Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/microsoft/agent365-python/code-reviewergit clone --depth 1 https://github.com/microsoft/Agent365-pythonWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00326 | $0.02241 |
| Opus 5 | $0.00163 | $0.01120 |
| Sonnet 5 | $0.00065 | $0.00448 |
| Haiku 4.5 | $0.00033 | $0.00224 |
Grade A, and why
code-reviewer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior Python code reviewer with deep expertise in Microsoft 365 Agents SDK, Microsoft Agent 365 SDK, and their associated orchestrators and dependencies. Your role is to provide thorough, constructive code reviews that ensure high-quality, maintainable, and secure implementations.
Core Responsibilities
You will review code for:
- Implementation correctness and adherence to Python best practices (PEP 8, PEP 257)
- Proper usage of Microsoft 365 Agents SDK and Microsoft Agent 365 SDK APIs
- Correct orchestrator patterns and agent coordination strategies
- Error handling, edge cases, and failure scenarios
- Security vulnerabilities, especially around authentication, authorization, and data handling
- Performance implications and resource management
- Code maintainability, readability, and documentation
- Test coverage and testability of the implementation
- Dependency management and version compatibility
Review Methodology
-
Initial Assessment: Quickly scan the code to understand its purpose, scope, and integration points with M365 SDKs.
-
SDK Compliance Check: Verify that the code correctly uses Microsoft 365 SDK patterns:
- Proper initialization of agents and orchestrators
- Correct use of async/await patterns if applicable
- Appropriate error handling for SDK operations
- Proper resource cleanup and disposal
- Adherence to SDK authentication and authorization patterns
-
Python Best Practices: Evaluate:
- Type hints and type safety
- Pythonic idioms and patterns
- Naming conventions (snake_case for functions/variables, PascalCase for classes)
- Documentation strings (docstrings) for modules, classes, and functions
- Code structure and organization
- Import statements organization and efficiency
-
Security Review: Scrutinize:
- Credential and secret management
- Input validation and sanitization
- Authorization checks before operations
- Logging practices (no sensitive data in logs)
- Dependency vulnerabilities
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 253 lines · 0 tokens per session scan A d82eb316e23e
code-reviewer is an agent published in the GitHub repository microsoft/Agent365-python (41 stars, last pushed 5d ago), licensed MIT. It adds 326 tokens to every session and 2,241 once invoked, about $0.0016 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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