Thermo Nuclear Code Quality Review
nicknisi/claude-plugins
Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth.
Review your own verl-omni branch against the project rubric before opening or updating a PR.
$ npx skills add verl-project/verl-omni --skill self-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install verl-project/verl-omni self-review --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/verl-project/verl-omni.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/code-review .claude/skills/self-review && 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 "self-review" agent skill from https://github.com/verl-project/verl-omni/tree/main/.agents/skills/code-review into .claude/skills/self-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "self-review", 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/verl-project/verl-omni/tree/main/.agents/skills/code-reviewType 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 verl-project/verl-omni --skill self-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install verl-project/verl-omni self-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/verl-project/verl-omni.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/code-review .agents/skills/self-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "self-review" agent skill from https://github.com/verl-project/verl-omni/tree/main/.agents/skills/code-review into .agents/skills/self-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "self-review", 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 verl-project/verl-omni --skill self-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install verl-project/verl-omni self-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/verl-project/verl-omni.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/code-review .cursor/skills/self-review && 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 "self-review" agent skill from https://github.com/verl-project/verl-omni/tree/main/.agents/skills/code-review into .cursor/skills/self-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "self-review", 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/verl-project/verl-omni.git --path .agents/skills/code-review--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 verl-project/verl-omni --skill self-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install verl-project/verl-omni self-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/verl-project/verl-omni.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/code-review .gemini/skills/self-review && 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 "self-review" agent skill from https://github.com/verl-project/verl-omni/tree/main/.agents/skills/code-review into .gemini/skills/self-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "self-review", 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 verl-project/verl-omni self-reviewInstalls 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 verl-project/verl-omni --skill self-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/verl-project/verl-omni.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/code-review .github/skills/self-review && 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 "self-review" agent skill from https://github.com/verl-project/verl-omni/tree/main/.agents/skills/code-review into .github/skills/self-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "self-review", 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 verl-project/verl-omni --skill self-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install verl-project/verl-omni self-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/verl-project/verl-omni.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/code-review .opencode/skills/self-review && 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 "self-review" agent skill from https://github.com/verl-project/verl-omni/tree/main/.agents/skills/code-review into .opencode/skills/self-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "self-review", 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.
self-reviewReview your own verl-omni branch against the project rubric before opening or updating a PR.
Self Review is an agent skill from verl-project/verl-omni. Review your own verl-omni branch against the project rubric before opening or updating a PR. Use before submitting a contribution, or whenever asked to self-review. Report-only: covers technical purpose, code quality, goal completeness and validation evidence, with a READY / NEEDS CHANGES verdict. Never edits files.
Its SKILL.md is about 2k 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 Development, covering Code quality and Quizzes and assessments. The repository describes itself as: Multimodal RL training framework for diffusion & omni models. 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 022b110. 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:
gitFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
github.comFrom 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.
Self Review loads about 2k tokens when it runs. Until then it costs about 82 tokens; SKILL.md has 934 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 verl-project/verl-omni at commit 022b110, republished under its Apache-2.0 licence (© verl-project). 934 words, ~2,018 tokens.
.claude/skills/self-review/SKILL.md (or your agent's skills folder).Review the whole change, not only its latest commit. Keep the report proportional to the diff; a small fix does not need a technical essay.
Report-only — do not edit, commit, or push as part of reviewing. Once the contributor makes fixes, load commit-and-pr for the commit/PR conventions and run-cpu-tests for tests.
Identify the intended base and its remote; a stacked PR may not target main.
Record the exact base and head SHAs, then inspect the whole three-dot diff:
git remote -v
git fetch <base-remote> <base-branch>
git rev-parse <base-ref> HEAD
git diff <base-ref>...HEADDo not replace this with a last-commit review. A two-dot comparison against newer
main includes main-only changes; check the merge base before calling those
regressions. Use individual commits for history, not to omit parts of the final
diff. For local uncommitted work, also inspect git diff --cached and git diff.
Re-check affected evidence if the reviewed head changes.
AGENTS.md is the top-level contract. Read the current guides, not a remembered
copy. Formatting and project-specific conventions belong to these sources:
| Area | Guide |
|---|---|
| code style, runtime boundaries, shell recipes | .agents/rules/code-style.md |
| config dataclasses / generated YAML | .agents/rules/config.md |
| diffusion pipelines / adapters | .agents/rules/pipelines.md, docs/contributing/integrating_a_diffusion_model.md |
| diffusion algorithm | add-pipeline selects the policy-gradient or direct-preference guide |
| reward scorers | .agents/rules/reward.md |
| tests | .agents/rules/testing.md, docs/contributing/testing_guide.md |
| recurring traps | docs/contributing/common_pitfalls.md |
| CI / GPU smoke | docs/contributing/ci_cd.md, docs/contributing/gpu_smoke_tests.md |
Summarize the problem, the mechanism being changed, and why the change is needed. Trace the relevant callers and consumers: e.g. config → allocation → worker, rollout → replay → loss, or adapter export → binding → forward. Check whether an existing implementation already solves it before recommending another abstraction.
Inspect changed lines and their execution context, using the code-style rules. Classify findings by subject; these categories are not severity levels:
| Category | Inspect |
|---|---|
| Correctness | tensor shape/dtype/device, gradients, wire compatibility, concurrency and resource lifetime |
| Performance | host/device synchronization, allocation, hot-loop overhead and measured workload equivalence |
| Maintainability | ownership, reuse, imports, naming and unnecessary abstractions |
| Style | clarity, useful comments/types and consistency beyond automated formatting |
| Process | reproducible tests, dependency compatibility and evidence for the claimed scope |
Mark an issue blocking or non-blocking from its impact, independently of category. Missing critical validation can block; a naming preference usually cannot. Do not invent findings to avoid saying the code is sound, or impose source-line limits, blanket bans on framework hooks, or formatter-only nits.
Project-specific checks:
prompt_token_ids, multi_modal_data and extra_fields intact end to end.
Unsupported or conflicting fields must not disappear silently.DiffusionIOSpec / media_kind rather than guessing
modality from ndim or a dimension equal to three.Each finding needs: severity + category + evidence tag → path:line → triggering
input/path → impact and why → concrete fix or next verification step.
Compare the final diff with the issue and PR description. List unmet requirements, unsupported configurations, prerequisite PRs and changed defaults/compatibility. An intentional limitation is not a proven bug, but must not be presented as implemented or validated support. Check that examples and docs use the same contract as the code.
Separate what you ran from author-reported evidence and untested paths. Choose the required layer from the testing guide; CPU tests, GPU trainer completion, performance and convergence are different claims, not interchangeable badges.
.github/*_pin.txt and the interpreter/worker source binding before
attributing an import or runtime failure to the patch. Compare with the base
when needed; a dependency mismatch is not automatically a code regression.AGENTS.md for disclosure and human accountability, and never check off human
review on someone else's behalf.End with READY / NEEDS CHANGES, blocking actions, and residual risks. READY means no blockers for the stated scope, not proof of untested GPU behavior or convergence. If required evidence is missing, explain why it blocks. If there are no findings, say what supports that conclusion rather than just "LGTM".
Iterate after the contributor fixes findings. Keep review notes out of the code diff. Suggest updating the PR description when scope or evidence changes.
Publishing follows the accountability rules in AGENTS.md: draft review
comments and replies for the user, and post only what they asked for and
approved word for word.
When asked to suggest reviewers, use docs/community/governance.md for ownership
and .github/CODEOWNERS for path routing (last matching rule wins). Suggest at
most two relevant owners; do not automatically tag them.
The four-part review structure is adapted from Code Review Style Guide. Project rules take precedence: categories are separate from severity, abstraction is contextual, and evidence replaces speculative AI-code detection.
<!--
MAINTAINER GUIDE — Keep rule details in .agents/rules/ and procedures in docs/.
Recheck this rubric when review permissions, wire contracts or CI gates change.
-->
© verl-project, 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 .agents/skills/code-review of verl-project/verl-omni.
Open the folder on GitHubat commit 022b110
Self Review 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 |
|---|---|---|---|---|---|---|
| Self Review this skillverl-project/verl-omni | 1.2k | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Thermo Nuclear Code Quality Reviewnicknisi/claude-plugins | 114 | — | ~3.4k | Automated safety check: Pass | MIT | |
| Skill Doctoralirezarezvani/claude-skills | 28k | — | ~1.5k | Automated safety check: Pass | MIT | |
| LobeHub Alint Rule Set Maintenancelobehub/lobehub | 83k | — | ~1.9k | Automated safety check: Pass | Custom licence | |
| Review PRmicrosoft/vscode-containers | 141 | — | ~900 | Automated safety check: Pass | Custom licence | |
| RAG Code Reviewlyonzin/knowledge-rag | 292 | — | ~1.8k | Automated safety check: Pass | MIT |
nicknisi/claude-plugins
Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth.
alirezarezvani/claude-skills
A skill your agent uses when the user wants their agent setup graded from real conversation history, asks which installed skills are actually working, or wants evidence-backed skill edits — scores…
lobehub/lobehub
Maintains LobeHub's model-backed alint rule set: writing rules, removing false positives against real code, deciding warn versus error and tracking token cost.
microsoft/vscode-containers
Review a specific vscode-containers pull request on demand from the CLI (or any interactive agent), the way a Container Tools maintainer would.
lyonzin/knowledge-rag
When performing code review on a PR, diff, snippet, or "look at this change" request, first consult the corpus for related ADRs, coding standards, prior patterns, and similar files.
tetherto/qvac
Run the deterministic code-quality audit, turn related findings into contextual remediation groups, prepare approval-gated Asana proposals, reconcile recurring runs, or configure twice-monthly…
verl-project/verl-omni
Router for adding a diffusion or omni pipeline to verl-omni.
verl-project/verl-omni
Guide for adding a new reward scorer to verl-omni and wiring it into a run.
verl-project/verl-omni
Route a verl-omni performance investigation to the right tool and capture a usable trace.
verl-project/verl-omni
How to write and run verl-omni CPU tests (testoncpu.py) that exercise adapters, rewards, and configs without a GPU or model weights.
verl-project/verl-omni
verl-omni commit message + PR conventions and the mandatory contribution policy.
verl-project/verl-omni
Route verl-omni training/inference consistency checks through MindStudio's MSProbe collection and root-cause analysis skills.
Categories
Review your own verl-omni branch against the project rubric before opening or updating a PR. Self Review is an agent skill from verl-project/verl-omni. Review your own verl-omni branch against the project rubric before opening or updating a PR.
Self Review fits situations like: tasks that involve Code quality; tasks that involve Quizzes and assessments.
Run `npx skills add verl-project/verl-omni --skill self-review -a claude-code`. Or copy the skill folder (.agents/skills/code-review in verl-project/verl-omni) into .claude/skills/self-review in your project. Claude Code loads it when a task matches its description.
Run `npx skills add verl-project/verl-omni --skill self-review -a codex`. Or copy the skill folder (.agents/skills/code-review in verl-project/verl-omni) into .agents/skills/self-review 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 verl-project/verl-omni --skill self-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/self-review, .gemini/skills/self-review, .github/skills/self-review and .opencode/skills/self-review in your project.
Going by SKILL.md and its folder, Self Review needs the command-line tools its instructions call (git).
SKILL.md names 1 domain. As links in the text: github.com. 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.
Self Review 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 2k tokens (SKILL.md is roughly 8.1k 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 Self Review: Thermo Nuclear Code Quality Review (nicknisi/claude-plugins, 114 stars), Skill Doctor (alirezarezvani/claude-skills, 28k stars), LobeHub Alint Rule Set Maintenance (lobehub/lobehub, 83k stars) and Review PR (microsoft/vscode-containers, 141 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
verl-project (a GitHub organization) maintains it in verl-project/verl-omni, which has 1,210 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 9, 2026.
Source: verl-project/verl-omni on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.