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Generate spec compliant Conventional Commit messages with strict formatting and no filler. Enforce consistent commit standards across your team without deviation. Source: https://a
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Fill in your environment, expected vs actual behavior, exact error text, and what you've already tried, and the AI can pinpoint the root cause instead of throwing out random fixes.
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Turns the model into a strict code maintainability reviewer that scores your code, names specific smells, and lists concrete refactoring steps without touching the code itself. Use
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Scans your codebase for swallowed exceptions, unchecked error returns, and misleading log and continue paths, then scores overall error handling quality. Use it before a release or
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Generates a risk ordered refactoring plan that sequences changes from least to most invasive, with a verification test after each step. Use it when you need to modernize or restruc
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Runs a structured senior engineer style review on any code snippet, flagging issues across correctness, security, performance, and readability with a consistent per issue output fo
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Runs a structured comparison of two competing architecture options across seven dimensions like scalability, cost, and complexity, then delivers a direct recommendation plus the sp
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Audits code for injection attacks, authentication flaws, data exposure, and insecure defaults. Returns a prioritized list of findings, each with a severity rating and a concrete fi
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9
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Runs a structured failure mode analysis on a proposed system architecture, ranking the top 5 risks by likelihood times impact with a one sentence mitigation for each. Use it before
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12
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Describe your bug and get back three hypotheses ranked by probability, each with concrete steps to confirm or rule it out. Use it when you're stuck and need a structured starting p
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9
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Breaks a product requirement into named system components with single responsibilities and I/O boundaries before any tech stack is chosen. Use this at the start of design sessions
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10
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Evaluates system architecture proposals by surfacing risks, trade offs, and alternatives you may have missed. Use it before committing to a technical direction or during design rev
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Imagines your system 12 months post launch and catalogs what went wrong, covering data loss, cascading failures, performance cliffs, and operational overload. Use it before finaliz