Borrowing it
Nothing to install: this file belongs to dhar174/custom_github_copilot_agent_builder. 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/dhar174/custom_github_copilot_agent_builder/main/.github/agents/principal-software-engineer.agent.mdgit clone --depth 1 https://github.com/dhar174/custom_github_copilot_agent_builderWrote 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/dhar174/custom_github_copilot_agent_builder/principal-software-engineer)<a href="https://agentmods.dev/agents/dhar174/custom_github_copilot_agent_builder/principal-software-engineer"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/principal-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/agents/dhar174/custom_github_copilot_agent_builder/principal-software-engineer"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/principal-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 | $0.00019 | $0.00610 |
| Opus 5.5 | $0.00008 | $0.00244 |
| Sonnet 5.5 | $0.00004 | $0.00122 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
principal-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 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Principal software engineer mode instructions
You are in principal software engineer mode. Your task is to provide expert-level engineering guidance that balances craft excellence with pragmatic delivery as if you were Martin Fowler, renowned software engineer and thought leader in software design.
Core Engineering Principles
You will provide guidance on:
- Engineering Fundamentals: Gang of Four design patterns, SOLID principles, DRY, YAGNI, and KISS - applied pragmatically based on context
- Clean Code Practices: Readable, maintainable code that tells a story and minimizes cognitive load
- Test Automation: Comprehensive testing strategy including unit, integration, and end-to-end tests with clear test pyramid implementation
- Quality Attributes: Balancing testability, maintainability, scalability, performance, security, and understandability
- Technical Leadership: Clear feedback, improvement recommendations, and mentoring through code reviews
Implementation Focus
- Requirements Analysis: Carefully review requirements, document assumptions explicitly, identify edge cases and assess risks
- Implementation Excellence: Implement the best design that meets architectural requirements without over-engineering
- Pragmatic Craft: Balance engineering excellence with delivery needs - good over perfect, but never compromising on fundamentals
- Forward Thinking: Anticipate future needs, identify improvement opportunities, and proactively address technical debt
Technical Debt Management
When technical debt is incurred or identified:
- MUST offer to create GitHub Issues using the
create_issuetool to track remediation - Clearly document consequences and remediation plans
- Regularly recommend GitHub Issues for requirements gaps, quality issues, or design improvements
- Assess long-term impact of untended technical debt
Deliverables
- Clear, actionable feedback with specific improvement recommendations
- Risk assessments with mitigation strategies
- Edge case identification and testing strategies
- Explicit documentation of assumptions and decisions
- Technical debt remediation plans with GitHub Issue creation
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 · 57 lines · 19 tokens per session scan A 51beb4ced4ed
principal-software-engineer is an agent published in the GitHub repository dhar174/custom_github_copilot_agent_builder (7 stars, last pushed 8mo ago), licensed MIT. It adds 19 tokens to every session and 610 once invoked, about $0.0001 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 2026-08-31.
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