PyTorch Issue Triage Skill

This skill helps triage GitHub issues by routing issues, applying labels, and leaving first-line responses.

MCP Tools Available
Labels You Must NEVER Add
Issue Triage Steps
- Step 0: Already Routed — SKIP
- Step 1: Question vs Bug/Feature
- Step 1.5: Needs Reproduction — External Files
- Step 2: Transfer
- Step 2.5: PT2 Issues — Special Handling
- Step 3: Redirect to Secondary Oncall
- Step 4: Label the Issue
- Step 5: High Priority — REQUIRES HUMAN REVIEW
- Step 6: bot-triaged (automatic)
- Step 7: Mark Triaged
V1 Constraints

Labels reference: See labels.json for the full catalog of 305 labels suitable for triage. ONLY apply labels that exist in this file. Do not invent or guess label names. This file excludes CI triggers, test configs, release notes, and deprecated labels.

PT2 triage guide: See pt2-triage-rubric.md for detailed labeling guidance when triaging PT2/torch.compile issues.

Response templates: See templates.json for standard response messages.

MCP Tools Available

Use these GitHub MCP tools for triage:

Tool	Purpose
`mcp__github__issue_read`	Get issue details, comments, and existing labels
`mcp__github__issue_write`	Apply labels or close issues
`mcp__github__add_issue_comment`	Add comment (only for redirecting questions)
`mcp__github__search_issues`	Find similar issues for context

Labels You Must NEVER Add

Prefix/Category	Reason
Labels not in `labels.json`	Only apply labels that exist in the allowlist
`ciflow/*`	CI job triggers for PRs only
`test-config/*`	Test suite selectors for PRs only
`release notes: *`	Auto-assigned for release notes
`ci-` , `ci:`	CI infrastructure controls
`sev*`	Severity labels require human decision
`merge blocking`	Requires human decision
Any label containing "deprecated"	Obsolete

If blocked: When a label is blocked by the hook, add ONLY

triage review

and stop. A human will handle it.

These rules are enforced by a PreToolUse hook that validates all labels against

labels.json

Issue Triage (for each issue)

0) Already Routed — SKIP

If an issue already has ANY
oncall:
label, SKIP IT entirely. Do not:

Add any labels
Add
```
triaged
```
Leave comments
Do any triage work

That issue belongs to the sub-oncall team. They own their queue.

1) Question vs Bug/Feature

If it is a question (not a bug report or feature request): close and use the
```
redirect_to_forum
```
template from
```
templates.json
```
.
If unclear whether it is a bug/feature vs a question: request additional information using the
```
request_more_info
```
template and stop.

1.5) Needs Reproduction — External Files

Check if the issue body contains links to external files that users would need to download to reproduce.

Patterns to detect:

File attachments:
```
.zip
```
,
```
.pt
```
,
```
.pth
```
,
```
.pkl
```
,
```
.safetensors
```
,
```
.onnx
```
,
```
.bin
```
files
External storage: Google Drive, Dropbox, OneDrive, Mega, WeTransfer links
Model hubs: Hugging Face Hub links to model files

Action:

Edit the issue body to remove/redact the download links

Replace with:

[Link removed - external file downloads are not permitted for security reasons]

Add
```
needs reproduction
```
label
Use the
```
needs_reproduction
```
template from
```
templates.json
```
to request a self-contained reproduction
Do NOT add
```
triaged
```
— wait for the user to provide a reproducible example

1.6) Edge Cases & Numerical Accuracy

If the issue involves extremal values or numerical precision differences:

Patterns to detect:

Values near

torch.finfo(dtype).max

torch.finfo(dtype).min

NaN/Inf appearing in outputs from valid (but extreme) inputs
Differences between CPU and GPU results
Precision differences between dtypes (e.g., fp32 vs fp16)
Fuzzer-generated edge cases

Action:

Add
```
module: edge cases
```
label
If from a fuzzer, also add
```
topic: fuzzer
```
Use the
```
numerical_accuracy
```
template from
```
templates.json
```
to link to the docs
If the issue is clearly expected behavior per the docs, close it with the template comment

2) Transfer (domain library or ExecuTorch)

If the issue belongs in another repo (vision/text/audio/RL/ExecuTorch/etc.), transfer the issue and STOP.

2.5) PT2 Issues — Special Handling

When triaging PT2 issues (torch.compile, dynamo, inductor), see pt2-triage-rubric.md for detailed labeling decisions.

Key differences from general triage:

For PT2 issues, you MAY apply

module:

labels (e.g.,

module: dynamo

module: inductor

module: dynamic shapes

)

Use the rubric to determine the correct component labels
Only redirect to
```
oncall: cpu inductor
```
for MKLDNN-specific issues; otherwise keep in PT2 queue

3) Redirect to Secondary Oncall

CRITICAL: When redirecting issues to an oncall queue (critical with the exception of PT2), apply exactly one

oncall: ...

label and STOP. Do NOT:

Add any
```
module:
```
labels
Mark it
```
triaged
```
Do any further triage work

The sub-oncall team will handle their own triage. Your job is only to route it to them.

Oncall Redirect Labels

Label	When to use
`oncall: jit`	TorchScript issues
`oncall: distributed`	Distributed training (DDP, FSDP, RPC, c10d, DTensor, DeviceMesh, symmetric memory, context parallel, pipelining)
`oncall: export`	torch.export issues
`oncall: quantization`	Quantization issues
`oncall: mobile`	Mobile (iOS/Android), excludes ExecuTorch
`oncall: profiler`	Profiler issues (CPU, GPU, Kineto)
`oncall: visualization`	TensorBoard integration

Note:

oncall: cpu inductor

is a sub-queue of PT2. For general triage, just use

oncall: pt2

4) Label the issue (if NOT transferred/redirected)

Only if the issue stays in the general queue:

Add 1+
```
module: ...
```
labels based on the affected area
If feature request: add
```
feature
```
(or
```
function request
```
for a new function or new arguments/modes)
If small improvement: add
```
enhancement
```

5) High Priority — REQUIRES HUMAN REVIEW

CRITICAL: If you believe an issue is high priority, you MUST:

Add
```
triage review
```
label and do not add
```
triaged
```

Do NOT directly add

high priority

without human confirmation.

High priority criteria:

Crash / segfault / illegal memory access
Silent correctness issue (wrong results without error)
Regression from a prior version
Internal assert failure
Many users affected
Core component or popular model impact

6) bot-triaged (automatic)

The

bot-triaged

label is automatically applied by a post-hook after any issue mutation. You do not need to add it manually.

7) Mark triaged

If not transferred/redirected and not flagged for review, add

triaged

V1 Constraints

DO NOT:

Close bug reports or feature requests automatically
Close issues unless they are clear usage questions per Step 1
Assign issues to users
Add
```
high priority
```
directly without human confirmation
Add module labels when redirecting to oncall
Add comments to bug reports or feature requests, except a single info request when classification is unclear

DO:

Close clear usage questions and point to discuss.pytorch.org (per step 1)
Be conservative - when in doubt, add
```
triage review
```
for human attention
Apply type labels (
```
feature
```
,
```
enhancement
```
,
```
function request
```
) when confident
Add
```
triaged
```
label when classification is complete