Official agent skill

Fix Verify

by intel in intel/torch-xpu-ops

A skill your agent uses when asked to verify a fix works, confirm a staged patch resolves a failure, or produce a before/after summary of a fix.

OfficialApache-2.0Auto-check passedAI & LLM Engineering

Install Fix Verify

skills CLI
$ npx skills add intel/torch-xpu-ops --skill fix-verify -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install intel/torch-xpu-ops fix-verify --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/intel/torch-xpu-ops.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/fix-verify .claude/skills/fix-verify && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
fix-verify
GitHub stars
115
Token cost
~3.3k tokens
SKILL.md length
1,460 words
Files
1
Skills in repo
29
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when asked to verify a fix works, confirm a staged patch resolves a failure, or produce a before/after summary of a fix.

  • Works in 4 steps: Classify whether a rebuild is needed → Verify the fix → Run test → …
  • Asked to verify a fix works
  • SKILL.md covers Contents, Inputs, Shell helpers and Step 1: Classify whether a…, plus 4 more sections
  • Calls git, python and pip

What it does

Fix Verify is an agent skill from intel/torch-xpu-ops, published by the product's own GitHub organization. Use when asked to verify a fix works, confirm a staged patch resolves a failure, or produce a before/after summary of a fix. Runs the test command against a source build with the fix applied and reports PASSED / FAILED / CANNOTVERIFY. Called by both issue-handler orchestrator after fix-implement.

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering. It works with C++ and PyTorch. The licence is Apache-2.0.

When your agent uses it

  • Asked to verify a fix works
  • Confirm a staged patch resolves a failure
  • Produce a before/after summary of a fix

Example prompts

  • “/fix-verify”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Classify whether a rebuild is needed
  2. Verify the fix
  3. Run test
  4. Lint

What it can do on your machine

Read from SKILL.md and the folder at commit 0187b3b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git
    • python
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git and pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Fix Verify loads about 3.3k tokens when it runs. Until then it costs about 77 tokens; SKILL.md has 1,460 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~77
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from intel/torch-xpu-ops at commit 0187b3b, republished under its Apache-2.0 licence (© intel). 1,460 words, ~3,344 tokens.

Download SKILL.mdSave it as .claude/skills/fix-verify/SKILL.md (or your agent's skills folder).
name
fix-verify
description
Use when asked to verify a fix works, confirm a staged patch resolves a failure, or produce a before/after summary of a fix. Runs the test command against a source build with the fix applied and reports PASSED / FAILED / CANNOT_VERIFY. Called by both issue-handler orchestrator after fix-implement.

Verify — Confirm the Fix Works

Runs the test with the fix applied and reports whether the fix is effective. A fix that has to be compiled in is verified against a source build — never a nightly wheel, which cannot see local code.

Contents

Inputs

  • refined_command — the exact test command from fix-reproduce's output.
  • PYTORCH_DIR — path to local PyTorch checkout.
  • target_repo_dir — path to the checkout that holds the staged fix (same derivation rule as in fix-implement: equals PYTORCH_DIR for target_repo=pytorch, <PYTORCH_DIR>/third_party/torch-xpu-ops for target_repo=torch-xpu-ops). All git operations run against target_repo_dir. The rebuild (Step 2) still runs from PYTORCH_DIR because pip install -e . builds pytorch and pulls its submodule pin.
  • changed_files — list of changed files from fix-implement's output; if any are C++/SYCL (.cpp, .h, .cu, .sycl) or CMake (CMakeLists.txt, *.cmake), a rebuild is required before running.

This skill always rebuilds if needed (Step 2) and runs the test with the fix applied (Step 3), then lints a passing result (Step 4); there are no flags to toggle any of these off.

Shell helpers

The recipes below call abort (exit non-zero with a diagnostic). It is not a shell builtin — define it once at the top of your shell, same as the orchestrators do:

bash
abort() { echo "ABORT: $*" >&2; exit 1; }

An abort in this skill means "return CANNOT_VERIFY to the orchestrator with that message as the blocker", never "continue silently".

Step 1: Classify whether a rebuild is needed

This step only classifies; the rebuild itself happens in Step 2.

If any of changed_files are C++/SYCL (.cpp, .h, .cu, .sycl) or CMake (CMakeLists.txt, *.cmake), a rebuild is required so the fix is compiled in before the test runs. On the first rebuild (Step 2), clean the build cache and retry once if xpu-build-pytorch reports a cache-related failure. For a torch-xpu-ops fix the rebuild also needs the third_party/xpu.txt pin override that makes CMake see the fix (done in Step 2).

If all changed files are python-only, no rebuild is needed — nothing has to be compiled for the edit to take effect.

Step 2: Verify the fix

Reaching this skill means fix-reproduce already ran the test and observed the failure (the "before" state). This step rebuilds with the fix applied (when needed) and sets up for the Step 3 test run that confirms it now passes. fix-implement always leaves the fix staged; the caller may additionally have committed it onto a branch before invoking this skill. Both arrangements are accepted — do not assume either. No stash/checkout dance is needed.

Assert the tested tree is the tree that gets handed off. The caller either exports base_sha..branch (committed) or picks up git diff --cached (staged), so the fix must live entirely in one of those two places — never partly in the worktree. Before rebuilding:

bash
# Nothing may be left in the worktree: an unstaged edit would be tested
# here but excluded from both hand-off paths. Check this first, so a fix
# that was edited but never staged reports the precise cause.
git -C "$target_repo_dir" diff --quiet || \
  { echo "FAILED reason=unstaged_changes_present"; exit 1; }

unstaged_changes_present catches a re-implement retry that edited a file without staging or amending it, which would make the tested tree differ from what the caller hands off.

All git commands here run against target_repo_dir (not PYTORCH_DIR); these can differ when target_repo == "torch-xpu-ops".

When any changed_files are C++/SYCL or CMake, the fix must be compiled in before the test (per Step 1). Python-only changes need no rebuild.

bash
# For torch-xpu-ops fixes, point the pin at the working branch so the
# rebuild sees the fix (Commit Pin & Development Override in AGENTS.md;
# do NOT stage or commit this file).
if [ "$target_repo_dir" != "$PYTORCH_DIR" ]; then
    git -C $target_repo_dir rev-parse HEAD > $PYTORCH_DIR/third_party/xpu.txt
fi
# Rebuild WITH the fix (only if C++/SYCL or CMake changed):
#   invoke xpu-build-pytorch skill here
# Then run the test in Step 3; its result is the "after" output.

Confirm the tree under test is the source build. A fix that the running interpreter does not pick up cannot be verified. Checking torch.version.git_version is NOT sufficient: released and nightly wheels also carry a real commit hash. Check where torch is imported from:

bash
python -c "import torch, os; print(os.path.realpath(torch.__file__))"
  • A rebuild was required (C++/SYCL/CMake): the printed path must be under $(realpath $PYTORCH_DIR)/torch/ — the rebuild above is what produces that source build. If it still resolves into site-packages of an unrelated prefix, the rebuild did not take effect: return CANNOT_VERIFY(reason=wheel_install_not_source) with blocker="torch imported from <path>; verify requires a source build".
  • No rebuild was required (python-only): a wheel install is fine for files the interpreter reads from the checkout (test files, skip lists), which is where python-only fixes normally live. A python fix inside the installed package (torch/) is not picked up by a wheel — same CANNOT_VERIFY(reason=wheel_install_not_source).

The "before" cell of the comparison table (Output section) is filled from fix-reproduce's recorded failure, not re-run here; "after" is the result from Step 3 with the fix applied. The two come from different phases (reproduce may have run against a nightly wheel, verify against the rebuilt tree), so the table is a before-fix-vs-after-fix summary, not a single-build A/B.

Caveat (read before trusting a PASSED verdict): because the "before" is a nightly-wheel failure and the "after" is a source build with the fix, a PASSED verdict means "the test passes on a source build that includes the fix" — it does not prove the fix is what made it pass. If the bug was already resolved upstream after the nightly was cut, the source build passes regardless of the fix. This skill does not re-run the source build without the fix to rule that out (that would cost a second cold build). State this limitation in the report; a human reviewing the patch should confirm the change is actually responsible.

Show full SKILL.md (615 more words)Show less

Step 3: Run test

Run ALL failing test cases from the original report individually.

Result interpretation:

  • all skipped → read pytest's SKIPPED [N] <file:line>: <reason> line to classify:
    • Reason matches an XPU marker (skipIfXpu, xfailIfXPU, expectedFailureXPU, skipXPU, or a message containing "xpu") → FAILED with reason=stale_skip_after_fix. Rationale: a fix that leaves the failing test skipped is an incomplete fix. This is intentionally different from fix-reproduce's handling — reproduce temporarily unskips to confirm the bug, but verify's job is to confirm the fix; if the XPU-marker skip is still in place, the fix did not touch what it should have. Suggest in reason_detail: "test still skipped after fix — the stale skip decorator should have been removed as part of the fix (see the Skip operations section of fix-implement)."
    • Reason is environmental (missing dep, no GPU, tool not found, "no accelerator", etc.) → CANNOT_VERIFY(reason=environmental_skip) with blocker="test skipped for environmental reason: <marker>".
  • xfailed → FAILED with reason=xfail_after_fix.
  • FAILED → FAILED with reason=test_still_failing.
  • PASSED → PASSED with reason=ok.

Step 4: Lint

Always run after a passing test result. Run it in target_repo_dir — the repo that owns the changed files — not in PYTORCH_DIR:

bash
cd $target_repo_dir
spin fixlint
# fixlint rewrites files in the working tree, leaving them unstaged.
# Stage them so the lint fixes travel with the fix and Step 2's
# clean-worktree invariant holds; the caller folds the staged lint fixes
# into its hand-off (issue-handler amends them into the fix commit).
# Nothing outside changed_files may be folded in; if `git status` shows
# fixlint touched other files, return FAILED rather than widening the diff.
git -C $target_repo_dir add -- <changed_files>
spin lint 2>&1 | tail -40
  • If clean: include lint: clean in the PASSED output.
  • If errors remain after fixlint: return FAILED(reason=lint_errors_after_autofix) with the lint errors as failure_output and suggest that the remaining errors need a human touch.

Output

Return to the orchestrator a report (markdown block plus JSON block). The skill does not commit or push — the caller consumes stdout and decides what to do, per the pattern established by issue-triage, fix-reproduce, fix-root-cause, and fix-implement.

Include the <!-- agent:verify --> marker on the first line of the markdown block so a downstream caller can locate its own previous verify comment (if any) and update it in place. Comment location and update is the caller's responsibility.

<!-- agent:verify -->

## Verify

<One or two sentences: what was built and where — source build sha or
wheel version, `TORCH_XPU_ARCH_LIST`, and the fact that baseline and
fixed builds differ only by the changed files.>

| Test case | Before | After |
|-----------|--------|-------|
| `TestFooXPU::test_bar` | FAIL | PASS |

<One line saying what `Before` was: the failure signature `fix-reproduce`
recorded, backticked.>

Regression checks on the fixed build:

| Suite | Result |
|---|---|
| `test_foo_ops.py -k xpu` | 85 passed, 1 skipped |

- **Verdict:** <PASSED | FAILED | CANNOT_VERIFY> — <one-line reason>
- **Lint:** <clean | errors: <summary>>

*Automated by fix-verify.*

Before = the failure fix-reproduce recorded; After = the Step 3 test result with the fix applied. One row per test case, same labels the reproduce block used. The regression table lists the suites run beyond the reproducer; omit the table and its heading line when none were run.

json
{
  "target_repo": "pytorch or torch-xpu-ops",
  "refined_command": "<echo of input>",
  "changed_files": ["path/to/file1.py"],
  "verdict": "PASSED or FAILED or CANNOT_VERIFY",
  "reason": "<enumerated reason code, see below>",
  "reason_detail": "one-line human-readable detail",
  "before_after_table": "<markdown table string, or null>",
  "failure_output": "<test/lint output excerpt on FAILED, or null>"
}
Field contract
  • target_repo — echo from fix-implement's output.
  • refined_command — echo the exact command that was run.
  • changed_files — echo from fix-implement; downstream orchestrator uses this to build the commit's file list.
  • before_after_table — the markdown table pairing fix-reproduce's recorded failure (before) with the Step 3 result (after); null only when the test never ran (e.g. a CANNOT_VERIFY before Step 3).
  • failure_output — non-null on FAILED; excerpt of the test or lint output (bounded — do not dump multi-MB logs, ~40 lines is enough for a human to see the failure).
reason values

On verdict=PASSED:

  • ok — test passed with the fix applied; lint clean.

On verdict=FAILED:

  • test_still_failing — Step 3 reported FAILED; fix is incomplete.
  • unstaged_changes_present — Step 2 found edits left in the worktree, outside both hand-off paths; the tested tree would differ from what the caller picks up.
  • stale_skip_after_fix — Step 3 reported all skipped with an XPU marker still in place.
  • xfail_after_fix — Step 3 reported xfailed; fix did not turn the test green.
  • lint_errors_after_autofix — Step 4 could not clean the lint after spin fixlint; a human touch is needed.
  • unrelated_files_touched_by_lint — Step 4's spin fixlint modified files outside changed_files.

On verdict=CANNOT_VERIFY:

  • wheel_install_not_source — Step 2 saw torch imported from site-packages; can't verify a source-tree fix through a wheel.
  • rebuild_failed — xpu-build-pytorch returned failure during the Step 2 rebuild.
  • environmental_skip — Step 3's all skipped had an environmental reason (missing dep, no accelerator).
  • test_collect_zero — Step 3's refined_command resolves to zero collected tests; the fix cannot be validated against the reported reproducer.
  • test_timeout — the test process exceeded its timeout and was killed.
  • other — fallback; put full explanation in reason_detail.

The orchestrator decides whether to loop back to fix-implement on FAILED, or proceed to commit/PR on PASSED, based on verdict and reason.

© intel, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/fix-verify of intel/torch-xpu-ops.

Open the folder on GitHubat commit 0187b3b

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Works with

Questions about Fix Verify

What does Fix Verify do?

A skill your agent uses when asked to verify a fix works, confirm a staged patch resolves a failure, or produce a before/after summary of a fix. Fix Verify is an agent skill from intel/torch-xpu-ops, published by the product's own GitHub organization. Use when asked to verify a fix works, confirm a staged patch resolves a failure, or produce a before/after summary of a fix.

When should I use Fix Verify?

Fix Verify fits situations like: asked to verify a fix works; confirm a staged patch resolves a failure; produce a before/after summary of a fix.

How do I install Fix Verify in Claude Code?

Run `npx skills add intel/torch-xpu-ops --skill fix-verify -a claude-code`. Or copy the skill folder (.claude/skills/fix-verify in intel/torch-xpu-ops) into .claude/skills/fix-verify in your project. Claude Code loads it when a task matches its description.

How do I install Fix Verify in Codex?

Run `npx skills add intel/torch-xpu-ops --skill fix-verify -a codex`. Or copy the skill folder (.claude/skills/fix-verify in intel/torch-xpu-ops) into .agents/skills/fix-verify in your project. Codex loads it when a task matches its description.

Can I use Fix Verify in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add intel/torch-xpu-ops --skill fix-verify -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fix-verify, .gemini/skills/fix-verify, .github/skills/fix-verify and .opencode/skills/fix-verify in your project.

What does Fix Verify need to run?

Going by SKILL.md and its folder, Fix Verify needs the command-line tools its instructions call (git, python and pip). Our summary lists: Python 3.

Does Fix Verify access the network?

SKILL.md contains no URLs. Its commands use git and pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Fix Verify safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Fix Verify use?

Fix Verify is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Fix Verify use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Fix Verify?

Skills that share tags, products or a category with Fix Verify: Ako4all (TongmingLAIC/AKO4ALL, 369 stars), Paddle Op Dev (PaddlePaddle/Paddle, 24k stars), Embedded AI Deployment (matlab/agent-skills-playground, 181 stars) and Qualcomm QNN Backend Development (pytorch/executorch, 5.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fix Verify?

intel (a GitHub organization, an official publisher) maintains it in intel/torch-xpu-ops, which has 115 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on October 6, 2026.

Source: intel/torch-xpu-ops on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.