:distributed and needs second-level triage.
EnglishDocument undocumented public APIs in PyTorch by removing functions from coverageignorefunctions and coverageignoreclasses in docs/source/conf.py, running Sphinx coverage, and adding the appropriate autodoc directives to the correct .md or .rst doc files. Use when a user asks to remove functions from conf.py ignore lists.
EnglishUse when something is failing in ML/AI work — OOM, NaN, divergence, crashes, bad throughput, wrong outputs, dependency…
EnglishDebug PyTorch 2 compiler stack failures including Dynamo graph breaks, Inductor codegen errors, AOTAutograd crashes, and accuracy mismatches. Use when encountering torch.compile errors, BackendCompilerFailed exceptions, recompilation issues, Triton kernel failures, FX graph problems, or when the user mentions debugging PT2, Dynamo, Inductor, or compiled model issues.
EnglishMigrate a file to use stricter Pyrefly type checking with annotations required for all functions, classes, and attributes.
EnglishFetch, analyze, reproduce, and minimize GitHub issue reproductions. Use when asked to check if an issue reproduces, minimize a repro, analyze a bug report, or scrub/triage an issue for reproducibility.
EnglishIncludes CI Metrics, Cuda Index Width, Distributed Triage, and other workflows.
Supported by the Atlas install prompt. Skill-specific requirements vary.
Pack stats
What’s included
CI Metrics
Query PyTorch CI, GitHub Actions, HUD, Grafana, and infrastructure metrics. Use when users ask about CI duration, job failures, queue times, workflow trends, runner health, dashboard data, or PyTorch infrastructure metrics.
Cuda Index Width
Choose 32-bit vs 64-bit index math in PyTorch CUDA kernels. Use when fixing large-tensor indexing overflows, deciding whether to use int64t, canUse32BitIndexMath, CUDAKERNELLOOPTYPE, or ATDISPATCHINDEXTYPES, and when considering binary-size or performance impact of index-type templating.
Distributed Triage
Sub-triages issues in the oncall:distributed queue by assigning distributed module labels, routing to sub-oncalls, and marking triaged. Use when an issue has been routed to oncall:distributed and needs second-level triage.
Document Public APIs
Document undocumented public APIs in PyTorch by removing functions from coverageignorefunctions and coverageignoreclasses in docs/source/conf.py, running Sphinx coverage, and adding the appropriate autodoc directives to the correct .md or .rst doc files. Use when a user asks to remove functions from conf.py ignore lists.
Ml Debug
Use when something is failing in ML/AI work — OOM, NaN, divergence, crashes, bad throughput, wrong outputs, dependency conflicts
Pt2 Bug Basher
Debug PyTorch 2 compiler stack failures including Dynamo graph breaks, Inductor codegen errors, AOTAutograd crashes, and accuracy mismatches. Use when encountering torch.compile errors, BackendCompilerFailed exceptions, recompilation issues, Triton kernel failures, FX graph problems, or when the user mentions debugging PT2, Dynamo, Inductor, or compiled model issues.
Pyrefly Type Coverage
Migrate a file to use stricter Pyrefly type checking with annotations required for all functions, classes, and attributes.
Scrub Issue
Fetch, analyze, reproduce, and minimize GitHub issue reproductions. Use when asked to check if an issue reproduces, minimize a repro, analyze a bug report, or scrub/triage an issue for reproducibility.
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