Coding & Debugging
PromptBeginner5 minmarkdown
- Detect debug modes
verbose error output
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Showing 24 of 17,093Categories: Coding & Debugging, Data, Research & Learning, Productivity
Coding & Debugging
PromptBeginner5 minmarkdown
- Search for hardcoded secrets
API keys
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Data
PromptBeginner5 minmarkdown
- Classify changes by risk category (auth
data handling
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Coding & Debugging
PromptBeginner5 minmarkdown
- Note the programming language
framework
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Coding & Debugging
PromptBeginner5 minmarkdown
- **Assess** code quality risks that create security vulnerabilities: race conditions
null pointer dereferences
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Coding & Debugging
PromptBeginner5 minmarkdown
- **Flag** security misconfigurations including debug modes
missing security headers
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Coding & Debugging
PromptBeginner5 minmarkdown
- **Identify** sensitive data exposure such as hardcoded secrets
API keys
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Data
PromptBeginner5 minmarkdown
- **Scan** staged git diffs for injection flaws including SQLi
command injection
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Productivity
PromptBeginner5 minmarkdown
- Assign each task a stable ID (e.g.
TASK-1.1) and use checklist items in outputs.
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Productivity
PromptBeginner5 minmarkdown
- Treat every requirement below as an explicit
trackable task.
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Research & Learning
PromptBeginner5 minmarkdown
You are a senior security researcher and specialist in application security auditing
offensive security analysis
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Coding & Debugging
PromptBeginner5 minmarkdown
**RULE:** When using this prompt
you must create a file named `TODO_perf-tuning.md`. This file must contain the findings resulting from this research as checkable checkboxes that can be coded and tracked by an LLM.,TRUE,TEXT,wkaandem...
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Coding & Debugging
PromptBeginner5 minmarkdown
Write all proposed optimizations and any code snippets to `TODO_perf-tuning.md` only. Do not create any other files. If specific files should be created or edited
include patch-style diffs or clearly labeled file blocks inside the TODO.
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Data
PromptBeginner5 minmarkdown
- **Over-caching without invalidation**: Adding caches without invalidation strategies
serving stale data and creating consistency bugs
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Data
PromptBeginner5 minmarkdown
- **Missing database indexes**: Full table scans on frequently queried columns
causing query times to grow linearly with data volume
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Coding & Debugging
PromptBeginner5 minmarkdown
- **Synchronous blocking in async code**: Blocking the event loop or thread pool with synchronous operations
destroying concurrency benefits
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Data
PromptBeginner5 minmarkdown
- **N+1 query patterns**: Fetching related data in loops instead of using joins or batch queries
multiplying database round-trips linearly
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Data
PromptBeginner5 minmarkdown
### Database (Query Analyzers
Index Tuning)
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Data
PromptBeginner5 minmarkdown
- Deploy Application Performance Monitoring (Datadog
New Relic
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Coding & Debugging
PromptBeginner5 minmarkdown
- Use language-specific CPU and memory profilers (pprof for Go
py-spy for Python
0
Productivity
PromptBeginner5 minmarkdown
- Run Lighthouse for automated audits covering LCP
FID
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Data
PromptBeginner5 minmarkdown
- Use reproducible benchmarks with consistent hardware
data volume
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Coding & Debugging
PromptBeginner5 minmarkdown
- [ ] API response times meet SLA: <200ms (p95) for standard endpoints
<50ms (p95) for database queries
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Coding & Debugging
PromptBeginner5 minmarkdown
- Correlate bottlenecks with specific code paths
queries
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