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CATALOG DOMAIN · 7 CATEGORIES

AI Agents

91 cards

Coding agents, agent frameworks, tools, prompting, evaluation, safety, and autonomous workflows.

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Filtering this domain · category agent-design-and-orchestration · 91 matching cards.

CATEGORYcoding-agents57 public cardsCATEGORYagent-frameworks24 public cardsCATEGORYmcp-and-tools23 public cardsCATEGORYprompting10 public cardsCATEGORYagent-design-and-orchestration91 public cardsCATEGORYmcp-tooling-and-context8 public cardsCATEGORYprompting-and-agent-evaluation11 public cards
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You are a test automation expert specializing in generating comprehensive, maintainable unit tests across multiple languages and frameworks. Create tests that maximize coverage, catch edge cases, and follow best practices for assertion quality and test organization. Use it to give an agent explicit responsibilities, steps and constraints.

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You are a Senior QA Engineer with 15 years of experience in software testing and quality assurance. You are systematic, evidence-driven, and thorough. You test against requirements — you do not modify production code. Use it to give an agent explicit responsibilities, steps and constraints.

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Require a human approval signal before an AI agent can post PR reviews, comments, merges, or writes to CI configuration. Built on protect-mcp + Cedar, with every decision producing an Ed25519-signed receipt that verifies offline. Use it to give an agent explicit responsibilities, steps and constraints.

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1. Keep It DRY : Use templates to avoid repetition 2. Validate Early : Check variables before rendering 3. Version Templates : Track changes like code 4. Test Variations : Ensure templates work with diverse inputs 5. Document Variables : Clearly specify required/op. Use it to give an agent explicit responsibilities, steps and constraints.

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1. Establish Baseline : Always measure initial performance 2. Change One Thing : Isolate variables for clear attribution 3. Test Thoroughly : Use diverse, representative test cases 4. Track Metrics : Log all experiments and results 5. Validate Significance : Use st. Use it to give an agent explicit responsibilities, steps and constraints.

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Few-shot learning enables LLMs to perform tasks by providing a small number of examples (typically 1-10) within the prompt. This technique is highly effective for tasks requiring specific formats, styles, or domain knowledge. Use it to give an agent explicit responsibilities, steps and constraints.

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You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natural language understanding, context management, and seamless integrations. Use it to give an agent explicit responsibilities, steps and constraints.

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