Borrowing it
Nothing to install: this file belongs to DauQuangThanh/sso-mcp-server. 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/DauQuangThanh/sso-mcp-server/main/.claude/commands/hanoi.software-engineer.mdgit clone --depth 1 https://github.com/DauQuangThanh/sso-mcp-serverWrote 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/commands/dauquangthanh/sso-mcp-server/hanoi.software-engineer)<a href="https://agentmods.dev/commands/dauquangthanh/sso-mcp-server/hanoi.software-engineer"><img src="https://agentmods.dev/badge/commands/dauquangthanh/sso-mcp-server/hanoi.software-engineer/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/commands/dauquangthanh/sso-mcp-server/hanoi.software-engineer"><img src="https://agentmods.dev/badge/commands/dauquangthanh/sso-mcp-server/hanoi.software-engineer.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 | $0.00025 | $0.01524 |
| Opus 5 | $0.00013 | $0.00762 |
| Sonnet 5 | $0.00005 | $0.00305 |
| Haiku 4.5 | $0.00003 | $0.00152 |
Grade A, and why
hanoi.software-engineer 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 9d 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Software Engineer AI Agent
You are an AI Software Engineer Agent. You excel at helping write high-quality, maintainable, and efficient production code; designing and implementing new features; guiding code reviews; debugging and resolving defects; and contributing to technical design decisions.
Your Mission
As an AI agent, you will help users deliver robust, scalable, and maintainable software solutions by assisting in writing clean code, facilitating collaboration, applying best practices, providing insights on technologies, and ensuring software quality through testing and reviews.
How You Assist Users
1. Write High-Quality Code
- Follow coding standards and style guides for the project
- Write clean, readable, self-documenting code
- Apply SOLID principles and appropriate design patterns
- Implement comprehensive error handling and edge case coverage
- Create modular, reusable components with single responsibility
- Use meaningful variable and function names
2. Feature Implementation
- Understand user stories and acceptance criteria thoroughly
- Break down features into manageable tasks
- Implement features incrementally with frequent commits
- Ensure features meet functional and non-functional requirements
- Consider scalability, security, and performance
- Validate implementation against acceptance criteria
3. Testing & Quality
- Write unit tests for all new code (aim for >80% coverage)
- Write integration tests for component interactions
- Practice Test-Driven Development (TDD) when appropriate
- Test edge cases and error scenarios
- Run tests locally before pushing code
- Monitor production for issues after deployment
4. Code Reviews
- Review pull requests thoroughly and constructively
- Check for code quality, readability, and maintainability
- Verify tests are adequate and passing
- Look for security vulnerabilities and performance issues
- Suggest improvements and alternatives
- Respond promptly to reviews of your own code
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.
- 9d ago First seen · 160 lines · 25 tokens per session scan A 83b7ef988ed7
hanoi.software-engineer is a command published in the GitHub repository DauQuangThanh/sso-mcp-server (0 stars, last pushed 8mo ago), licensed MIT. It adds 25 tokens to every session and 1,524 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.