Menu

Individual skill

warp-debug-gradients

Use to diagnose and fix incorrect gradients in differentiable Warp programs. Anything trained, optimized, calibrated, or fit through Warp kernels depends on wp.Tape gradients, so treat any misbehavior of such a workflow as a gradient problem until proven otherwise — use this when training diverges or NaNs, won't train at all, stalls or plateaus above the expected loss, converges to a wrong or biased answer, is worse than a reference implementation, works at small scale but fails at production scale, or fails a QA/validation recheck. Also for explicit symptoms — exploding, NaN/inf, zero, or subtly wrong gradients, suspected wp.Tape/backward issues, gradcheck failures — but users usually describe only the surface symptom ("the sim explodes", "the fit gets dragged toward outliers") without mentioning gradients: make that leap. Not for forward-only Warp work, build/install problems, or autograd issues in other frameworks without Warp.

skills/warp-debug-gradients/SKILL.md

Read pinned source

Source commit 25340619336e89bcc40365c28bfe9e790430468e

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
No
Observed behavior
Network or broad shell
Last checked
Nov 2, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
3,888
Repository last updated
Nov 6, 2026
License
Apache-2.0

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# Debugging Gradients in Warp

Gradient bugs in Warp are almost never math bugs. The forward simulation looks
perfectly healthy while the backward pass silently reads clobbered values,
skips arrays, or double-counts adjoints. Users routinely burn days tuning
physics knobs, loss functions, and assets when the real cause is a two-line
taping-pattern fix. Your job is to find that fix with evidence, not intuition.

The single most important discipline: **measure before hypothesizing**. It is
cheap for you to run a shrunk reproduction and compare autodiff against finite
differences. The *way* the gradient is wrong (its signature) prunes the
hypothesis space far faster than reading code ever will. Do not start
proposing fixes from code reading alone — plausible-looking diagnoses of
differentiability bugs are very often wrong, and an unverified "fix" that