Agent skill

Comprehensive Review

by EliasOulkadi in EliasOulkadi/shokunin

Comprehensive code review using parallel specialized subagents.

MITAuto-check passedDevelopment

Install Comprehensive Review

skills CLI
$ npx skills add EliasOulkadi/shokunin --skill comprehensive-review -a claude-code

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

GitHub CLI
$ gh skill install EliasOulkadi/shokunin comprehensive-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/EliasOulkadi/shokunin.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.pack/skills/comprehensive-review .claude/skills/comprehensive-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
comprehensive-review
GitHub stars
114
Token cost
~4.8k tokens
SKILL.md length
2,175 words
Files
1
Skills in repo
49
Repo updated
First seen
Licence
MIT

At a glance

Comprehensive code review using parallel specialized subagents.

  • Works in 7 steps: Determine review mode → Fetch diff and task description via… → Run specialized reviews → …
  • Tasks that involve Subagents
  • SKILL.md covers Variables, Workflow, Error Handling and Anti-Patterns, plus 2 more sections
  • Calls gh; reaches github.com; needs GITHUB_TOKEN

What it does

Comprehensive Review is an agent skill from EliasOulkadi/shokunin. Comprehensive code review using parallel specialized subagents. If a PR URL is provided, fetches PR details and can post comments. If no PR is provided, reviews the diff between the current branch and its base branch plus any uncommitted changes. CRITICAL: this skill is costly, don't use it unless user explicitly requested to use it.

Its SKILL.md is about 4.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: opencode

It sits in Development, covering Subagents and Code review. The repository describes itself as: 職人 Shokunin 62 AI agent skills for OpenCode, Claude Code, Cursor, Windsurf. ChromaDB memory, MCP servers, declarative self-updates. Multi-model, open source, zero cost. The licence is MIT.

When your agent uses it

  • Tasks that involve Subagents
  • Tasks that involve Code review

Example prompts

  • “/comprehensive-review”

Requirements

  • Compatibility (from SKILL.md): opencode

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Determine review mode
  2. Fetch diff and task description via subagent
  3. Run specialized reviews
  4. Merge, filter, and prioritize results
  5. Ask user how to handle each finding
  6. Apply fixes for issues marked "Fix"
  7. Post selected issues as PR comments (PR mode only)

What it can do on your machine

Read from SKILL.md and the folder at commit 4c68e5b. 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

    Shell commands in SKILL.md call:

    • gh

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GITHUB_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    opencode

    From compatibility in the SKILL.md frontmatter.

Context cost

Comprehensive Review loads about 4.8k tokens when it runs. Until then it costs about 89 tokens; SKILL.md has 2,175 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~89
When it runs · the whole SKILL.md, loaded when a task matches
~4.8k

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 EliasOulkadi/shokunin at commit 4c68e5b, republished under its MIT licence (© EliasOulkadi). 2,175 words, ~4,818 tokens.

Download SKILL.mdSave it as .claude/skills/comprehensive-review/SKILL.md (or your agent's skills folder).
name
comprehensive-review
description
Comprehensive code review using parallel specialized subagents. If a PR URL is provided, fetches PR details and can post comments. If no PR is provided, reviews the diff between the current branch and its base branch plus any uncommitted changes. CRITICAL: this skill is costly, don't use it unless user explicitly requested to use it.
compatibility
opencode
triggers
comprehensive review, full code review, deep code review, thorough review, complete review, review everything
negatives
quick review, simple review, design review, UI review
license
MIT
metadata.version
2.1.0
metadata.workflow
quality
metadata.audience
developers

Comprehensive Code Review

Run parallel specialized code reviews via subagents, covering architecture, security, performance, code quality, requirements compliance, and bugs. Merge findings and let the user act on them. Works with both GitHub PRs and local branch diffs.

Variables

  • {TEMP_DIR} — the OS temporary directory (e.g. /tmp on Unix, %TEMP% on Windows). Use it for all intermediate files.

Workflow

Step 1: Determine review mode

Check if the user provided a GitHub PR link.

  • PR mode: A PR URL is provided matching https://github.com/<OWNER>/<REPO>/pull/<PR_NUMBER>. Extract owner, repo, and PR number.
  • Local mode: No PR URL provided. The review will be based on the diff between the current branch and its base branch, plus any uncommitted changes.
Step 2: Fetch diff and task description via subagent

Call a subagent to gather all change details, save the diff, and checkout the correct branch.

CRITICAL: You MUST spawn a subagent for this step. Do NOT perform the diff-gathering, branch detection, or complexity assessment yourself.

Construct the subagent prompt as follows:

Gather the code change details for a comprehensive code review.

Mode: <PR mode or Local mode>
<If PR mode: Owner: <OWNER>, Repo: <REPO>, PR Number: <PR_NUMBER>>

Instructions:
- PR mode: Fetch PR details via GitHub API (title, description, diff). Use `gh pr view <PR_NUMBER> --repo <OWNER>/<REPO> --json title,body` for metadata and `gh pr diff <PR_NUMBER> --repo <OWNER>/<REPO>` for the diff. Save diff to {TEMP_DIR}/review-diff-<branch>.patch.
- Local mode: Detect the current branch and its base branch (try main, master, develop). Use `git diff <base>...HEAD` for committed changes and `git diff` for uncommitted changes. Combine into {TEMP_DIR}/review-diff-<branch>.patch.
- Determine complexity: simple (<200 diff lines, single file/module), medium (200-800 lines, 2-5 files), hard (>800 lines, 6+ files, or touches architecture).
- Return: diff file path, diff line count, title, comprehensive task description, and complexity assessment.

Use a subagent tool to spawn the subagent. Use a powerful model since this involves complex reasoning to assess complexity.

The subagent will return:

  • Diff file path: absolute path to the saved diff file (must start with /, e.g. {TEMP_DIR}/review-diff-feature.patch)
  • Diff line count: total number of lines in the diff file
  • Title: the PR title or summary from commits
  • Description: comprehensive task description with all requirements
  • Complexity: one of simple, medium, or hard

Remember these values for use in subsequent steps.

Step 3: Run specialized reviews

The review strategy depends on the complexity returned by the fetch-diff subagent.

Review Criteria

Each subagent reviews the diff through one specialized lens:

CriterionWhat to review
architectureModule boundaries, dependency direction, design patterns, SOLID principles, separation of concerns, circular dependencies, appropriate abstraction levels
securityOWASP Top 10, input validation, authentication/authorization, secret handling, injection risks, insecure deserialization, logging of sensitive data
performanceN+1 queries, unnecessary allocations, blocking operations, missing indexes, bundle size impact, render-blocking resources, memory leaks
code-qualityReadability, naming conventions, function length, error handling patterns, type safety, testability, consistent coding style
requirements-complianceDoes the change satisfy the stated task requirements? Are edge cases covered? Does it handle all user stories? Are acceptance criteria met?
bugsLogic errors, off-by-one, null/undefined handling, race conditions, incorrect state transitions, missing error handling, incorrect assumptions

Note: This skill is self-contained. Referenced files (criteria/*.md, fetch-diff.md, scripts/post_review.js) are placeholders for future expansion. All review instructions and criteria are defined inline above.

Strategy A: Simple complexity

For simple PRs, perform the review yourself (the root agent) without calling subagents.

  1. Read the Review Criteria table above to understand each review lens.
  2. Read the diff file.
  3. Apply all criteria to review the change yourself, producing findings as a flat list without priorities (same format as subagents would). You will assign priorities in Step 4.
Strategy B: Medium complexity

For medium PRs, launch 6 parallel subagent calls — one per review criterion.

CRITICAL: You MUST spawn subagents for this step. Do NOT perform the reviews yourself.

Use a subagent tool to spawn each subagent. Select the single most powerful model from each available provider. Alternate these models across the 6 criteria (e.g., provider A's best model for criteria 1, 3, 5 and provider B's best model for criteria 2, 4, 6). If only 1 provider is available, use its most powerful model for all 6.

Construct prompts for subagents as follows:

Review the following change through the {criterion} lens. Apply the criteria defined in the Review Criteria table for this category.

## <title>

### Task Description
<task description>

### Diff
Read the diff from file: <absolute path to diff file> (total lines: <diff line count>)

IMPORTANT: Do NOT invoke the Skill tool. Do NOT run tests, builds, linters, or type-checks — your review is based on static analysis only.
Strategy C: Hard complexity

For hard PRs, launch 2 parallel subagent calls per criterion (12 total) — one per criterion per model, using 2 different models from different providers for diverse perspectives.

CRITICAL: You MUST spawn subagents for this step. Do NOT perform the reviews yourself.

Model selection: Choose exactly 2 models — the single most powerful model from each of 2 different providers. If only 1 provider is available, use its most powerful model for all 12 calls (fall back to Strategy B behavior with 2 calls per criterion).

Use a subagent tool to spawn each subagent.

For each of the 6 criteria, launch 2 subagents — one with each model. Use following prompt:

Review the following change through the {criterion} lens. Apply the criteria defined in the Review Criteria table for this category.

## <title>

### Task Description
<task description>

### Diff
Read the diff from file: <absolute path to diff file> (total lines: <diff line count>)

IMPORTANT: Do NOT invoke the Skill tool. Do NOT run tests, builds, linters, or type-checks — your review is based on static analysis only.

All 12 calls should be launched in parallel.

Step 4: Merge, filter, and prioritize results

Subagents return findings as flat lists without priority or severity labels. The root agent is responsible for deduplication, false-positive filtering, and priority assignment.

4a. Collect and deduplicate
  1. Collect all findings from each review (self-review or subagent responses).
  2. Group findings by file and line number.
  3. Merge issues that describe the same problem (same file, similar line range, same category). When merging, combine their review types. For hard PRs, findings from different models on the same criterion that agree strengthen confidence; findings from only one model should be noted as lower confidence.
  4. Keep the best description, suggested fix, and Diff line from among duplicates. Track Diff line values internally for use in Step 7 but do NOT include them in the output shown to the user.
4b. Filter false positives

Review each finding and discard it if:

  • The subagent itself expressed doubt about whether it's a real issue.
  • You can verify from the code context that the issue does not apply (e.g., the code is already protected by a guard the subagent missed, or the flagged pattern is intentional and correct).
  • The finding is about a pre-existing issue not introduced by the change.

Be conservative — when in doubt, keep the finding.

4c. Assign priorities

Assign a priority to each remaining finding using these levels:

PriorityMeaningAction
P0Critical — blocks merge, causes crashes/data loss/security breachMust fix before merge
P1Major — significant issue affecting correctness, security, or maintainabilityMust fix
P2Minor — real issue but low impact, improvement opportunityNice to fix
P3Suggestion — nitpick, style preference, optional enhancementOptional

When assigning priorities, consider:

  • Cross-criteria signal: A finding flagged by multiple criteria (e.g., both architecture and security) is likely more important.
  • Blast radius: Issues affecting hot paths, public APIs, or security boundaries deserve higher priority.
  • Confidence: Findings confirmed by multiple models (hard PRs) or backed by concrete evidence deserve higher priority than speculative ones.
  • Context: The same issue type may deserve different priorities depending on the codebase and change context.
4d. Format output

Sort by priority (P0 first), then by file path. Each finding must be a standalone entry — do NOT bundle multiple distinct issues into a single row even if they are related.

## Comprehensive Review Findings

| # | Priority | Issue | File:Line | Review type |
|---|----------|-------|-----------|------------|
| 1 | P0 | Description | link to specific line in file | architecture(opus-4-6-think), security(gpt-5-3-codex) |
| 2 | P1 | Description | link to specific line in file | bugs(opus-4-6-think) |
| ... | | | | |

### Details

#### 1. [P0] Issue title
**File:** link to specific line in file
**Review type:** architecture(opus-4-6-think), security(gpt-5-3-codex)

Description and why it matters.

**Suggested fix:**
\`\`\`
code
\`\`\`
Step 5: Ask user how to handle each finding

Skip this step if the user already specified what to do with findings in their initial prompt (e.g., "fix all issues", "post comments for all P0s", etc.). In that case, proceed directly to Steps 6/7 based on their instructions.

Otherwise, send a single message asking the user which findings to fix or post as comments. List each finding with its number, priority, and short description, and ask the user to reply with their choices.

  • PR mode: Ask which issues to fix and which to post as PR comments.
  • Local mode: Only ask which issues to fix. Do NOT mention posting comments.
Step 6: Apply fixes for issues marked "Fix"

For each finding the user chose "Fix":

  1. Read the relevant file and understand the surrounding context.
  2. Apply the suggested fix (or an appropriate fix if the suggestion is incomplete).
  3. After all fixes are applied, present a summary of changes made.
Step 7: Post selected issues as PR comments (PR mode only)

Skip this step entirely if no findings were marked "Post comment".

Only applies in PR mode. Post line-specific comments via the GitHub API.

Show full SKILL.md (925 more words)Show less
7a. Build the review payload JSON

Construct a JSON object with this structure:

json
{
  "event": "COMMENT",
  "body": "## Comprehensive Code Review\n\n### Findings Summary\n\n| Priority | Issue | Location | Review type |\n|----------|-------|----------|------------|\n| P0 | Issue title | `path/to/file.ts:42` | code-quality(gpt-5-3-codex) |\n\n### Recommendation\n[Concise recommendation]",
  "comments": [
    {
      "path": "path/to/file.ts",
      "line": 42,
      "side": "RIGHT",
      "body": "**[P0] Issue Title** (review type: code-quality(gpt-5-3-codex))\n\nDescription.\n\n**Suggested fix:**\n```\ncode\n```"
    }
  ]
}

For each finding marked "Post comment":

  • path: the file path relative to repo root
  • line: the line number for the comment. For RIGHT side, this is the new-file line number (from +new_start,new_count hunk range). For LEFT side, this is the old-file line number (from -old_start,old_count hunk range). Use the Diff line value from the findings table when the finding targets new/modified code. For findings targeting deleted code, use the old-file line number from the --side of the diff hunk
  • side: RIGHT for new/modified code, LEFT for deleted code. Use LEFT only when commenting on lines that were removed (shown with - prefix in the diff)
  • body: include priority, title, review type with model name, description, and suggested fix
  • Each finding gets its own comment — do NOT merge multiple findings into one comment

If user added custom notes to a finding, update description and/or suggested fix according to these notes.

Save the JSON to a file named {TEMP_DIR}/review_payload-<branch-name>.json.

7b. Post via the script

Post each comment via the GitHub API using gh api:

bash
gh api repos/<OWNER>/<REPO>/pulls/<PR_NUMBER>/reviews --method POST -F "commit_id=$(gh pr view <PR_NUMBER> --repo <OWNER>/<REPO> --json headRefOid --jq .headRefOid)" -F "event=COMMENT" -F "body=<review-body>" -F "comments=<comments-json>"

Validate comment line numbers against the diff before posting. Adjust line numbers to the nearest valid diff line when close, and move out-of-range comments to the review body.

Error Handling

CauseFix
Subagent fails to spawn (timeout, model unavailable, API error)Retry with a different model from another provider. If all models fail, fall back to Strategy A (root agent reviews all 6 criteria) and note reduced coverage in output
Diff file is empty or contains only binary/image changesReport to user: "No reviewable text changes found." Skip subagents entirely. Do not force a review on empty or binary-only diffs
Fetch-diff subagent cannot determine base branch for local modeTry main first, then master, then develop. If none exist, report error to user with the branches found and ask them to specify the base
Subagent returns findings without file:line referencesRe-run that specific subagent with explicit instruction: "You MUST include file path and line number for every finding. Findings without location context cannot be used."
PR posting script fails with GitHub API authentication error (401/403)Verify GITHUB_TOKEN env var is set with repo scope. For private repos, use a Personal Access Token with full repo access. Check token hasn't expired
Duplicate findings from parallel subagents cannot be auto-merged with confidenceFlag to user: "N findings reduced to M unique after deduplication. Manual review recommended for findings where subagents disagreed on severity or scope"
Diff exceeds 10,000 lines (hard complexity) — reviews take too longWarn user before proceeding: "Diff is very large (N lines). Review quality decreases with size. Consider splitting into smaller PRs. Continue anyway?"
Posted PR comment line number doesn't match any diff hunk exactlyAuto-adjust to nearest valid line. If adjustment fails (line too far from any hunk), comment moves to review body instead

Anti-Patterns

PatternProblemFix
Reviewing without reading the task description or PR bodyMisses context on intent. Flags intentional design decisions as bugs. Reviewer and author talk past each otherAlways read task description first. Compare diff against stated requirements, not reviewer's assumptions
Nitpicking formatting, naming, and style onlyMisses logic errors, security holes, and performance regressions. Creates false sense of thoroughness while letting real bugs throughLinting/formatting handled by CI. Review focuses on correctness, security, performance, architecture. Style comments are P3 at most
Requesting changes without suggesting alternative approachBlocks contributor who then has to schedule another round-trip to discuss. Slows velocityEvery P0/P1 finding includes a concrete suggested fix or at minimum a direction. Reviewer invests time in solutions, not just problem-spotting
Rubber-stamping PRs from senior team members or frequent collaboratorsAuthority bias. Senior engineers make mistakes. Most post-mortems trace to "reviewed by peer who trusted author's experience"Apply identical review criteria regardless of author seniority. If too busy, don't approve — ask another reviewer
Reviewing only the diff in isolation, not the integration surfaceChange correct in isolation but breaks when composed with other recent changes or crosses module boundariesCheck out branch locally. Run full test suite. Grep for callers of modified functions. Check for merge conflicts and cross-module interactions
Blocking merge on P3 nits and stylistic preferencesSlows velocity without quality gain. Contributor spends time on changes that don't reduce bugs or improve performanceP3 = approve with optional suggestions. "Request changes" only for P0 and P1. Trust the contributor to decide on style preferences
Posting dozens of PR comments without prioritizationOverwhelms the author. They can't distinguish critical from cosmeticGroup and prioritize before posting. Top comment should summarize: X critical, Y major, Z minor. Critical issues get individual comments; minor issues can be batched in summary
Using review as a gatekeeping or knowledge-hoarding mechanismDeliberately slow reviews to maintain information asymmetry. Toxic to team cultureSet SLA: review within 4 business hours. If blocked waiting for domain expert, note it and unblock with partial review

Checklist

  • Diff fetched from correct base branch
  • All related changes included (no partial diffs)
  • Each subagent model confirmed available before dispatch
  • Critical (P0) and High (P1) findings clearly separated from suggestions
  • False positives reviewed before presenting final report

Sources

  • Google Engineering Practices — Code Review Developer Guide (google.github.io/eng-practices/review)
  • Microsoft Code With Engineering Playbook — Code Reviews (microsoft.github.io/code-with-engineering-playbook)
  • Palantir — Code Review Best Practices (blog.palantir.com)
  • SmartBear — Best Practices for Peer Code Review (smartbear.com)
  • "Modern Code Review: A Case Study at Microsoft" — Bacchelli & Bird, 2013 (ACM)
  • "Expectations, Outcomes, and Challenges of Modern Code Review" — Microsoft Research (2013)
  • GitHub Docs — About Pull Request Reviews (docs.github.com)
  • Google SRE Workbook — Change Management chapter

© EliasOulkadi, 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 .pack/skills/comprehensive-review of EliasOulkadi/shokunin.

Open the folder on GitHubat commit 4c68e5b

Compare with similar skills

Comprehensive 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.

Comprehensive Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Comprehensive Review this skillEliasOulkadi/shokunin114—~4.8kAutomated safety check: PassMIT
GitHub Review Iterationprisma/orm48k—~2.2kAutomated safety check: PassApache-2.0
Cherry Studio PR ReviewCherryHQ/cherry-studio53k—~3.9kAutomated safety check: PassAGPL-3.0
PR Reviewjaemk/self_update961—~1.5kAutomated safety check: NotesMIT
Cursor Composer Task DelegateChachamaru127/claude-code-harness3.2k—~4.4kAutomated safety check: NotesMIT
Local PR Reviewwindmill-labs/windmill18k—~995Automated safety check: PassCustom licence

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Questions about Comprehensive Review

What does Comprehensive Review do?

Comprehensive code review using parallel specialized subagents. Comprehensive Review is an agent skill from EliasOulkadi/shokunin. Comprehensive code review using parallel specialized subagents.

When should I use Comprehensive Review?

Comprehensive Review fits situations like: tasks that involve Subagents; tasks that involve Code review.

How do I install Comprehensive Review in Claude Code?

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

How do I install Comprehensive Review in Codex?

Run `npx skills add EliasOulkadi/shokunin --skill comprehensive-review -a codex`. Or copy the skill folder (.pack/skills/comprehensive-review in EliasOulkadi/shokunin) into .agents/skills/comprehensive-review in your project. Codex loads it when a task matches its description.

Can I use Comprehensive 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 EliasOulkadi/shokunin --skill comprehensive-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/comprehensive-review, .gemini/skills/comprehensive-review, .github/skills/comprehensive-review and .opencode/skills/comprehensive-review in your project.

What does Comprehensive Review need to run?

Going by SKILL.md and its folder, Comprehensive Review needs the command-line tools its instructions call (gh) and credentials named GITHUB_TOKEN. Compatibility (from SKILL.md): opencode.

Does Comprehensive Review access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Comprehensive 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 Comprehensive Review use?

Comprehensive 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 Comprehensive Review use?

About 4.8k tokens (SKILL.md is roughly 19k 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 Comprehensive Review?

Skills that share tags, products or a category with Comprehensive Review: GitHub Review Iteration (prisma/orm, 48k stars), Cherry Studio PR Review (CherryHQ/cherry-studio, 53k stars), PR Review (jaemk/self_update, 961 stars) and Cursor Composer Task Delegate (Chachamaru127/claude-code-harness, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Comprehensive Review?

EliasOulkadi (a GitHub user) maintains it in EliasOulkadi/shokunin, which has 114 GitHub stars. The repository holds 49 skills in this directory. The repository was last updated on October 5, 2026.

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