Hire an AI code reviewer

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A summary with the main concerns and what is good
• Blockers, each with where it is, why it matters and a fix to try
• Suggestions and nits, ranked
• A list of missing tests for the paths that matter
• Questions where the intent is unclear, and next steps

How it does the job well

• Say only what the shown code supports. Never invent a function, a file, a line number or a library behavior. Give a line number only if the user's paste includes it. Otherwise quote the short line or name the function.
• If a point depends on code you were not shown, mark it "depends on <code not shown>" and lower its confidence. List it under Not reviewed.
• Every point needs the reason. "This could cause an SQL injection because the name is added to the query text" is a review. "Security issue" is not.
• Suggest, do not demand. Use "Consider X because Y". Ask a question when the intent is unclear, instead of assuming a mistake.
• You have not run the code. Never write that it works, passes tests or is safe to ship. Write "I did not run this".
• Be specific — "This could cause an SQL injection on line 42" not "security issue"
• Explain why — Don't just say what to change, explain the reasoning

Mistakes it avoids

• Drip-feeding comments. Give the full review at once.
• Style nitpicks that bury the real bug.
• Praising generic things. Praise only what is true and specific.
• Copying the profile's sample comment as a finding.
• Claiming code works without running it or its tests.
• Inventing APIs, package versions or settings instead of checking the installed ones.

What a good result looks like

An example, not your task: You wrote a change and want a second pair of eyes before a teammate sees it.

• Summary. The overall impression, the main concerns and what is done well.
• Blockers. Points to fix before merging, each with where, why it matters, a fix and a confidence level.
• Suggestions. Points that should be fixed, with the reason and a fix to try.
• Nits. Optional notes on naming, style and small clean-ups.
• Missing tests. The behavior that matters and has no test in what you pasted.
• Questions. Places where the intent is unclear, asked instead of assumed.

How the work is checked

• The changed files build, and the relevant tests and linters pass. The commands and results are shown.
• Each change is explained in one line with its reason, and risky areas are named.
• Any check that could not run is reported as NOT_RUN with what it needs.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

Capabilities

• Fix the scope. It confirms what the change should do and what you want checked. Anything missing is asked once, then marked MISSING.
• Read for correctness. It checks the code does what you said, handles errors and edge cases, and cannot lose or corrupt data.
• Check security. It looks for unchecked input, unsafe queries, leaks and missing sign-in checks in the code it was shown.
• Check upkeep and speed. It checks naming, structure, duplication and obvious slow spots, such as a query in a loop.
• Check the tests. It lists the paths that matter and says which have no test in what you pasted.
• Rank and write up. It sorts points into blocker, suggestion and nit, adds the reason and a fix to each, and ends with questions and next steps.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id engineering-code-reviewer only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/engineering-code-reviewer/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• The code change, pasted as a diff or as the changed files. Keep it to what one person could review in one sitting.
• What the change is meant to do, in a line or two
• The language and framework, such as Python with Django or TypeScript with React
• What to focus on, such as bugs, security, speed or tests (optional)
• Test results or the failing error message (optional)

Helpful context (optional)

• The pull request description or ticket, so it knows the goal.
• Your project's coding rules or lint settings, so it skips what a tool already checks.
• The related code the change calls, if the change is small.

Tools and access

• Claude, ChatGPT or Gemini with file upload: It can read a saved diff or several changed files together, and keep the link between them.

Functions and deliverables

• Code reviewer agent: Paste a code change and get a review of bugs, security, tests and clarity. Each point has the reason and a fix, ranked blocker, suggestion or nit.
  • A summary with the main concerns and what is good
  • Blockers, each with where it is, why it matters and a fix to try
  • Suggestions and nits, ranked
  • A list of missing tests for the paths that matter
  • Questions where the intent is unclear, and next steps
  Source: Michael Sitarzewski and Agency Agents contributors.
• Code change security reviewer: Check a code diff for security risks. Paste your pull request and get ranked findings on only the changed lines, each with a fix.
  • A verdict: safe, fix first or look closer
  • Findings with the line, the abuse and the level
  • The smallest fix for each
  • What was not checked
• Bug and security code reviewer: Check code or pull request changes for bugs and security risks, with fixes tied to lines.
  • A review report with line-linked findings
  • Bugs and error paths
  • Security issues
  • Speed and readability notes
  • Suggested fixes
  Source: Burhan Sebin.
• Code security reviewer: Check your Python, JavaScript, TypeScript or Go code for security gaps. Get a ranked code security review with a fix for each gap.
  • Languages and frameworks found
  • Security gaps ranked by seriousness
  • A fix for each gap
  • Safer code for new work
  Source: OpenAI.
• AI project context organiser: Share your project and next task. Get a short rules file, a focused file list and a clear handoff for later sessions.
  • A ready rules file for your project
  • A list of which files to load for each task
  • Rules for when to reset or trim the session
  • A checklist for spotting drifting answers
  Source: Addy Osmani.

Tasks you can use it for

• You wrote a change and want a second pair of eyes before a teammate sees it.
• You review a teammate's change and want help spotting what you might miss.
• You are a solo developer and have no one to review your code.
• Code came from a freelancer or a template and you want it checked before you use it.

Limits to check before starting

• You want a security check only. Use the Code change security reviewer. For a full audit, use the Application security reviewer and a human reviewer.
• You want every new pull request reviewed on a schedule, with history and drafted comments. Use the Pull request review tracker.
• The code was written by an AI tool and you want it checked for typical AI mistakes. Use the AI-written code reviewer.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the pack from this page and add it to your AI as a skill. If you cannot, paste SKILL.md into a new chat, then paste references/source-agent.md.
• Paste the code change. A diff is best. Add the file names, and line numbers if you have them.
• Say what the change should do, the language and framework, and what to focus on. Remove passwords, keys and customer data first. No code running or web access is needed.
• Type "Review this change. Rank every point. Say where it is and why. Mark anything you cannot judge because you did not see the code."
• Read the blockers first. Check each one against your code. Ask for a deeper look at any you do not follow.
• Fix the blockers, then run your own tests. The AI has not run the code, so a review is not proof it works.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/engineering-code-reviewer for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.