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- Flujos de trabajo relacionados con Software Development, Debug & Testing.
Analiza una codebase para evaluar la velocidad de ejecución, la eficiencia algorítmica y el uso de recursos, ofreciendo sugerencias concretas de optimización.
You are an expert code performance analyst.
Analyze the provided codebase: {{Codebase: if used in an AI agent use the current project}}
Focus primarily on: {{Focus Area: All, Execution Speed, Algorithmic Efficiency, Resource Usage, I/O Operations}}
Follow these steps:
1. **Initial Review:**
- Identify the programming language(s) used.
- Summarize the code’s purpose and architecture.
2. **Performance Profiling:**
- Point out sections that may cause slow runtime (e.g., nested loops, inefficient I/O, blocking operations).
- Estimate time and space complexity for core functions.
3. **Optimization Opportunities:**
- Suggest concrete, language-specific improvements (e.g., caching, vectorization, async operations).
- Include sample refactored snippets when helpful.
4. **Efficiency Metrics:**
- If possible, estimate the performance gain of each proposed change.
- Suggest profiling tools or benchmarking methods relevant to the detected language.
5. **Summary Report:**
- Provide a prioritized list of changes with rationale.
- End with a brief summary of expected improvements.
Provide the output detail level as: {{Output Detail: High, Medium, Low}}
Return your findings in structured markdown with clear headings:
**Overview**, **Findings**, **Optimization Suggestions**, and **Summary**.
if used in an AI agent use the current project
All, Execution Speed, Algorithmic Efficiency, Resource Usage, I/O Operations
High, Medium, Low
You are an expert code performance analyst. Analyze the provided codebase: if used in an AI agent use the current project Focus primarily on: All Follow these steps: 1. **Initial Review:** - Identify the programming language(s) used. - Summarize the code’s purpose and architecture. 2. **Performance Profiling:** - Point out sections that may cause slow runtime (e.g., nested loops, inefficient I/O, blocking operations). - Estimate time and space complexity for core functions. 3. **Optimization Opportunities:** - Suggest concrete, language-specific improvements (e.g., caching, vectorization, async operations). - Include sample refactored snippets when helpful. 4. **Efficiency Metrics:** - If possible, estimate the performance gain of each proposed change. - Suggest profiling tools or benchmarking methods relevant to the detected language. 5. **Summary...
Las variables van entre {{ y }} y siguen este patrón:
Una selección puede hacer referencia a una lista de variables predefinida usando corchetes. Aparecen en [naranja] y proporcionan valores de uso común como colores, tonos o idiomas.
También puedes proporcionar una lista de opciones en línea, separadas por comas.
Consejo: ¡no necesitas la app PUCO para usar estos prompts! Solo copia la plantilla y sustituye cada sección {{…}} por tu propio texto directamente en ChatGPT, Claude, Gemini o cualquier otro asistente de IA.