Gemini Peer Review

Consult Gemini as a coding peer for a second opinion on code quality, architecture decisions, debugging, or security reviews.

Setup

API Key

Set

GEMINI_API_KEY

as an environment variable. Get a key from

https://aistudio.google.com/apikey

if you don't have one.

export

GEMINI_API_KEY

=

"your-key-here"

Workflow

Determine mode

from user request (review, architect, debug, security, quick)

Read target files

into context

Build prompt

using the AI-to-AI template from

references/prompt-templates.md

Write prompt to file

at

.claude/artifacts/gemini-prompt.txt

(avoids shell escaping issues)

Call the API

— generate a Python script that:

Reads

GEMINI_API_KEY

from environment

Reads the prompt from

.claude/artifacts/gemini-prompt.txt

POSTs to

https://generativelanguage.googleapis.com/v1beta/models/{model}:generateContent

Payload:

{"contents": [{"parts": [{"text": prompt}]}], "generationConfig": {"temperature": 0.3, "maxOutputTokens": 8192}}

Extracts text from

candidates[0].content.parts[0].text

Prints result to stdout

Write the script to

.claude/scripts/gemini-review.py

and run it.

Synthesize

— present Gemini's findings, add your own perspective (agree/disagree), let the user decide what to implement

Modes

Code Review

Review specific files for bugs, logic errors, security vulnerabilities, performance issues, and best practice violations.

Read the target files, build a prompt using the Code Review template, call with

gemini-2.5-flash

.

Architecture Advice

Get feedback on design decisions with trade-off analysis. Include project context (CLAUDE.md, relevant source files).

Read project context, build a prompt using the Architecture template, call with

gemini-2.5-pro

.

Debugging Help

Analyse errors when stuck after 2+ failed fix attempts. Gemini sees the code fresh without your debugging context bias.

Read the problematic files, build a prompt using the Debug template (include error message and previous attempts), call with

gemini-2.5-flash

.

Security Scan

Scan code for security vulnerabilities (injection, auth bypass, data exposure).

Read the target directory's source files, build a prompt using the Security template, call with

gemini-2.5-pro

.

Quick Question

Fast question without file context. Build prompt inline, write to file, call with

gemini-2.5-flash

.

Model Selection

Mode

Model

Why

review, debug, quick

gemini-2.5-flash

Fast, good for straightforward analysis

architect, security-scan

gemini-2.5-pro

Better reasoning for complex trade-offs

Check current model IDs if errors occur — they change frequently:

curl

-s

"https://generativelanguage.googleapis.com/v1beta/models?key=

$GEMINI_API_KEY

"

|

python3

-c

"import sys,json; [print(m['name']) for m in json.load(sys.stdin)['models'] if 'gemini' in m['name']]"

When to Use

Good use cases

:

Before committing major changes (final review)

When stuck debugging after multiple attempts

Architecture decisions with multiple valid options

Security-sensitive code review

Avoid using for

:

Simple syntax checks (Claude handles these faster)

Every single edit (too slow, unnecessary)

Questions with obvious answers

Prompt Construction

Critical

Always use the AI-to-AI prompting format. Write the full prompt to a file — never pass code inline via bash arguments (shell escaping will break it). When building the prompt: Start with the AI-to-AI header from references/prompt-templates.md Append the mode-specific template Append the file contents with clear --- filename --- separators Write to .claude/artifacts/gemini-prompt.txt Generate and run the API call script Reference Files When Read Building prompts for any mode references/prompt-templates.md