prompt-engineer
Writes, refactors, and evaluates prompts for LLMs — generating optimized prompt templates, structured output schemas, evaluation rubrics, and test suites. Use when designing prompts for new LLM applications, refactoring existing prompts for better accuracy or token efficiency, implementing chain-of-thought or few-shot learning, creating system prompts with personas and guardrails, building JSON/function-calling schemas, or developing prompt evaluation frameworks to measure and improve model performance.
64
75%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/prompt-engineer/SKILL.mdSecurity
1 medium severity finding. This skill can be installed but you should review these findings before use.
W011: Third-party content exposure detected (indirect prompt injection risk)
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
Third-party content exposure detected (high risk: 0.90). The skill's reference materials explicitly include ReAct search tools ("search(query): Search the web" in references/prompt-patterns.md) and RAG/retrieval guidance (references/context-management.md describing "Retrieved Context (RAG)" and how to inject/filter retrieved documents), which indicate the agent will fetch and read untrusted public web/RAG content and use those observations to drive subsequent actions—exposing it to indirect prompt injection risk.
- Repository
- jeffallan/claude-skills
- Commit
e8be415
- Audited
- Security analysis
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