Agent skill

Code Quality Review

by ntorga in ntorga/agent-starter-kit

Reviews code and plans against the project's coding rules. An agent skill from ntorga/agent-starter-kit.

MITAuto-check passedDevelopment

Install Code Quality Review

skills CLI
$ npx skills add ntorga/agent-starter-kit --skill code-quality-review -a claude-code

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

GitHub CLI
$ gh skill install ntorga/agent-starter-kit code-quality-review --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/ntorga/agent-starter-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/code-quality-review .claude/skills/code-quality-review && 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
code-quality-review
GitHub stars
146
Token cost
~1.3k tokens
SKILL.md length
630 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

Reviews code and plans against the project's coding rules. An agent skill from ntorga/agent-starter-kit.

  • Works in 5 steps: Initialize the progress file. Create… → Collect the applicable rules. Load all… → Walk the work against every rule and… → …
  • Tasks that involve Code quality
  • SKILL.md covers Purpose, Procedure and Guardrails
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Code Quality Review is an agent skill from ntorga/agent-starter-kit. Reviews code and plans against the project's coding rules.

Its SKILL.md is about 1.3k 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 Development, covering Code quality. The repository describes itself as: The scaffold for your multi-model, personalized Natural Language AI Harness (NLAH) . The licence is MIT.

When your agent uses it

  • Tasks that involve Code quality

Example prompts

  • “Use the code-quality-review skill to review code and plans against the project's coding rules. An agent skill from ntorga/agent-starter-kit”
  • “/code-quality-review”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Initialize the progress file. Create .memory/reviews/review-quality-.md
  2. Collect the applicable rules. Load all files from rules/code/. Also load any applicable rules (e.g., rules/git.md). Classify each rule's…
  3. Walk the work against every rule and classify findings. Check each statement in each loaded rule file against the changed code or plan. Do…
  4. Verify style proximity. For each changed file, run ls on its directory. Read one or two sibling files — pick those most similar in…
  5. Dedup findings. Review all findings in the progress file. If a style proximity finding overlaps with a rule-based finding (e.g., both…

What it can do on your machine

Read from SKILL.md and the folder at commit 851e942. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

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

  • Network

    No URLs in SKILL.md.

    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

Code Quality Review loads about 1.3k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 630 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

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 ntorga/agent-starter-kit at commit 851e942, republished under its MIT licence (© ntorga). 630 words, ~1,264 tokens.

Download SKILL.mdSave it as .claude/skills/code-quality-review/SKILL.md (or your agent's skills folder).
name
code-quality-review
description
Reviews code and plans against the project's coding rules.
usedBy
reviewer
version
0.3.0
lastUpdated
2026-09-12

Purpose

A code review without a checklist drifts toward gut feeling — the reviewer catches what they notice and misses what they don't. This skill turns the project's coding rules into a repeatable procedure. It tells the reviewer what to inspect and in what order.

Procedure

  1. Initialize the progress file. Create .memory/reviews/review-quality-<timestamp>.md:

    markdown
    # Quality Review Progress
    
    ## Status
    - Last updated: <timestamp>
    - Overall: In Progress
    
    ## Phases
    - [ ] 1. Collect applicable rules
    - [ ] 2. Walk work against rules
    - [ ] 3. Verify style proximity
    - [ ] 4. Dedup findings
    
    ## Files
    - [ ] <path>
    - [ ] <path>
    
    ## Findings
  2. Collect the applicable rules. Load all files from rules/code/. Also load any applicable rules (e.g., rules/git.md). Classify each rule's statements by RFC language:

    • MUST / MUST NOT / SHALL / SHALL NOT — violations are always Blockers. No exceptions.
    • SHOULD / SHOULD NOT — violations require justification visible in the code (a comment earned under rules/code/general.md § Comments, a design note, or a .context.md entry). If the justification is clear, it is a Warning. If absent or unclear, it is a Blocker.

    Language-to-severity mapping:

    • MUST violation → always Blocker.
    • SHOULD violation without visible justification → Blocker.
    • SHOULD violation with documented justification → Warning.

    If the codebase uses a specific language with a dedicated rule file, include that file. If the language has no dedicated file, apply only rules/code/general.md. One pass-routing exception — severity rules are unchanged: the behavior-over-implementation rule in rules/code/general.md § Testing is a test-proof question — hand it to the coherence pass per the Guardrails; do not classify it here.

    Mark phase 1 as [x] in the progress file.

  3. Walk the work against every rule and classify findings. Check each statement in each loaded rule file against the changed code or plan. Do not skip or paraphrase rules — the rules are the source of truth. Classify each issue found:

    • Blocker — MUST violation, unjustified SHOULD violation, readability violation (cryptic code is always a blocker). Must be fixed.
    • Warning — justified SHOULD deviation, minor inconsistency. Should be addressed.
    • Note — style suggestion beyond what rules mandate. No action required.

    After reviewing each changed file, update the progress file: mark the file as [x] with finding counts, add findings under ## Findings:

    ### <file-path>
    
    **Blockers:**
    - <file>:<line> — <what violates which rule>. (rule: <rule-file-name>)
    
    **Warnings:**
    - <file>:<line> — <what violates which rule>. (rule: <rule-file-name>)
    
    **Notes:**
    - <file>:<line> — <observation>

    Mark the file as reviewed. Move to the next file only after the progress file is saved. Mark phase 2 as [x] when all files are reviewed.

  4. Verify style proximity. For each changed file, run ls on its directory. Read one or two sibling files — pick those most similar in function to the changed code. Compare the changed code against the siblings. Flag any structural or pattern mismatch as a Warning. The Coder's self-review is not evidence — verify independently.

    Add style findings to the progress file under each file's section. Mark phase 3 as [x].

  5. Dedup findings. Review all findings in the progress file. If a style proximity finding overlaps with a rule-based finding (e.g., both caught the same naming issue — one as style mismatch, one as rule violation), keep the rule-based finding and remove the style duplicate. The rule finding has a specific rule reference; the style finding is redundant.

    Mark phase 4 as [x] and set Overall to Complete. If review is interrupted, the progress file shows which phases were completed.

Show full SKILL.md (146 more words)Show less

Guardrails

  • Never flag a SHOULD deviation as a blocker when justification is documented. SHOULD is guidance, not law — documented justification earns a warning, not a veto.
  • Never invent rules. If an issue does not trace back to a loaded rule file, it is a Note at most, not a Warning or Blocker.
  • If a pattern match is ambiguous, skip it rather than rationalizing it into a finding.
  • Never flag line length in template or markup files (templ, HTML, JSX, Vue SFCs, etc.). A single tag or attribute list often cannot be split without harming readability — the line-length rule exempts these. Apply the limit to surrounding logic code, not to the markup.
  • Never flag test proof issues — whether a test verifies behavior or skip markers. Those are coherence questions. Test style issues land here through the rules: naming, table-driven cases, setup placement, file independence mechanics (rules/code/general.md § Testing).

© ntorga, MIT. 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 skills/code-quality-review of ntorga/agent-starter-kit.

Open the folder on GitHubat commit 851e942

Compare with similar skills

Code Quality 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.

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Skill Doli Code ReviewDolibarr/dolibarr7.7k1 repos~1.1kAutomated safety check: PassMIT

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Categories

Questions about Code Quality Review

What does Code Quality Review do?

Reviews code and plans against the project's coding rules. An agent skill from ntorga/agent-starter-kit. Code Quality Review is an agent skill from ntorga/agent-starter-kit. Reviews code and plans against the project's coding rules.

When should I use Code Quality Review?

Code Quality Review fits situations like: tasks that involve Code quality.

How do I install Code Quality Review in Claude Code?

Run `npx skills add ntorga/agent-starter-kit --skill code-quality-review -a claude-code`. Or copy the skill folder (skills/code-quality-review in ntorga/agent-starter-kit) into .claude/skills/code-quality-review in your project. Claude Code loads it when a task matches its description.

How do I install Code Quality Review in Codex?

Run `npx skills add ntorga/agent-starter-kit --skill code-quality-review -a codex`. Or copy the skill folder (skills/code-quality-review in ntorga/agent-starter-kit) into .agents/skills/code-quality-review in your project. Codex loads it when a task matches its description.

Can I use Code Quality Review 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 ntorga/agent-starter-kit --skill code-quality-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/code-quality-review, .gemini/skills/code-quality-review, .github/skills/code-quality-review and .opencode/skills/code-quality-review in your project.

What does Code Quality Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Code Quality Review is instructions for the agent only.

Does Code Quality Review access the network?

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.

Is Code Quality Review 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 Code Quality Review use?

Code Quality Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code Quality Review use?

About 1.3k tokens (SKILL.md is roughly 5.1k 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 Code Quality Review?

Skills that share tags, products or a category with Code Quality Review: Install Anti-Slop Oxlint Rules (dmmulroy/anti-slop, 5.3k stars), WooCommerce Code Review (woocommerce/woocommerce, 11k stars), Systematic Code Refactoring (luongnv89/claude-howto, 42k stars) and Constraint-Driven Development (addyosmani/agent-skills, 103k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code Quality Review?

ntorga (a GitHub user) maintains it in ntorga/agent-starter-kit, which has 146 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on September 12, 2026.

Source: ntorga/agent-starter-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.