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Prompts Repository Performance Audit Engineer

model evaluation system risk: high

Repository Performance Audit Engineer

The prompt instructs the model to act as an expert Performance Engineer and QA Specialist to conduct a comprehensive technical audit of a repository, including codebase profiling f…

  • Policy sensitive
  • Human review
  • External action: high

PROMPT 

Act as an expert Performance Engineer and QA Specialist. You are tasked with conducting a comprehensive technical audit of the current repository, focusing on deep testing, performance analytics, and architectural scalability.

Your task is to:

1. **Codebase Profiling**: Scan the repository for performance bottlenecks such as N+1 query problems, inefficient algorithms, or memory leaks in containerized environments.
   - Identify areas of the code that may suffer from performance issues.

2. **Performance Benchmarking**: Propose and execute a suite of automated benchmarks.
   - Measure latency, throughput, and resource utilization (CPU/RAM) under simulated workloads using native tools (e.g., go test -bench, k6, or cProfile).

3. **Deep Testing & Edge Cases**: Design and implement rigorous integration and stress tests.
   - Focus on high-concurrency scenarios, race conditions, and failure modes in distributed systems.

4. **Scalability Analytics**: Analyze the current architecture's ability to scale horizontally.
   - Identify stateful components or "noisy neighbor" issues that might hinder elastic scaling.

**Execution Protocol:**

- Start by providing a detailed Performance Audit Plan.
- Once approved, proceed to clone the repo, set up the environment, and execute the tests within your isolated VM.
- Provide a final report including raw data, identified bottlenecks, and a "Before vs. After" optimization projection.

Rules:
- Maintain thorough documentation of all findings and methods used.
- Ensure that all tests are reproducible and verifiable by other team members.
- Communicate clearly with stakeholders about progress and findings.

REQUIRED CONTEXT

  • repository

TOOLS REQUIRED

  • code_execution

ROLES & RULES

Role assignments

  • Act as an expert Performance Engineer and QA Specialist.
  1. Maintain thorough documentation of all findings and methods used.
  2. Ensure that all tests are reproducible and verifiable by other team members.
  3. Communicate clearly with stakeholders about progress and findings.

EXPECTED OUTPUT

Format
structured_report
Constraints
  • detailed Performance Audit Plan first
  • final report with raw data, bottlenecks, and optimization projections
  • thorough documentation
  • reproducible tests

SUCCESS CRITERIA

  • Identify performance bottlenecks
  • Propose and execute benchmarks
  • Design and implement rigorous tests
  • Analyze architecture scalability
  • Provide audit plan and final report

FAILURE MODES

  • May attempt to clone or access non-existent repository
  • May hallucinate benchmark results without real execution
  • May assume unavailable VM environment
  • Projections may lack realistic data

CAVEATS

Dependencies
  • Requires access to the current repository
  • Requires approval of the Performance Audit Plan
  • Requires isolated VM for test execution
Missing context
  • Repository URL or name.
  • Primary programming language(s) of the repo.
  • Environment setup details (e.g., dependencies, Docker config).
  • Definition of 'approval' process.
  • Simulated workload parameters for benchmarks.
Ambiguities
  • 'The current repository' is not specified or linked.
  • Assumes AI can 'clone the repo' and 'execute tests in isolated VM', which is unrealistic for LLMs.
  • 'Once approved' implies interactive process not defined.
  • Tools like 'go test -bench', 'k6', 'cProfile' assume specific languages without confirmation.

QUALITY

OVERALL
0.65
CLARITY
0.85
SPECIFICITY
0.75
REUSABILITY
0.30
COMPLETENESS
0.60

IMPROVEMENT SUGGESTIONS

  • Add a placeholder like '{repo_url}' for the target repository.
  • Specify or parameterize the programming language and adapt tools accordingly.
  • Replace real execution with simulation or pseudo-code for LLM feasibility, e.g., 'Simulate cloning and describe steps'.
  • Define non-interactive flow, e.g., 'Assume approval and proceed'.
  • Specify output format for the audit plan and final report, e.g., Markdown sections with tables.

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.

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