Converts a markdown PR writeup or code review (one with diff fenced blocks and severity-tagged [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT] callouts) into a single-file 2-column HTML review — unified-diff on…

MITAuto-check passedFrontend & Design

Install Md Review

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill md-review -a claude-code

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

GitHub CLI
$ gh skill install alirezarezvani/claude-skills md-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/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/markdown-html/skills/md-review .claude/skills/md-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
md-review
GitHub stars
28k
Token cost
~1.6k tokens
SKILL.md length
584 words
Files
8 (incl. scripts, references, assets)
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

Converts a markdown PR writeup or code review (one with diff fenced blocks and severity-tagged [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT] callouts) into a single-file 2-column HTML review — unified-diff on…

  • Works in 7 steps: reviewer is mandatory. A code review… → Refuses if no hunks present. No ---… → Refuses input < 100 lines. Markdown wins… → …
  • The markdown-html-orchestrator classifies an input as REVIEW
  • SKILL.md covers When to invoke, Pipeline, What gets rendered and Hard rules, plus 4 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Md Review is an agent skill from alirezarezvani/claude-skills. Converts a markdown PR writeup or code review (one with diff fenced blocks and severity-tagged [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT] callouts) into a single-file 2-column HTML review — unified-diff on the left, severity-tagged annotation cards on the right, top jump-nav listing every finding, mandatory named reviewer footer. Triggers when the markdown-html-orchestrator classifies an input as REVIEW, or when invoked directly via /cs:md-review. Refuses without explicit --reviewer (a code review must name a human)…

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `references/diff_rendering_canon.md`, `references/pr_annotation_ux.md` and `references/severity_coding.md`).

It sits in Frontend & Design, covering Accessibility, Code review and Markdown. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • The markdown-html-orchestrator classifies an input as REVIEW
  • Invoked directly via /cs:md-review

Example prompts

  • “Use the md-review skill to convert a markdown PR writeup or code review (one with diff fenced blocks and severity-tagged…”
  • “/md-review”

Requirements

  • Python 3

Workflow steps

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

  1. reviewer is mandatory. A code review must name a human reviewer. Refuses with exit 3 otherwise. Mirrors research-ops's "named owner"…
  2. Refuses if no hunks present. No --- a/file + @@ ... @@ blocks means this isn't a code review — refuses with exit 4 and recommends…
  3. Refuses input < 100 lines. Markdown wins below the threshold (Shihipar).
  4. Refuses without onboarding. Same gate as every converter.
  5. Severity is never color-only. Each badge ships color + icon + aria-label + text. WCAG 1.4.1 enforced at the renderer level.
  6. Single-file output. All CSS inline. Only external is Google Fonts CSS. No Prism in md-review (diff coloring conflicts with syntax…
  7. Custom severity convention. --severity-convention "critical,important,suggestion,nit" swaps tier names; position 0 is most severe. Default…

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. 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

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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

Md Review loads about 1.6k tokens when it runs, and up to ~5.5k if it reads all its reference files. Until then it costs about 184 tokens; SKILL.md has 584 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~184
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.5k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 584 words, ~1,619 tokens.

Download SKILL.mdSave it as .claude/skills/md-review/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
md-review
description
Converts a markdown PR writeup or code review (one with ```diff fenced blocks and severity-tagged > [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT] callouts) into a single-file 2-column HTML review — unified-diff on the left, severity-tagged annotation cards on the right, top jump-nav listing every finding, mandatory named reviewer footer. Triggers when the markdown-html-orchestrator classifies an input as REVIEW, or when invoked directly via /cs:md-review. Refuses without explicit --reviewer (a code review must name a human), refuses if no diff hunks present (route to md-document instead), and refuses to encode severity in color only (every badge ships color + icon + aria-label per WCAG 1.4.1). Use after orchestrator routing.
version
2.10.2
author
Alireza Rezvani
license
MIT
tags
markdown, html, code-review, diff, severity, annotations, single-file, design-system, wcag-1.4.1
compatible_tools
claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli

md-review — Code-review markdown → 2-column HTML

The code-review converter from Tier 2 of Shihipar's essay ("Code Review and PR Writeups"). Takes a markdown PR writeup with diff blocks + severity callouts and produces a single-file HTML review with a jump-nav, 2-column diff + annotation layout, and a named reviewer footer.

Three stdlib tools pipeline together:

diff_parser.py  →  annotation_extractor.py  →  review_html_renderer.py
   (md → diff hunks)   (md → severity-tagged    (hunks + annotations
                        annotations attached     + tokens → 2-col HTML)
                        to nearest hunk)

When to invoke

SymptomAction
markdown-html-orchestrator routes input as REVIEWInvoke this skill
User runs /cs:md-review <path>.md directlyInvoke this skill
Input contains ```diff fenced blocks + > [!MAJOR]/> [!BLOCKER]/etc. calloutsInvoke this skill
Input is a long-form spec / report (no diff blocks)Route to md-document instead
Input is a slide deckRoute to md-slides instead
Input < 100 linesRefuse (Shihipar threshold)
Design-system not onboardedRefuse; surface /cs:design-system

Pipeline

bash
# 1. Parse markdown → diff hunks JSON
python3 markdown-html/skills/md-review/scripts/diff_parser.py \
    --input <path>.md --output hunks.json

# 2. Extract severity-tagged annotations, attach to nearest preceding hunk
python3 markdown-html/skills/md-review/scripts/annotation_extractor.py \
    --input <path>.md --diff-blocks hunks.json --output annotations.json

# 3. Render 2-col HTML (--reviewer is mandatory — refuses without)
python3 markdown-html/skills/md-review/scripts/review_html_renderer.py \
    --diff-blocks hunks.json --annotations annotations.json \
    --reviewer "Jane Doe" --title "PR #123: Add retry logic" \
    --output review.html

What gets rendered

  • Top jump-nav — every annotation with severity badge + 80-char preview + jump link; severity counts in the heading ("3 BLOCKER · 2 MAJOR · 1 NIT")
  • 2-column hunk rows — unified diff on the left (per-line old/new line numbers, +/− marks, addition/deletion background tint from design-system tokens), annotation cards on the right (color + icon + aria-label per WCAG 1.4.1)
  • Approval bar — if LGTM markers are present and no severity annotations, a success-tinted "LGTM — no findings flagged" bar
  • General comments — annotations not attached to any hunk render at the bottom in their own section
  • Reviewer footer — mandatory; refuses to render without --reviewer
  • Responsive — 2-col collapses to stacked on viewports < 900px

Hard rules

  1. --reviewer is mandatory. A code review must name a human reviewer. Refuses with exit 3 otherwise. Mirrors research-ops's "named owner" discipline.
  2. Refuses if no hunks present. No --- a/file + @@ ... @@ blocks means this isn't a code review — refuses with exit 4 and recommends md-document.
  3. Refuses input < 100 lines. Markdown wins below the threshold (Shihipar).
  4. Refuses without onboarding. Same gate as every converter.
  5. Severity is never color-only. Each badge ships color + icon + aria-label + text. WCAG 1.4.1 enforced at the renderer level.
  6. Single-file output. All CSS inline. Only external is Google Fonts CSS. No Prism in md-review (diff coloring conflicts with syntax highlighting).
  7. Custom severity convention. --severity-convention "critical,important,suggestion,nit" swaps tier names; position 0 is most severe. Default is BLOCKER / MAJOR / MINOR / NIT (Google Code Review Developer Guide).
Show full SKILL.md (228 more words)Show less

Forcing-question library (Matt Pocock grill discipline)

  1. Who is the named reviewer? Recommended: the user signing off on the review. Canon: research-ops named-owner pattern; SWE at Google ch. 9.
  2. Which severity convention applies — default (BLOCKER/MAJOR/MINOR/NIT) or custom? Recommended: default unless your team has a documented alternative. Canon: Google Code Review Developer Guide.
  3. Are annotations anchored to specific hunks, or are some general? Recommended: anchor everything you can; general goes to the unanchored section. Canon: SWE at Google ch. 9 — "Comments must reference a specific line".
  4. What's the PR title for the <title> and header? Recommended: the actual PR / commit title. Canon: docs-as-context-for-readers.
  5. Should LGTM markers ship as the approval bar? Recommended: yes if there are no severity annotations; otherwise the findings take precedence.

Distinct from

  • md-document — that converter renders prose + tables + code + callouts. This one renders diff hunks + margin annotations.
  • md-slides — that converter splits on --- boundaries. This one is a single-page artifact.
  • GitHub PR comments — those are a thread. This is a single-author snapshot artifact.

Output artifact

{default_output_dir}/review-{slug}.html (path resolved by orchestrator's output_path_resolver.py; collision suffix -2, -3, … by default).

References

  • Shihipar — Claude Code HTML output (Medium, 2026), Tier 2 use case
  • Software Engineering at Google (Manshreck & Wright, O'Reilly 2020), ch. 9 "Code Review"
  • Google Code Review Developer Guide — severity convention source
  • WCAG 2.2 §1.4.1 — color-not-sole-signal enforcement
  • See references/ for full citations (diff_rendering_canon, severity_coding, pr_annotation_ux)

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

Files

SKILL.md and 7 other files (scripts, references, assets) in markdown-html/skills/md-review of alirezarezvani/claude-skills.

  • SKILL.md
  • assets/md_review_template.html
  • references/diff_rendering_canon.md
  • references/pr_annotation_ux.md
  • references/severity_coding.md
  • scripts/annotation_extractor.py
  • scripts/diff_parser.py
  • scripts/review_html_renderer.py

Open the folder on GitHubat commit 19392f7

Compare with similar skills

Md 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.

Md Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Md Review this skillalirezarezvani/claude-skills28k—~1.6kAutomated safety check: PassMIT
React Code Reviewgiuseppe-trisciuoglio/developer-kit357—~2.6kAutomated safety check: NotesMIT
Blog ChartAgriciDaniel/claude-blog2.3k—~2.4kAutomated safety check: PassMIT
React Component Documentationgetsentry/sentry46k—~3.6kAutomated safety check: PassCustom licence
Md Reviewborghei/Claude-Skills891—~3.8kAutomated safety check: PassMIT
Markdown A11y AssistantCommunity-Access/accessibility-agents423—~932Automated safety check: PassMIT

Similar skills

  • React Code Review

    giuseppe-trisciuoglio/developer-kit

    Provides comprehensive code review capability for React applications, validates component architecture, hooks usage, React 19 patterns, state management, performance optimization, accessibility…

    357 GitHub stars~2.6k tokensUpdated 1 mo ago
    Frontend & DesignAuto-check: notes
  • Blog Chart

    AgriciDaniel/claude-blog

    Generate dark-mode-compatible inline SVG data visualization charts for blog posts.

    2.3k GitHub stars~2.4k tokensUpdated yesterday
    Frontend & DesignAuto-check passed
  • Official

    Create or update component documentation in Sentry's MDX stories format.

    46k GitHub stars~3.6k tokensUpdated today
    Frontend & DesignAuto-check passed
  • Md Review

    borghei/Claude-Skills

    Pre-publication quality gate for authored Markdown — heading structure, on-disk link resolution, readability, accessibility, terminology.

    891 GitHub stars~3.8k tokensUpdated 3 days ago
    Frontend & DesignAuto-check passed
  • Markdown A11y Assistant

    Community-Access/accessibility-agents

    Guided WCAG audit of markdown docs: link text, alt text, heading order, tables, emoji, diagrams and anchors.

    423 GitHub stars~932 tokensUpdated 16 days ago
    Frontend & DesignAuto-check passed
  • Markdown Scanner

    Community-Access/accessibility-agents

    Internal helper: scan one markdown file across all nine domains.

    423 GitHub stars~1.6k tokensUpdated 16 days ago
    Frontend & DesignAuto-check passed

More from alirezarezvani/claude-skills

All 342 skills in this repo
  • Agile Product Owner

    alirezarezvani/claude-skills

    Writes INVEST-checked user stories with acceptance criteria, splits epics, plans sprints from velocity and ranks the backlog with a weighted score.

    28k GitHub starsUsed in 3 repos~3.2k tokens
    Auto-check passed
  • Product Strategist

    alirezarezvani/claude-skills

    OKR cascade toolkit for product leaders: generates aligned company-to-team OKRs from five strategy types and scores how well they line up.

    28k GitHub starsUsed in 2 repos~1.8k tokens
    Auto-check passed
  • App Store Optimization

    alirezarezvani/claude-skills

    App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store.

    28k GitHub starsUsed in 1 repo~4.2k tokens
    Auto-check passed
  • AWS Solution Architect

    alirezarezvani/claude-skills

    Design AWS architectures for startups using serverless patterns and IaC templates.

    28k GitHub starsUsed in 1 repo~2.5k tokens
    Auto-check passed
  • Campaign Analytics

    alirezarezvani/claude-skills

    Calculates attribution, funnel and ROI figures for marketing campaigns with three Python scripts that need only the standard library.

    28k GitHub starsUsed in 1 repo~2.1k tokens
    Auto-check passed
  • Code to PRD

    alirezarezvani/claude-skills

    Reverse-engineers a frontend, backend or fullstack codebase into a product requirements document with per-page docs, an enum dictionary and an API inventory.

    28k GitHub starsUsed in 1 repo~4.9k tokens
    Auto-check passed

Questions about Md Review

What does Md Review do?

Converts a markdown PR writeup or code review (one with diff fenced blocks and severity-tagged [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT] callouts) into a single-file 2-column HTML review — unified-diff on…. Md Review is an agent skill from alirezarezvani/claude-skills.NIT] callouts) into a single-file 2-column HTML review — unified-diff on the left, severity-tagged annotation cards on the right, top jump-nav listing every finding, mandatory named reviewer footer.

When should I use Md Review?

Md Review fits situations like: the markdown-html-orchestrator classifies an input as REVIEW; invoked directly via /cs:md-review.

How do I install Md Review in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill md-review -a claude-code`. Or copy the skill folder (markdown-html/skills/md-review in alirezarezvani/claude-skills) into .claude/skills/md-review in your project. Claude Code loads it when a task matches its description.

How do I install Md Review in Codex?

Run `npx skills add alirezarezvani/claude-skills --skill md-review -a codex`. Or copy the skill folder (markdown-html/skills/md-review in alirezarezvani/claude-skills) into .agents/skills/md-review in your project. Codex loads it when a task matches its description.

Can I use Md 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 alirezarezvani/claude-skills --skill md-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/md-review, .gemini/skills/md-review, .github/skills/md-review and .opencode/skills/md-review in your project.

What does Md Review need to run?

Going by SKILL.md and its folder, Md Review needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Md 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 Md 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Md Review use?

Md Review is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Md Review use?

About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.9k tokens, read only when the agent opens those files.

What are the alternatives to Md Review?

Skills that share tags, products or a category with Md Review: React Code Review (giuseppe-trisciuoglio/developer-kit, 357 stars), Blog Chart (AgriciDaniel/claude-blog, 2.3k stars), React Component Documentation (getsentry/sentry, 46k stars) and Md Review (borghei/Claude-Skills, 891 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Md Review?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,938 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

Source: alirezarezvani/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.