ai-prompt-engineering
Provides operational guidance for building production-ready prompts in LLM applications, focusing on structured outputs and safety.
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The ai-prompt-engineering skill was audited on Mar 8, 2026 and we found 4 security issues across 2 threat categories. Review the findings below before installing.
Categories Tested
Security Issues
medium line 316
Access to hidden dotfiles in home directory
SourceSKILL.md
| 316 | - **AGENTS.md Integration**: Place project-specific prompt guidance in AGENTS.md files at global (~/.codex/AGENTS.md), project-level (./AGENTS.md), or subdirectory scope for layered instructions |
low line 8
External URL reference
SourceSKILL.md
| 8 | **Modern Best Practices (January 2026)**: versioned prompts, explicit output contracts, regression tests, and safety threat modeling for tool/RAG prompts (OWASP LLM Top 10: https://owasp.org/www-proje |
low line 171
External URL reference
SourceSKILL.md
| 171 | - **Security**: prompt injection, data exfiltration, and tool misuse are primary threats (OWASP LLM Top 10: https://owasp.org/www-project-top-10-for-large-language-model-applications/). |
low line 176
External URL reference
SourceSKILL.md
| 176 | - Align tracing/metrics with OpenTelemetry GenAI semantic conventions (https://opentelemetry.io/docs/specs/semconv/gen-ai/). |
Scanned on Mar 8, 2026
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Categorydevelopment
UpdatedApril 10, 2026
claude-codecodexapiml-ai-engineerdata-scientistproduct-managertechnical-pmgrowth-pmopenaianthropicgoogle-geminidevelopmentdata analyticsproduct
diegosouzapw/awesome-omni-skill