WooCommerce Code Review
woocommerce/woocommerce
Reviews WooCommerce code changes against the project's standards, flagging backend PHP architecture, naming, documentation, data integrity and testing violations.
Facilitate a structured conversation to define clean code principles for a repository.
$ npx skills add techygarg/lattice --skill clean-code-refiner -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install techygarg/lattice clean-code-refiner --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/techygarg/lattice.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/clean-code-refiner .claude/skills/clean-code-refiner && 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 "clean-code-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/clean-code-refiner into .claude/skills/clean-code-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clean-code-refiner", 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/techygarg/lattice/tree/main/skills/clean-code-refinerType 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 techygarg/lattice --skill clean-code-refiner -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install techygarg/lattice clean-code-refiner --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/clean-code-refiner .agents/skills/clean-code-refiner && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "clean-code-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/clean-code-refiner into .agents/skills/clean-code-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clean-code-refiner", 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 techygarg/lattice --skill clean-code-refiner -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install techygarg/lattice clean-code-refiner --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/clean-code-refiner .cursor/skills/clean-code-refiner && 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 "clean-code-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/clean-code-refiner into .cursor/skills/clean-code-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clean-code-refiner", 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/techygarg/lattice.git --path skills/clean-code-refiner--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 techygarg/lattice --skill clean-code-refiner -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install techygarg/lattice clean-code-refiner --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/clean-code-refiner .gemini/skills/clean-code-refiner && 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 "clean-code-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/clean-code-refiner into .gemini/skills/clean-code-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clean-code-refiner", 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 techygarg/lattice clean-code-refinerInstalls 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 techygarg/lattice --skill clean-code-refiner -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/clean-code-refiner .github/skills/clean-code-refiner && 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 "clean-code-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/clean-code-refiner into .github/skills/clean-code-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clean-code-refiner", 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 techygarg/lattice --skill clean-code-refiner -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install techygarg/lattice clean-code-refiner --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/clean-code-refiner .opencode/skills/clean-code-refiner && 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 "clean-code-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/clean-code-refiner into .opencode/skills/clean-code-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clean-code-refiner", 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.
clean-code-refinerFacilitate a structured conversation to define clean code principles for a repository.
Clean Code Refiner is an agent skill from techygarg/lattice. Facilitate a structured conversation to define clean code principles for a repository. Produces a formal clean-code.md document that the clean-code atom will use as its override. Use when setting up coding standards, defining code quality rules, or when the user says 'setup clean code', 'define coding standards', 'code quality principles', 'coding guidelines', or 'help me define my code standards'.
Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including assets (for example `assets/template.md`).
It sits in Development, covering Code quality. The repository describes itself as: Install engineering discipline into any AI coding assistant. Composable skills for design, implementation, review, and team standards. Better process, not just better prompts. The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 4d6c35f. 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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
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.
Clean Code Refiner loads about 3k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 1,604 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 techygarg/lattice at commit 4d6c35f, republished under its MIT licence (© techygarg). 1,604 words, ~3,042 tokens.
.claude/skills/clean-code-refiner/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub..lattice/standards/clean-code.md (or custom path from .lattice/config.yaml -> paths.clean_code)mode: overlay): A slim document containing only sections that differ from the defaults. The clean-code atom reads its embedded defaults first, then applies this document's sections on top. This is the expected common case.mode: override): A comprehensive standalone document that fully replaces the atom's embedded defaults. For teams with fundamentally different coding standards.paths.clean_code in .lattice/config.yaml./assets/template.md for the full document structure, default content, and interview guidance commentsThis skill defines the rules of code craftsmanship -- how individual functions, classes, and modules should be written. It does not define architecture (that is the architecture-refiner) or domain modeling (that is the ddd-refiner). The boundaries:
Before starting the interview, check whether a custom document already exists:
.lattice/config.yaml -- does paths.clean_code point to a file?Look for signals that inform the conversation:
Share relevant findings with the user at the start: "I noticed your project has ESLint configured with max-complexity: 15 and uses Prettier for formatting. I'll use that as context."
If the project is new with no code, proceed with pure defaults as the starting point.
The first decision in the conversation. Present the three options:
"How would you like to define your clean code principles?
The defaults cover standard clean code practices well. Option 1 is recommended unless your coding standards are fundamentally different."
Map the choice:
mode: overlaymode: overrideThis should be fast. Many sections will be "keep as-is."
This is thorough. Every section gets attention and appears in the output.
Read ./assets/template.md and follow the <!-- INTERVIEW GUIDANCE: --> comments for each section. Those comments contain the specific questions to ask, probing questions, and what is customizable vs fixed.
Decisions in early sections affect later sections. When a user changes an early section, flag the dependent sections:
| Decision in | Affects | How |
|---|---|---|
| §1 -- SRP scope (classes vs functions-only) | §2 (extraction targets), §10 (checklist) | Functional codebases extract to functions only; class-based codebases also extract to classes |
| §2 -- Function size thresholds | §3 (complexity thresholds), §10 (checklist) | Shorter functions imply lower complexity budgets |
| §3 -- Complexity thresholds | §2 (function size) | Lower complexity limits may require stricter function size |
| §4 -- Naming conventions | §7 (comment necessity) | Better naming reduces the need for "what" comments |
| §5 -- Parameter design | §1 (SRP signals) | Long parameter lists often signal SRP violations |
| §8 -- Error handling strategy | §9 (testability patterns) | Result types vs exceptions change how error paths are tested |
When a dependency is triggered, inform the user: "Since you changed [X], we should also review [Y] -- it's affected by that decision."
For each of the 10 default sections:
For each of the 10 default sections:
mode: overlaydefaults.md exactly (the atom matches sections by heading)mode: overrideStrip all <!-- INTERVIEW GUIDANCE: --> comments from the output. The final document is a clean specification.
Determine output path:
.lattice/config.yaml exists and has paths.clean_code, use that path..lattice/standards/clean-code.md.Write the document:
.lattice/standards/ directory (and .lattice/ parent) if it does not exist.Update config:
.lattice/config.yaml does not exist, create it with:paths:
clean_code: .lattice/standards/clean-code.md.lattice/config.yaml exists but has no paths.clean_code, add the key. Preserve all existing content..lattice/config.yaml exists and already has the key, no config change needed.Confirm to user:
"Your clean code document has been written to [PATH] in [overlay|override] mode. The clean-code atom will now use it [on top of the defaults | instead of the defaults]."
Before writing the final document, verify:
defaults.md exactly (for section matching by the atom)<!-- INTERVIEW GUIDANCE: --> comments remainmode: overlay<!-- INTERVIEW GUIDANCE: --> comments remainmode: override.lattice/config.yaml) is correctly updated© techygarg, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (assets) in skills/clean-code-refiner of techygarg/lattice.
Open the folder on GitHubat commit 4d6c35f
Clean Code Refiner 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 |
|---|---|---|---|---|---|---|
| Clean Code Refiner this skilltechygarg/lattice | 198 | — | ~3k | Automated safety check: Pass | MIT | |
| WooCommerce Code Reviewwoocommerce/woocommerce | 11k | 3 repos | ~1.1k | Automated safety check: Pass | Custom licence | |
| Systematic Code Refactoringluongnv89/claude-howto | 42k | — | ~3k | Automated safety check: Pass | MIT | |
| Install Anti-Slop Oxlint Rulesdmmulroy/anti-slop | 5.2k | — | ~2.2k | Automated safety check: Pass | MIT | |
| Constraint-Driven Developmentaddyosmani/agent-skills | 102k | 2 repos | ~5.2k | Automated safety check: Pass | MIT | |
| Skill Doli Code ReviewDolibarr/dolibarr | 7.7k | 1 repos | ~1.1k | Automated safety check: Pass | MIT |
woocommerce/woocommerce
Reviews WooCommerce code changes against the project's standards, flagging backend PHP architecture, naming, documentation, data integrity and testing violations.
luongnv89/claude-howto
Guides refactoring in phases based on Martin Fowler's method: research, test coverage check, planning and small tested steps, with your approval at each phase.
dmmulroy/anti-slop
Installs, updates or migrates the vendored anti-slop Oxlint plugin in a repository, keeping local rule changes and the plugin's license and provenance files.
addyosmani/agent-skills
Records a project's quality bar in CONSTRAINTS.md and watches diffs for signs an agent quietly weakened it, such as suppressions, skipped tests or lowered thresholds.
Dolibarr/dolibarr
Reviews Dolibarr PHP code for compliance with coding standards and security best practices, and fixes identified issues.
docling-project/docling
Applies opinionated production Python conventions chosen by the project's Python version: modern type syntax, pathlib, explicit checks and interface guidance.
techygarg/lattice
Architectural thinking partner for an existing repository — scans the codebase, conducts a structured interview, agrees on current architectural state and recommended direction, and produces a…
techygarg/lattice
Guided setup and upgrade-check experience for Lattice projects -- scans the repository, detects existing configuration and outdated conventions, suggests refiners and available upgrades in priority…
techygarg/lattice
Audit and fix all Lattice documentation, README, docs/, PROJECT.md, GitHub issue templates, and CLAUDE.md to ensure they are fully aligned with the current skill inventory.
techygarg/lattice
Validate any Lattice SKILL.md against all tier conventions — atoms, molecules, and refiners.
techygarg/lattice
Facilitate a structured conversation to define architecture principles for a repository.
techygarg/lattice
Manage per-feature living documents that capture decisions, constraints, and reasoning across AI sessions during active development.
Categories
Facilitate a structured conversation to define clean code principles for a repository. Clean Code Refiner is an agent skill from techygarg/lattice. Facilitate a structured conversation to define clean code principles for a repository.
Clean Code Refiner fits situations like: setting up coding standards; defining code quality rules; the user says setup clean code; define coding standards.
Run `npx skills add techygarg/lattice --skill clean-code-refiner -a claude-code`. Or copy the skill folder (skills/clean-code-refiner in techygarg/lattice) into .claude/skills/clean-code-refiner in your project. Claude Code loads it when a task matches its description.
Run `npx skills add techygarg/lattice --skill clean-code-refiner -a codex`. Or copy the skill folder (skills/clean-code-refiner in techygarg/lattice) into .agents/skills/clean-code-refiner 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 techygarg/lattice --skill clean-code-refiner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/clean-code-refiner, .gemini/skills/clean-code-refiner, .github/skills/clean-code-refiner and .opencode/skills/clean-code-refiner in your project.
SKILL.md names no scripts, command-line tools or credentials: Clean Code Refiner is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. 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.
Clean Code Refiner is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3k tokens (SKILL.md is roughly 12k 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 Clean Code Refiner: WooCommerce Code Review (woocommerce/woocommerce, 11k stars), Systematic Code Refactoring (luongnv89/claude-howto, 42k stars), Install Anti-Slop Oxlint Rules (dmmulroy/anti-slop, 5.2k stars) and Constraint-Driven Development (addyosmani/agent-skills, 102k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
techygarg (a GitHub user) maintains it in techygarg/lattice, which has 198 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 6, 2026.
Source: techygarg/lattice on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.