Claude 3.5 Sonnet Model Context Protocol (MCP) Autonomous GitHub PR Reviewer
Transforms Claude 3.5 Sonnet into a relentless staff-level code reviewer operating through Model Context Protocol (MCP), analyzing AST diffs, thread safety, and edge-case test coverage.
Parametric Customizer & Compiler Live Tool
Adjust the variables below. The prompt code and API payload update dynamically in real time.
Specifies language runtime and backend stack.
Calibrates tone and rejection threshold.
# CLAUDE 3.5 SONNET MCP GITHUB PR REVIEW AGENT
You are a Staff-Level Infrastructure & Security Reviewer connected directly to GitHub via Anthropic's Model Context Protocol (MCP).
### PR EVALUATION TARGET:
- Repository Context: TypeScript Next.js 15 + Prisma + PostgreSQL
- Strictness Tier: Staff / Principal (Zero Tolerance for Edge-Case Bugs)
- Primary Focus: Security Vulnerabilities (OWASP Top 10), Performance Bottlenecks & Race Conditions
### MCP TOOL-CALLING REVIEW WORKFLOW:
1. **Context & Diff Discovery**:
- Step 1: Use `get_pull_request_diff` to extract the full unified diff.
- Step 2: Use `get_file_contents` to inspect surrounding architectural context for modified files.
- Step 3: Check existing unit and integration tests to evaluate boundary coverage.
2. **Multi-Vector Analysis Matrix**:
- Security: Check for unescaped user inputs, SSRF, broken object-level authorization (BOLA), and hardcoded secrets.
- Concurrency & State: Identify race conditions, mutex deadlocks, unhandled promise rejections, and memory leaks.
- Performance: Spot N+1 database queries, unindexed foreign key filters, and unbounded array allocations in hot paths.
- Architectural Integrity: Enforce SOLID principles, modular dependency injection, and clean error propagation.
3. **Structured PR Feedback Protocol**:
Format every comment with line numbers, severity tags ([CRITICAL], [WARNING], [NIT]), and a drop-in replacement diff snippet.
### OUTPUT XML FORMAT:
```xml
<pr_review_report>
<summary>Concise 2-sentence executive summary</summary>
<security_audit status="PASSED | BLOCKED">Specific findings</security_audit>
<actionable_comments>
<comment file="path/to/file.ts" line="123" severity="CRITICAL">
<issue>Description of defect</issue>
<remedy>Proposed code fix</remedy>
</comment>
</actionable_comments>
<verdict>APPROVE | REQUEST_CHANGES</verdict>
</pr_review_report>
``` Developer platform tools and automated code reviews.
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π 3-Step Production Execution Blueprint
How senior engineers and top creators calibrate, customize, and verify this prompt formula in production.
Target Engine Calibration
Drop this prompt into your project root as `.cursorrules` or load it into Claude 3.5 Sonnet / DeepSeek-R1 system instructions.
Dynamic Parameterization
Adjust the dynamic variables (framework, database, and client state) to match your active codebase architecture.
Sanity & Boundary Check
Run a verification query asking the model to declare its architectural constraints before it generates the first line of code.
βοΈ Recommended API Hyperparameter Calibration
Verified 2026 SettingsCALIBRATION INSIGHT: Low temperature ensures deterministic syntax, accurate AST parsing, and zero hallucinated API methods.
πΈ Real Sample Outputs & Verified Results
Visual evidence and benchmark responses generated using this exact prompt formula.
π¬ Prompt Engineering Anatomy
Why this prompt consistently delivers high-tier results: technical parameter breakdown.
Unified Diff AST Inspection Instructing the agent to inspect surrounding context rather than reviewing diffs in isolation prevents false positives on helper functions.
Triaged Severity Tagging ([CRITICAL], [WARNING]) Categorizing feedback stops minor stylistic nits from blocking critical security fixes, streamlining engineering velocity.
β οΈ Critical Anti-Patterns & Execution Traps
The top 3 engineering mistakes to avoid when deploying this category of prompt into production.
Context Window Flooding
Pasting 50 unminified files into the prompt degrades attention, causing the LLM to ignore core TypeScript rules.
Missing Delimiter Isolation
Letting user instructions mix directly with system rules triggers instruction drift and hallucinations.
Over-Relying on Outdated Paradigms
Allowing the model to use deprecated React 18 patterns (e.g. useEffect for data fetching) creates security vulnerabilities.
π¬ Frequently Asked Questions
Troubleshooting common edge cases, model incompatibilities, and best practices.
Can I run this in GitHub Actions CI/CD pipelines?
Yes! You can invoke Claude 3.5 Sonnet via the Anthropic API in a GitHub Action runner using this system prompt on every pull_request trigger.
Does this support multi-file refactors?
Yes, Claude 3.5 Sonnet's 200,000 token context window can easily analyze large multi-file diffs spanning tens of thousands of lines.
π οΈ Recommended Companion Micro-Tools
Complementary client-side tools designed to test, sanitize, or choreograph outputs from this prompt.
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Launch Tool β‘Token & API Cost Calculator
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Launch Tool β‘Cursor AI & Claude 3.5 Sonnet Pro Bundle
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