prompt-engineer-agenticDesigns and optimizes system prompts for advisory AI and autonomous agent systems using a three-layer architecture (Foundation → Structure → Execution). Inte...
Install via ClawdBot CLI:
clawdbot install iops/prompt-engineer-agenticGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 21, 2026
Designing system prompts for an AI that provides personalized investment advice, integrating confidence grading and regulatory compliance using domain calibration to handle high-stakes financial data.
Creating orchestrated prompts for specialized agents that handle inquiries, troubleshooting, and sales in a coordinated manner, using multi-agent extensions to ensure seamless tool use and response consistency.
Iterating on prompts for an AI that assists healthcare professionals by analyzing symptoms and medical records, employing RAG grounding for evidence-based citations and domain calibration for safety-critical applications.
Writing spec-driven prompts for an autonomous agent that retrieves and summarizes case law, using the spec builder to define tool specifications and ensure accurate, verifiable outputs in legal contexts.
Diagnosing and improving prompts for an advisory AI that tutors students in complex subjects, leveraging the three-layer architecture to structure explanations and integrate interactive tool use for learning.
Offering subscription-based consulting to businesses for designing and optimizing AI system prompts, using the skill's modular extensions to tailor solutions for specific domains like finance or healthcare.
Licensing the skill's architecture and spec builder to developers building custom agentic systems, enabling rapid prototyping and deployment with integrated RAG and multi-agent capabilities.
Providing courses and certifications on advanced prompt engineering techniques, leveraging the skill's evidence-graded methods to train professionals in industries adopting AI advisory systems.
💬 Integration Tip
Always load the core reference file first, then selectively add modules based on triggers like RAG needs or domain specificity to avoid overcomplication.
Scored Apr 19, 2026
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