Ako4all
TongmingLAIC/AKO4ALL
Drive an agentic loop that iteratively optimizes a GPU kernel for maximum speedup.
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.
$ npx skills add intel/torch-xpu-ops --skill fix-verify -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install intel/torch-xpu-ops fix-verify --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "fix-verify" agent skill from https://github.com/intel/torch-xpu-ops/tree/main/.claude/skills/fix-verify into .claude/skills/fix-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fix-verify", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/intel/torch-xpu-ops/tree/main/.claude/skills/fix-verifyType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add intel/torch-xpu-ops --skill fix-verify -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install intel/torch-xpu-ops fix-verify --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/intel/torch-xpu-ops.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/fix-verify .agents/skills/fix-verify && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "fix-verify" agent skill from https://github.com/intel/torch-xpu-ops/tree/main/.claude/skills/fix-verify into .agents/skills/fix-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fix-verify", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add intel/torch-xpu-ops --skill fix-verify -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install intel/torch-xpu-ops fix-verify --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/intel/torch-xpu-ops.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/fix-verify .cursor/skills/fix-verify && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "fix-verify" agent skill from https://github.com/intel/torch-xpu-ops/tree/main/.claude/skills/fix-verify into .cursor/skills/fix-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fix-verify", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/intel/torch-xpu-ops.git --path .claude/skills/fix-verify--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add intel/torch-xpu-ops --skill fix-verify -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install intel/torch-xpu-ops fix-verify --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/intel/torch-xpu-ops.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/fix-verify .gemini/skills/fix-verify && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "fix-verify" agent skill from https://github.com/intel/torch-xpu-ops/tree/main/.claude/skills/fix-verify into .gemini/skills/fix-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fix-verify", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install intel/torch-xpu-ops fix-verifyInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add intel/torch-xpu-ops --skill fix-verify -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/intel/torch-xpu-ops.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/fix-verify .github/skills/fix-verify && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "fix-verify" agent skill from https://github.com/intel/torch-xpu-ops/tree/main/.claude/skills/fix-verify into .github/skills/fix-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fix-verify", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add intel/torch-xpu-ops --skill fix-verify -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install intel/torch-xpu-ops fix-verify --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/intel/torch-xpu-ops.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/fix-verify .opencode/skills/fix-verify && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "fix-verify" agent skill from https://github.com/intel/torch-xpu-ops/tree/main/.claude/skills/fix-verify into .opencode/skills/fix-verify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fix-verify", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
fix-verifyA 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. 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.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 0187b3b. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
gitpythonpipFrom the folder's file list and the shell code blocks in SKILL.md.
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.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
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.
.claude/skills/fix-verify/SKILL.md (or your agent's skills folder).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.
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.
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:
abort() { echo "ABORT: $*" >&2; exit 1; }An abort in this skill means "return CANNOT_VERIFY to the
orchestrator with that message as the blocker", never "continue
silently".
This step only classifies; the rebuild itself happens in Step 2.
If any of changed_files are C++/SYCL (.cpp, .h, .cu, .sycl)
or CMake (CMakeLists.txt, *.cmake), a rebuild is required so the fix
is compiled in before the test runs. On the first rebuild (Step 2), clean
the build cache and retry once if xpu-build-pytorch reports a
cache-related failure. For a torch-xpu-ops fix the rebuild also needs the
third_party/xpu.txt pin override that makes CMake see the fix (done in
Step 2).
If all changed files are python-only, no rebuild is needed — nothing has to be compiled for the edit to take effect.
Reaching this skill means fix-reproduce already ran the test and
observed the failure (the "before" state). This step rebuilds with the
fix applied (when needed) and sets up for the Step 3 test run that
confirms it now passes. fix-implement always leaves the fix
staged; the caller may additionally have committed it onto a branch
before invoking this skill. Both arrangements are accepted — do not
assume either. No stash/checkout dance is needed.
Assert the tested tree is the tree that gets handed off. The caller
either exports base_sha..branch (committed) or picks up
git diff --cached (staged), so the fix must live entirely in one of
those two places — never partly in the worktree. Before rebuilding:
# Nothing may be left in the worktree: an unstaged edit would be tested
# here but excluded from both hand-off paths. Check this first, so a fix
# that was edited but never staged reports the precise cause.
git -C "$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.
# 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 > $PYTORCH_DIR/third_party/xpu.txt
fi
# Rebuild WITH the fix (only if C++/SYCL or CMake changed):
# invoke xpu-build-pytorch skill here
# Then run the test in Step 3; its result is the "after" output.Confirm the tree under test is the source build. A fix that the
running interpreter does not pick up cannot be verified. Checking
torch.version.git_version is NOT sufficient: released and nightly
wheels also carry a real commit hash. Check where torch is imported
from:
python -c "import torch, os; print(os.path.realpath(torch.__file__))"$(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".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.
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: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)."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.Always run after a passing test result. Run it in target_repo_dir —
the repo that owns the changed files — not in PYTORCH_DIR:
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 -40lint: clean in the PASSED output.FAILED(reason=lint_errors_after_autofix) with the lint errors as
failure_output and suggest that the remaining errors need a
human touch.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.
{
"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>"
}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 valuesOn 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
Just SKILL.md in .claude/skills/fix-verify of intel/torch-xpu-ops.
Open the folder on GitHubat commit 0187b3b
Fix Verify next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Fix Verify this skillintel/torch-xpu-ops | 115 | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | |
| Ako4allTongmingLAIC/AKO4ALL | 369 | — | ~4k | Automated safety check: Pass | MIT | |
| Paddle Op DevPaddlePaddle/Paddle | 24k | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Embedded AI Deploymentmatlab/agent-skills-playground | 181 | 1 repos | ~3.4k | Automated safety check: Pass | Custom licence | |
| Qualcomm QNN Backend Developmentpytorch/executorch | 5.1k | — | ~1.8k | Automated safety check: Pass | Custom licence | |
| Paddle Cross Ecosystem Custom OpPaddlePaddle/Paddle | 24k | — | ~883 | Automated safety check: Pass | Apache-2.0 |
TongmingLAIC/AKO4ALL
Drive an agentic loop that iteratively optimizes a GPU kernel for maximum speedup.
PaddlePaddle/Paddle
PaddlePaddle (飞桨) C++ 算子开发指南。提供从 YAML 配置、InferMeta 函数、Kernel 实现、Python API 封装、单元测试到编译验证的完整算子开发流程指导。在以下场景使用此 skill:(1) 为 Paddle 框架新增 C++ 算子 (2) 修改或调试已有 Paddle 算子 (3) 编写算子的 YAML…
matlab/agent-skills-playground
Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder).
pytorch/executorch
Helps build, test and extend the Qualcomm AI Engine Direct (QNN) backend in ExecuTorch, with routes for new ops, model export, Buck-vs-CMake parity fixes and per-layer accuracy debugging.
PaddlePaddle/Paddle
将原生 PyTorch 自定义算子库、Torch extension、生态库(TorchCodec/FlashInfer/DeepEP 等)以及 Kernel DSL 生态(Triton/TileLang/TVM FFI 等)以最小修改方式接入 PaddlePaddle。遇到以下场景务必使用:迁移外部算子库到 Paddle;分析 PFCCLab fork 与上游的兼容差异;处理…
amd/Quark
Install or verify the AMD Quark package and its dependencies.
intel/torch-xpu-ops
Select the Intel GPU device to use when a system has multiple Intel GPU devices.
intel/torch-xpu-ops
Check PyTorch ciflow/xpu (xpu.yml) on the main branch, collect the failing XPU test cases from the most recent completed run(s), analyze the ROOT CAUSE of each failure with AI, and produce a list…
intel/torch-xpu-ops
Convert PyTorch ATDISPATCH macros to ATDISPATCHV2 format in ATen C++ code.
intel/torch-xpu-ops
Review pull requests for XPU operator or backend code. An agent skill from intel/torch-xpu-ops.
intel/torch-xpu-ops
Guide users through creating Agent Skills for Claude Code. An agent skill from intel/torch-xpu-ops.
intel/torch-xpu-ops
Read the evidence a nightly UT run produced, decide which failures share a root cause and which are machine breakage rather than product bugs, and write one issue draft per root cause to drafts.json.
Categories
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.