diff --git a/examples/README.md b/examples/README.md
index cf088f1726..9c763aface 100644
--- a/examples/README.md
+++ b/examples/README.md
@@ -15,6 +15,7 @@
| Example | Description |
|---------|-------------|
| [deep_research](deep_research/) | Multi-step web research agent using Tavily for URL discovery, parallel sub-agents, and strategic reflection |
+| [code-reviewer](code-reviewer/) | Code review agent that analyzes source code for correctness, style, and security using static analysis and security auditing tools |
| [content-builder-agent](content-builder-agent/) | Content writing agent that demonstrates memory (`AGENTS.md`), skills, and subagents for blog posts, LinkedIn posts, and tweets with generated images |
| [text-to-sql-agent](text-to-sql-agent/) | Natural language to SQL agent with planning, skill-based workflows, and the Chinook demo database |
| [ralph_mode](ralph_mode/) | Autonomous looping pattern that runs with fresh context each iteration, using the filesystem for persistence |
diff --git a/examples/code-reviewer/.env.example b/examples/code-reviewer/.env.example
new file mode 100644
index 0000000000..6a4a49e1e5
--- /dev/null
+++ b/examples/code-reviewer/.env.example
@@ -0,0 +1,12 @@
+# API Keys for Code Reviewer Agent Example
+# Copy this file to .env and fill in your actual API keys
+
+# Anthropic API Key (for Claude Sonnet 4)
+ANTHROPIC_API_KEY=your_anthropic_api_key_here
+
+# OpenAI API Key (for GPT-4o-mini as alternative)
+OPENAI_API_KEY=your_openai_api_key_here
+
+# LangSmith API Key (required for LangGraph local server)
+# Get your key at: https://smith.langchain.com/settings
+LANGSMITH_API_KEY=lsv2_pt_your_api_key_here
diff --git a/examples/code-reviewer/README.md b/examples/code-reviewer/README.md
new file mode 100644
index 0000000000..17339a5d1f
--- /dev/null
+++ b/examples/code-reviewer/README.md
@@ -0,0 +1,152 @@
+# Code Reviewer
+
+## Quickstart
+
+**Prerequisites**: Install [uv](https://docs.astral.sh/uv/) package manager:
+
+```bash
+curl -LsSf https://astral.sh/uv/install.sh | sh
+```
+
+Ensure you are in the `code-reviewer` directory:
+
+```bash
+cd examples/code-reviewer
+```
+
+Install packages:
+
+```bash
+uv sync
+```
+
+Set your API keys in your environment:
+
+```bash
+export ANTHROPIC_API_KEY=your_anthropic_api_key_here # Required for Claude model
+export GOOGLE_API_KEY=your_google_api_key_here # Required for Gemini model ([get one here](https://ai.google.dev/gemini-api/docs))
+export LANGSMITH_API_KEY=your_langsmith_api_key_here # [LangSmith API key](https://smith.langchain.com/settings) (free to sign up)
+```
+
+## Usage Options
+
+You can run this example in two ways:
+
+### Option 1: Direct Python Invocation
+
+Run the code reviewer directly from Python:
+
+```python
+from deepagents import create_deep_agent
+from langchain.chat_models import init_chat_model
+from code_reviewer.tools import analyze_code, security_audit, think_tool
+from code_reviewer.prompts import REVIEW_WORKFLOW_INSTRUCTIONS
+
+model = init_chat_model(model="anthropic:claude-sonnet-4-5-20250929", temperature=0.0)
+
+agent = create_deep_agent(
+ model=model,
+ tools=[analyze_code, security_audit, think_tool],
+ system_prompt=REVIEW_WORKFLOW_INSTRUCTIONS,
+)
+
+result = agent.invoke({
+ "messages": [{
+ "role": "user",
+ "content": """Review this Python code:
+
+def calculate_total(items):
+ total = 0
+ for i in range(len(items)):
+ total = total + items[i]
+ return total
+
+class order_processor:
+ def process(self, data, db_conn, user_id, auth_token, config, callback):
+ eval(data[\"query\"])
+ return \"done\"
+""",
+ }]
+})
+
+print(result["messages"][-1].content)
+```
+
+### Option 2: LangGraph Server
+
+Run a local [LangGraph server](https://langchain-ai.github.io/langgraph/tutorials/langgraph-platform/local-server/) with a web interface:
+
+```bash
+langgraph dev
+```
+
+LangGraph server will open a new browser window with the Studio interface, where you can submit your code for review.
+
+You can also connect the LangGraph server to a [UI specifically designed for deepagents](https://github.com/langchain-ai/deep-agents-ui):
+
+```bash
+git clone https://github.com/langchain-ai/deep-agents-ui.git
+cd deep-agents-ui
+yarn install
+yarn dev
+```
+
+Then follow the instructions in the [deep-agents-ui README](https://github.com/langchain-ai/deep-agents-ui?tab=readme-ov-file#connecting-to-a-langgraph-server) to connect the UI to the running LangGraph server.
+
+This provides a user-friendly interface for submitting code and viewing review reports.
+
+## Custom Model
+
+By default, `deepagents` uses `"claude-sonnet-4-5-20250929"`. You can customize this by passing any [LangChain model object](https://python.langchain.com/docs/integrations/chat/). See the Deep Agents package [README](https://github.com/langchain-ai/deepagents?tab=readme-ov-file#model) for more details.
+
+```python
+from langchain.chat_models import init_chat_model
+from deepagents import create_deep_agent
+
+# Using Claude
+model = init_chat_model(model="anthropic:claude-sonnet-4-5-20250929", temperature=0.0)
+
+# Using Gemini
+from langchain_google_genai import ChatGoogleGenerativeAI
+model = ChatGoogleGenerativeAI(model="gemini-3-pro-preview")
+
+agent = create_deep_agent(
+ model=model,
+)
+```
+
+## Custom Instructions
+
+The code reviewer agent uses custom instructions defined in `code_reviewer/prompts.py` that complement (rather than duplicate) the default middleware instructions. You can modify these in any way you want.
+
+| Instruction Set | Purpose |
+|----------------|---------|
+| `REVIEW_WORKFLOW_INSTRUCTIONS` | Defines the 6-step code review workflow: save request → plan with TODOs → analyze with sub-agents → synthesize → write report → verify. Includes reporting format with severity-based issue classification (Critical, Major, Minor, Suggestion). |
+| `SUBAGENT_DELEGATION_INSTRUCTIONS` | Provides delegation strategies for multi-file reviews. Defaults to 1 sub-agent per review; parallelizes only for logically independent files. Sets limits on parallel execution (max 3 concurrent) and iteration rounds (max 3). |
+| `REVIEWER_INSTRUCTIONS` | Guides individual review sub-agents to analyze code for correctness, style, and security. Includes hard limits on tool calls (2-3 for simple scripts, max 5 for complex code) and emphasizes using `think_tool` after each analysis. |
+
+## Custom Tools
+
+The code reviewer agent adds the following custom tools beyond the built-in deepagent tools. You can also use your own tools, including via MCP servers. See the Deep Agents package [README](https://github.com/langchain-ai/deepagents?tab=readme-ov-file#mcp) for more details.
+
+| Tool Name | Description |
+|-----------|-------------|
+| `analyze_code` | Static analysis tool that uses Python's `ast` module to parse and inspect code structure. Checks for syntax errors, missing docstrings, naming convention violations (snake_case for functions, PascalCase for classes), excessive parameter counts (>5), overly long functions (>50 lines), long lines (>100 chars), and TODO/FIXME markers. Returns a categorized report with severity levels. |
+| `security_audit` | Security vulnerability scanner using regex pattern matching. Detects dangerous functions (eval, exec, pickle), SQL injection via f-strings or string formatting, shell injection (os.system, subprocess with shell=True), hardcoded credentials, unsafe yaml.load, requests without timeouts, and security-relevant comments. Reports findings with severity levels (CRITICAL, HIGH, MEDIUM, LOW). |
+| `think_tool` | Strategic reflection mechanism that helps the agent pause and assess progress between analysis calls, evaluate findings, identify gaps, and plan next steps. |
+
+### Example Analysis Output
+
+When run against code with common issues, the agent produces a structured report like this:
+
+**Correctness:**
+- [critical] Line 12: `eval(data["query"])` can execute arbitrary code — use `ast.literal_eval()` or a safer alternative
+
+**Style:**
+- [minor] Class `order_processor` (line 8) violates PascalCase naming convention
+- [minor] Function `calculate_total` is missing a docstring
+- [minor] Use `for item in items` instead of `for i in range(len(items))` for cleaner iteration
+
+**Security:**
+- [CRITICAL] Line 12: Use of eval() — can execute arbitrary code
+- [HIGH] Line 9: Function `process` has 6 parameters (max recommended: 5)
diff --git a/examples/code-reviewer/agent.py b/examples/code-reviewer/agent.py
new file mode 100644
index 0000000000..21898fe4cc
--- /dev/null
+++ b/examples/code-reviewer/agent.py
@@ -0,0 +1,53 @@
+"""Code Reviewer Agent - Standalone script for LangGraph deployment.
+
+This module creates a code review agent with custom tools and prompts
+for analyzing code correctness, style, and security.
+"""
+
+from deepagents import create_deep_agent
+from langchain.chat_models import init_chat_model
+
+from code_reviewer.prompts import (
+ REVIEWER_INSTRUCTIONS,
+ REVIEW_WORKFLOW_INSTRUCTIONS,
+ SUBAGENT_DELEGATION_INSTRUCTIONS,
+)
+from code_reviewer.tools import analyze_code, security_audit, think_tool
+
+# Limits
+max_concurrent_review_units = 3
+max_reviewer_iterations = 3
+
+# Combine orchestrator instructions (REVIEWER_INSTRUCTIONS only for sub-agents)
+INSTRUCTIONS = (
+ REVIEW_WORKFLOW_INSTRUCTIONS
+ + "\n\n"
+ + "=" * 80
+ + "\n\n"
+ + SUBAGENT_DELEGATION_INSTRUCTIONS.format(
+ max_concurrent_review_units=max_concurrent_review_units,
+ max_reviewer_iterations=max_reviewer_iterations,
+ )
+)
+
+# Create code review sub-agent
+review_sub_agent = {
+ "name": "code-reviewer",
+ "description": "Delegate a file or code snippet for detailed review. Give this reviewer one file or snippet at a time.",
+ "system_prompt": REVIEWER_INSTRUCTIONS,
+ "tools": [analyze_code, security_audit, think_tool],
+}
+
+# Model Gemini 3
+# model = ChatGoogleGenerativeAI(model="gemini-3-pro-preview", temperature=0.0)
+
+# Model Claude 4.5
+model = init_chat_model(model="anthropic:claude-sonnet-4-5-20250929", temperature=0.0)
+
+# Create the agent
+agent = create_deep_agent(
+ model=model,
+ tools=[analyze_code, security_audit, think_tool],
+ system_prompt=INSTRUCTIONS,
+ subagents=[review_sub_agent],
+)
diff --git a/examples/code-reviewer/code_reviewer/__init__.py b/examples/code-reviewer/code_reviewer/__init__.py
new file mode 100644
index 0000000000..7adae43ffa
--- /dev/null
+++ b/examples/code-reviewer/code_reviewer/__init__.py
@@ -0,0 +1,21 @@
+"""Code Reviewer Agent Example.
+
+This module demonstrates building a code review agent using the deepagents package
+with custom tools for code analysis and security auditing.
+"""
+
+from code_reviewer.prompts import (
+ REVIEWER_INSTRUCTIONS,
+ REVIEW_WORKFLOW_INSTRUCTIONS,
+ SUBAGENT_DELEGATION_INSTRUCTIONS,
+)
+from code_reviewer.tools import analyze_code, security_audit, think_tool
+
+__all__ = [
+ "analyze_code",
+ "security_audit",
+ "think_tool",
+ "REVIEWER_INSTRUCTIONS",
+ "REVIEW_WORKFLOW_INSTRUCTIONS",
+ "SUBAGENT_DELEGATION_INSTRUCTIONS",
+]
diff --git a/examples/code-reviewer/code_reviewer/prompts.py b/examples/code-reviewer/code_reviewer/prompts.py
new file mode 100644
index 0000000000..16e56ffd22
--- /dev/null
+++ b/examples/code-reviewer/code_reviewer/prompts.py
@@ -0,0 +1,133 @@
+"""Prompt templates and tool descriptions for the code review deepagent."""
+
+REVIEW_WORKFLOW_INSTRUCTIONS = """# Code Review Workflow
+
+Follow this workflow for all code review requests:
+
+1. **Plan**: Create a todo list with write_todos to break down the review into focused tasks
+2. **Save the request**: Use write_file() to save the code or reference to `/review_request.md`
+3. **Analyze**: Delegate code review tasks to sub-agents using the task() tool - delegate individual files or functions to sub-agents
+4. **Synthesize**: Review all sub-agent findings and consolidate the review
+5. **Write Report**: Write a comprehensive review report to `/review_report.md` (see Report Writing Guidelines below)
+6. **Verify**: Read `/review_request.md` and confirm you've addressed all aspects
+
+## Review Planning Guidelines
+- For single-file reviews, delegate the entire file to one sub-agent
+- For multi-file reviews, delegate one file per sub-agent
+- Each sub-agent should analyze one file or snippet and return findings
+- Focus on actionable, specific feedback rather than general observations
+
+## Report Writing Guidelines
+
+When writing the final report to `/review_report.md`, follow this structure:
+
+### Structure:
+1. **Overview**: Brief summary of what was reviewed
+2. **Correctness**: Logic errors, edge cases, error handling issues
+3. **Style**: Naming conventions, formatting, code organization
+4. **Security**: Vulnerabilities, unsafe patterns, hardcoded secrets
+5. **Recommendations**: Prioritized list of actionable changes
+6. **Summary**: Overall assessment and verdict
+
+### Issue severity levels:
+- **Critical**: Bugs, security vulnerabilities, data loss risks
+- **Major**: Significant code quality or maintainability concerns
+- **Minor**: Style violations, minor inefficiencies
+- **Suggestion**: Optional improvements or best practices
+
+### General guidelines:
+- Use clear section headings (## for sections, ### for subsections)
+- Be specific - include line numbers and code snippets where relevant
+- Prioritize issues: critical > major > minor > suggestion
+- Do NOT use self-referential language ("I found...", "I analyzed...")
+- Write as a professional review without meta-commentary
+- Each issue should include: severity, location, description, and recommendation
+"""
+
+REVIEWER_INSTRUCTIONS = """You are a code reviewer analyzing source code for correctness, style, and security.
+
+
+Your job is to use tools to analyze the provided code and return a detailed review.
+You can call these tools in series or in parallel, your analysis is conducted in a tool-calling loop.
+
+
+
+You have access to the following tools:
+1. **analyze_code**: For static analysis of Python code (AST parsing, naming conventions, complexity)
+2. **security_audit**: For security vulnerability scanning
+3. **think_tool**: For reflection and strategic planning during review
+**CRITICAL: Use think_tool after each analysis to reflect on findings and plan next steps**
+
+
+
+Think like an experienced code reviewer. Follow these steps:
+
+1. **Read the code carefully** - What does it do? What could go wrong?
+2. **Analyze correctness** - Check for logic errors, missing edge cases, exception handling
+3. **Analyze style** - Check naming, formatting, documentation, code organization
+4. **Analyze security** - Check for common vulnerabilities and unsafe patterns
+5. **Stop when you can provide a comprehensive review** - Don't keep analyzing for perfection
+
+
+
+**Analysis Budgets** (Prevent excessive tool calls):
+- **Simple scripts**: Use 2-3 analysis tool calls maximum
+- **Complex code**: Use up to 5 analysis tool calls maximum
+- **Always stop**: After 5 analysis tool calls if you cannot complete the review
+
+**Stop Immediately When**:
+- You can provide a comprehensive review
+- You have identified all critical and major issues
+- Your last 2 analysis calls returned overlapping findings
+
+
+
+After each analysis tool call, use think_tool to reflect:
+- What key issues did I find?
+- What aspects still need review?
+- Do I have enough to provide a comprehensive review?
+- Should I do more analysis or compile my findings?
+
+
+
+When providing your findings back to the orchestrator:
+
+1. **Structure your response**: Organize findings with clear headings by category (Correctness, Style, Security)
+2. **Be specific**: Include line numbers, code snippets, and exact recommendations
+3. **Prioritize issues**: Group by severity (Critical, Major, Minor, Suggestion)
+
+The orchestrator will consolidate findings from all reviewers into the final report.
+
+"""
+
+TASK_DESCRIPTION_PREFIX = """Delegate a task to a specialized sub-agent with isolated context. Available agents for delegation are:
+{other_agents}
+"""
+
+SUBAGENT_DELEGATION_INSTRUCTIONS = """# Sub-Agent Code Review Coordination
+
+Your role is to coordinate code reviews by delegating tasks from your TODO list to specialized review sub-agents.
+
+## Delegation Strategy
+
+**DEFAULT: Start with 1 sub-agent** for most reviews:
+- "Review this single file" → 1 sub-agent (full review)
+- "Check this function for issues" → 1 sub-agent
+
+**Parallelize for multi-file projects:**
+- Multiple independent files → 1 sub-agent per file
+- Only parallelize when files are logically independent
+
+## Key Principles
+- **Bias towards single sub-agent**: One comprehensive review is more token-efficient than multiple narrow ones
+- **Avoid premature decomposition**: Don't break "review file X" into "check correctness", "check style", "check security" - just use 1 sub-agent for all aspects of X
+
+## Parallel Execution Limits
+- Use at most {max_concurrent_review_units} parallel sub-agents per iteration
+- Make multiple task() calls in a single response to enable parallel execution
+- Each sub-agent returns findings independently
+
+## Review Limits
+- Stop after {max_reviewer_iterations} delegation rounds if you haven't completed the review
+- Stop when you have sufficient analysis for a comprehensive review
+- Bias towards focused review over exhaustive analysis"""
diff --git a/examples/code-reviewer/code_reviewer/tools.py b/examples/code-reviewer/code_reviewer/tools.py
new file mode 100644
index 0000000000..52848feed1
--- /dev/null
+++ b/examples/code-reviewer/code_reviewer/tools.py
@@ -0,0 +1,324 @@
+"""Code Review Tools.
+
+This module provides code analysis and security auditing utilities
+for the code reviewer agent, using Python standard library.
+"""
+
+import ast
+import re
+
+from langchain_core.tools import tool
+
+
+def _check_name(name: str, pattern: str, kind: str) -> tuple[bool, str]:
+ """Check if a name matches a naming convention pattern.
+
+ Args:
+ name: The identifier name to check
+ pattern: Regex pattern for the expected convention
+ kind: Description of the convention (e.g., "snake_case")
+
+ Returns:
+ Tuple of (passes, message)
+ """
+ if re.match(pattern, name):
+ return True, ""
+ return False, f" - '{name}' violates {kind} naming convention"
+
+
+def _count_lines(node: ast.AST) -> int:
+ """Count the number of lines in an AST node's source span.
+
+ Args:
+ node: The AST node
+
+ Returns:
+ Line count
+ """
+ if hasattr(node, "end_lineno") and hasattr(node, "lineno"):
+ return node.end_lineno - node.lineno
+ return 0
+
+
+@tool(parse_docstring=True)
+def analyze_code(code: str, filename: str = "") -> str:
+ """Analyze Python code for structural correctness, style, and complexity.
+
+ Uses Python's AST module to parse and analyze the code. Checks for syntax
+ errors, missing docstrings, naming convention violations, excessive
+ complexity, and other structural issues.
+
+ Args:
+ code: The Python source code to analyze
+ filename: Optional filename for error reporting context
+
+ Returns:
+ A formatted analysis report with findings grouped by category
+ """
+ issues: list[str] = []
+ info: list[str] = []
+
+ # 1. Syntax check
+ try:
+ tree = ast.parse(code)
+ except SyntaxError as e:
+ return f"**Syntax Error**: {e.msg} at line {e.lineno}, column {e.offset}"
+
+ # 2. Check for module-level docstring
+ if not ast.get_docstring(tree):
+ issues.append(" - [major] Module is missing a module-level docstring")
+
+ # 3. Walk the AST
+ for node in ast.walk(tree):
+ # Function definitions
+ if isinstance(node, ast.FunctionDef):
+ # Skip dunder methods
+ if node.name.startswith("__") and node.name.endswith("__"):
+ continue
+
+ # Check docstring
+ if not ast.get_docstring(node):
+ issues.append(
+ f" - [minor] Function '{node.name}' (line {node.lineno}) is missing a docstring"
+ )
+
+ # Check naming convention (snake_case)
+ passes, msg = _check_name(
+ node.name, r"^[a-z_][a-z0-9_]*$", "snake_case"
+ )
+ if not passes:
+ issues.append(f" - [minor] {msg} (line {node.lineno})")
+
+ # Check parameter count
+ if len(node.args.args) > 5:
+ issues.append(
+ f" - [major] Function '{node.name}' has "
+ f"{len(node.args.args)} parameters (max recommended: 5)"
+ )
+
+ # Check function length
+ line_count = _count_lines(node)
+ if line_count > 50:
+ issues.append(
+ f" - [major] Function '{node.name}' is {line_count} lines long "
+ "(max recommended: 50)"
+ )
+ elif line_count > 30:
+ issues.append(
+ f" - [minor] Function '{node.name}' is {line_count} lines long "
+ "(consider refactoring)"
+ )
+
+ # Class definitions
+ elif isinstance(node, ast.ClassDef):
+ # Check docstring
+ if not ast.get_docstring(node):
+ issues.append(
+ f" - [minor] Class '{node.name}' (line {node.lineno}) is missing a docstring"
+ )
+
+ # Check naming convention (PascalCase)
+ passes, msg = _check_name(
+ node.name, r"^[A-Z][a-zA-Z0-9]*$", "PascalCase"
+ )
+ if not passes:
+ issues.append(f" - [minor] {msg} (line {node.lineno})")
+
+ # Variable assignments (check for UPPER_CASE constants at module level)
+ elif isinstance(node, ast.Assign):
+ for target in node.targets:
+ if isinstance(target, ast.Name) and target.id.isupper():
+ info.append(
+ f" - Global constant '{target.id}' (line {node.lineno})"
+ )
+
+ # 4. Check for TODO/FIXME comments
+ todo_count = len(re.findall(r"#\s*(TODO|FIXME|HACK|XXX)", code))
+ if todo_count > 0:
+ info.append(f" - Found {todo_count} TODO/FIXME/HACK comment(s)")
+
+ # 5. Line length check
+ long_lines = []
+ for i, line in enumerate(code.split("\n"), 1):
+ if len(line) > 100:
+ long_lines.append(f" Line {i}: {len(line)} chars")
+
+ if long_lines:
+ issues.append(" - [minor] Lines exceeding 100 characters:")
+ issues.extend(long_lines[:5])
+ if len(long_lines) > 5:
+ issues.append(f" ... and {len(long_lines) - 5} more")
+
+ # Build report
+ total_lines = len(code.split("\n"))
+ report = f"## Analysis Report for '{filename}'\n\n"
+ report += f"- **Total lines**: {total_lines}\n"
+ report += f"- **Issues found**: {len(issues)}\n"
+ report += f"- **Info items**: {len(info)}\n\n"
+
+ if issues:
+ report += "### Issues\n\n"
+ report += "\n".join(issues) + "\n\n"
+
+ if info:
+ report += "### Information\n\n"
+ report += "\n".join(info) + "\n"
+
+ if not issues and not info:
+ report += "No issues or notable observations found.\n"
+
+ return report
+
+
+@tool(parse_docstring=True)
+def security_audit(code: str) -> str:
+ """Scan Python code for common security vulnerabilities and unsafe patterns.
+
+ Checks for dangerous function usage (eval, exec, pickle), injection
+ vulnerabilities, hardcoded secrets, unsafe deserialization, and other
+ security antipatterns.
+
+ Args:
+ code: The Python source code to scan
+
+ Returns:
+ A formatted security audit report with findings and severity levels
+ """
+ findings: list[str] = []
+
+ # Dangerous function patterns
+ danger_patterns = [
+ (
+ r"\beval\s*\(",
+ "CRITICAL",
+ "Use of eval() - can execute arbitrary code. Use ast.literal_eval() instead.",
+ ),
+ (
+ r"\bexec\s*\(",
+ "CRITICAL",
+ "Use of exec() - can execute arbitrary code. Avoid dynamic code execution.",
+ ),
+ (
+ r"\bcompile\s*\(",
+ "HIGH",
+ "Use of compile() - can be used to execute arbitrary code if sourced from untrusted input.",
+ ),
+ (
+ r"\bpickle\.loads?\s*\(",
+ "CRITICAL",
+ "Unsafe deserialization with pickle - can execute arbitrary code during unpickling.",
+ ),
+ (
+ r"\byaml\.load\s*\(",
+ "HIGH",
+ "Unsafe yaml.load() - can execute arbitrary code. Use yaml.safe_load() instead.",
+ ),
+ (
+ r"\bos\.system\s*\(",
+ "CRITICAL",
+ "Shell injection risk with os.system(). Use subprocess.run() with shell=False.",
+ ),
+ (
+ r"subprocess\.\w+\s*\(.*shell\s*=\s*True",
+ "CRITICAL",
+ "Shell injection risk with shell=True. Use shell=False and pass args as a list.",
+ ),
+ ]
+
+ # SQL injection patterns
+ sql_patterns = [
+ (
+ r"(execute|executemany)\s*\(\s*f[\"']",
+ "CRITICAL",
+ "SQL injection risk - f-string in database query. Use parameterized queries.",
+ ),
+ (
+ r"(execute|executemany)\s*\(\s*[\"'].*\%\s*",
+ "HIGH",
+ "Possible SQL injection - string formatting in query. Use parameterized queries.",
+ ),
+ ]
+
+ # Other unsafe patterns
+ other_patterns = [
+ (
+ r"requests\.(get|post|put|delete)\s*\([^)]*\)(?!.*timeout)",
+ "MEDIUM",
+ "HTTP request without timeout - can cause hanging connections.",
+ ),
+ (
+ r"#\s*(TODO|FIXME|HACK|XXX|SECURITY)",
+ "LOW",
+ "Security-relevant comment marker found.",
+ ),
+ ]
+
+ # Check all patterns
+ for pattern, severity, message in (
+ danger_patterns + sql_patterns + other_patterns
+ ):
+ for match in re.finditer(pattern, code, re.MULTILINE):
+ line_num = code[: match.start()].count("\n") + 1
+ findings.append(f" - [{severity}] Line {line_num}: {message}")
+
+ # Check for hardcoded secrets in variable assignments
+ for i, line in enumerate(code.split("\n"), 1):
+ stripped = line.strip()
+ if not stripped or stripped.startswith("#"):
+ continue
+ # Check for variable names that look like credentials
+ if re.match(
+ r"(?i)^\s*(api_key|secret|password|token|auth_token)\s*[=:]", stripped
+ ):
+ if not re.search(r"os\.environ|getenv|secrets\.", stripped):
+ findings.append(
+ f" - [HIGH] Line {i}: Possible hardcoded credential in variable assignment"
+ )
+
+ report = "## Security Audit Report\n\n"
+
+ if findings:
+ critical = sum(1 for f in findings if "[CRITICAL]" in f)
+ high = sum(1 for f in findings if "[HIGH]" in f)
+ medium = sum(1 for f in findings if "[MEDIUM]" in f)
+ low = sum(1 for f in findings if "[LOW]" in f)
+
+ report += (
+ f"**Summary**: {len(findings)} finding(s) - "
+ f"{critical} critical, {high} high, {medium} medium, {low} low\n\n"
+ )
+ report += "### Findings\n\n"
+ report += "\n".join(findings) + "\n"
+ else:
+ report += "No security issues detected.\n"
+
+ return report
+
+
+@tool(parse_docstring=True)
+def think_tool(reflection: str) -> str:
+ """Tool for strategic reflection on code review progress and decision-making.
+
+ Use this tool after each analysis to evaluate findings and plan next steps.
+ This creates a deliberate pause in the review workflow for quality assessment.
+
+ When to use:
+ - After analyzing code: What key issues did I find?
+ - Before deciding next steps: Do I have enough for a comprehensive review?
+ - When assessing gaps: What aspects of the code haven't I reviewed?
+ - Before concluding: Can I provide a complete review now?
+
+ Reflection should address:
+ 1. Analysis of current findings - What concrete issues have I identified?
+ 2. Gap assessment - What crucial aspects still need review?
+ 3. Quality evaluation - Do I have sufficient analysis for a good review?
+ 4. Strategic decision - Should I continue analyzing or compile my review?
+
+ Args:
+ reflection: Your detailed reflection on review progress, findings,
+ gaps, and next steps
+
+ Returns:
+ Confirmation that reflection was recorded for decision-making
+ """
+ return f"Reflection recorded: {reflection}"
diff --git a/examples/code-reviewer/langgraph.json b/examples/code-reviewer/langgraph.json
new file mode 100644
index 0000000000..1dd906a841
--- /dev/null
+++ b/examples/code-reviewer/langgraph.json
@@ -0,0 +1,7 @@
+{
+ "dependencies": ["."],
+ "graphs": {
+ "code_review": "./agent.py:agent"
+ },
+ "env": ".env"
+}
diff --git a/examples/code-reviewer/pyproject.toml b/examples/code-reviewer/pyproject.toml
new file mode 100644
index 0000000000..0a1a2db583
--- /dev/null
+++ b/examples/code-reviewer/pyproject.toml
@@ -0,0 +1,63 @@
+[project]
+name = "code-reviewer-example"
+version = "0.1.0"
+description = "Code review agent example using deepagents package"
+requires-python = ">=3.11"
+dependencies = [
+ "langchain-openai>=1.0.2",
+ "langchain-anthropic>=1.0.3",
+ "pydantic>=2.0.0",
+ "rich>=14.0.0",
+ "jupyter>=1.0.0",
+ "ipykernel>=6.20.0",
+ "deepagents>=0.2.6",
+ "python-dotenv>=1.0.0",
+ "langgraph-cli[inmem]>=0.1.55",
+ "langchain-google-genai>=3.1.0",
+]
+
+[tool.uv]
+override-dependencies = [
+ "nbconvert>=7.17.0", # CVE-2025-53000
+ "protobuf>=6.33.5", # CVE-2026-0994
+]
+
+[project.optional-dependencies]
+dev = [
+ "mypy>=1.11.1",
+ "ruff>=0.6.1",
+]
+
+[build-system]
+requires = ["setuptools>=73.0.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools]
+packages = ["code_reviewer"]
+
+[tool.setuptools.package-data]
+"*" = ["py.typed"]
+
+[tool.ruff]
+lint.select = [
+ "E", # pycodestyle
+ "F", # pyflakes
+ "I", # isort
+ "D", # pydocstyle
+ "D401", # First line should be in imperative mood
+ "T201",
+ "UP",
+]
+lint.ignore = [
+ "UP006",
+ "UP007",
+ "UP035",
+ "D417",
+ "E501",
+]
+
+[tool.ruff.lint.per-file-ignores]
+"tests/*" = ["D", "UP"]
+
+[tool.ruff.lint.pydocstyle]
+convention = "google"
diff --git a/examples/code-reviewer/uv.lock b/examples/code-reviewer/uv.lock
new file mode 100644
index 0000000000..cde291b966
--- /dev/null
+++ b/examples/code-reviewer/uv.lock
@@ -0,0 +1,3940 @@
+version = 1
+revision = 3
+requires-python = ">=3.11"
+resolution-markers = [
+ "python_full_version >= '3.15'",
+ "python_full_version == '3.14.*'",
+ "python_full_version < '3.14'",
+]
+
+[manifest]
+overrides = [
+ { name = "nbconvert", specifier = ">=7.17.0" },
+ { name = "protobuf", specifier = ">=6.33.5" },
+]
+
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
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