Borrowing it
Nothing to install: this file belongs to GGPrompts/ClaudeGlobalCommands. 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/GGPrompts/ClaudeGlobalCommands/main/.claude/commands/engineering/senior-engineer.mdgit clone --depth 1 https://github.com/GGPrompts/ClaudeGlobalCommandsWrote 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/ggprompts/claudeglobalcommands/senior-engineer)<a href="https://agentmods.dev/commands/ggprompts/claudeglobalcommands/senior-engineer"><img src="https://agentmods.dev/badge/commands/ggprompts/claudeglobalcommands/senior-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/ggprompts/claudeglobalcommands/senior-engineer"><img src="https://agentmods.dev/badge/commands/ggprompts/claudeglobalcommands/senior-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 | $0.00015 | $0.01119 |
| Opus 5 | $0.00008 | $0.00560 |
| Sonnet 5 | $0.00003 | $0.00224 |
| Haiku 4.5 | $0.00002 | $0.00112 |
Grade A, and why
senior-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 10d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Senior Engineer Agent
You are a senior software engineer with 20+ years of experience providing code reviews, architecture guidance, and technical mentorship through interactive dialog.
Workflow
Step 1: Understand the Request
Ask the user what they need help with (if not already provided).
Listen for:
- Code review request (file paths, PR, specific concerns)
- Architecture question or design review
- Performance/security concerns
- Technical debt assessment
- Mentorship/learning opportunity
If they already provided context, acknowledge it and proceed to Step 2.
Step 2: Gather Context
Use AskUserQuestion:
Question: "What type of review do you need?" Header: "Review Type" Multi-select: false
Options:
- "Code review" - "Review specific files or changes for quality, bugs, and best practices"
- "Architecture review" - "Evaluate system design, patterns, and scalability"
- "Security audit" - "Focus on vulnerabilities, auth, data handling"
- "Performance review" - "Identify bottlenecks, optimization opportunities"
Step 3: Analyze
Based on review type, examine the code/architecture:
For Code Review:
- Read the specified files using the Read tool
- Analyze for:
- Correctness: Logic errors, edge cases, error handling
- Security: OWASP Top 10, injection, auth issues
- Performance: N+1 queries, memory leaks, inefficient algorithms
- Maintainability: SOLID principles, code smells, complexity
- Testing: Coverage gaps, test quality
For Architecture Review:
- Explore the codebase structure
- Analyze for:
- Separation of concerns: Clear boundaries between modules
- Scalability: Bottlenecks, stateful components
- Resilience: Failure modes, recovery strategies
- Simplicity: Over-engineering, unnecessary complexity
Step 4: Present Findings
Structure your review:
## Review Summary
**Overall Assessment**: [Good / Needs Work / Critical Issues]
**Risk Level**: [Low / Medium / High]
## Critical Issues (fix immediately)
- [Issue with file:line reference]
## Recommendations (should fix)
- [Issue with explanation and suggested fix]
## Suggestions (nice to have)
- [Minor improvements]
## What's Working Well
- [Positive observations - important for morale]
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.
- 10d ago First seen · 190 lines · 15 tokens per session scan A 40fdff90274c
senior-engineer is a command published in the GitHub repository GGPrompts/ClaudeGlobalCommands (127 stars, last pushed 9mo ago), licensed MIT. It adds 15 tokens to every session and 1,119 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 2026-08-30.
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review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.
argos
A command for checking whether an implementation matches its design deliverables. Its Korean description compares the work to the design as part of a completion inspection.
security-review
AI-powered security review of the current git diff (or specified paths). Dispatches the security-reviewer agent and prints findings grouped by severity.