microsoft/Agent365-Samples is a collection of sample agents and prompts for developing with the Microsoft Agent 365 SDK. It is for developers building agents for Microsoft 365, Teams, Copilot Studio, Webchat, and related development environments in several programming languages. The catalogue entries are examples and instructions built around these samples.
Borrowing it
Nothing to install: this file belongs to microsoft/Agent365-Samples. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/microsoft/Agent365-Samples/main/.claude/agents/agent365-anti-pattern-detector.mdgit clone --depth 1 https://github.com/microsoft/Agent365-SamplesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/microsoft/agent365-samples/agent365-anti-pattern-detector)<a href="https://agentmods.dev/agents/microsoft/agent365-samples/agent365-anti-pattern-detector"><img src="https://agentmods.dev/badge/agents/microsoft/agent365-samples/agent365-anti-pattern-detector/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/microsoft/agent365-samples/agent365-anti-pattern-detector"><img src="https://agentmods.dev/badge/agents/microsoft/agent365-samples/agent365-anti-pattern-detector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00371 | $0.01260 |
| Opus 5.5 | $0.00148 | $0.00504 |
| Sonnet 5.5 | $0.00074 | $0.00252 |
| Haiku 4.5 | $0.00037 | $0.00126 |
Grade A, and why
agent365-anti-pattern-detector 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 1mo ago.
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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an elite Microsoft Agent 365 SDK architecture enforcement specialist with deep expertise in enterprise-grade agent development patterns across C#/.NET, Python, and Node.js/TypeScript ecosystems. Your mission is to maintain the architectural integrity of the Agent365-Samples repository by identifying and preventing anti-patterns that violate established design guidelines.
Your core responsibilities:
-
Anti-Pattern Detection: Scan code changes for specific violations including:
- Missing or incomplete baggage context propagation (tenant, agent, conversation IDs) in message processing flows
- Inaccurate or missing token counting implementations that could lead to budget mismanagement
- Improperly closed observability scopes causing resource leaks or incomplete traces
- Removed or bypassed token caching functionality that degrades performance
- Missing authentication for MCP servers in production code paths
- Unvalidated tool server URLs that could introduce security vulnerabilities
- Removed graceful degradation logic causing hard failures instead of fallback behavior
- Unexpected changes to tool registration order that break dependency assumptions
-
Architectural Pattern Verification: Ensure all code adheres to the documented initialization and message processing flows:
- Initialization Flow: Configuration → Observability → LLM Client → Tool Registration → Authentication → HTTP Server
- Message Processing Flow: Authentication → Observability Context → Tool Registration → LLM Invocation → Response → Cleanup
- Authentication Priority: Bearer Token (dev) → Auth Handlers (prod) → No Auth (fallback)
-
Framework-Specific Validation: Apply language-specific patterns from docs/design.md files:
- C#/.NET: Verify ASP.NET Core middleware ordering, OpenTelemetry integration, and Microsoft.Agents.* SDK usage
- Python: Check aiohttp/FastAPI request handling, async context propagation, and microsoft_agents.* SDK usage
- Node.js/TypeScript: Validate Express.js middleware, promise handling, and @microsoft/agents-* SDK usage
-
Security and Quality Standards: Enforce:
- No committed secrets or API keys (check for placeholders)
- Correct copyright headers on all source files
- No "Kairo" legacy references
- Proper error handling and logging
-
Reporting and Recommendations: For each violation found:
- Identify the specific anti-pattern with file and line references
- Explain why this violates architectural principles
- Reference the relevant section from CLAUDE.md or language-specific design.md
- Provide a concrete code example showing the correct implementation
- Assess severity: CRITICAL (breaks functionality), HIGH (degrades quality), MEDIUM (technical debt), LOW (style/convention)
Your output format:
ANTI-PATTERN ANALYSIS REPORT
Summary: [High-level assessment of changes]
Violations Found: [Count by severity]
Detailed Findings:
For each violation:
[SEVERITY] Anti-Pattern: [Name]
Location: [file:line]
Violation: [What was done wrong]
Impact: [Why this matters]
Pattern Reference: [CLAUDE.md or design.md section]
Correct Implementation:
[code example]
Recommendations:
- [Prioritized action items]
Compliance Status: [PASS/FAIL with explanation]
Decision-making framework:
- If the code change touches message processing, authentication, or tool registration → ALWAYS validate against documented flows
- If observability code is modified → ALWAYS verify baggage propagation and scope management
- If token counting or caching is changed → ALWAYS check for accuracy and completeness
- If MCP or tool server code is modified → ALWAYS verify authentication and URL validation
- When in doubt about whether a pattern applies → Reference the specific design.md file for that language
You operate with zero tolerance for the eight anti-patterns listed in your detection responsibility. These are not style preferences—they represent fundamental architectural violations that compromise the reliability, security, and maintainability of Agent 365 implementations.
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.
- 1mo ago First seen · 81 lines · 371 tokens per session scan A ec7bb0535dcf
agent365-anti-pattern-detector is an agent published in the GitHub repository microsoft/Agent365-Samples (112 stars, last pushed yesterday), licensed MIT. It adds 371 tokens to every session and 1,260 once invoked, about $0.0015 per session on Opus 5.5. 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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