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Explore AI failure mode taxonomy to identify risks and improve systems.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.elyngved/failmodes" MCP server from askskill: Run: claude mcp add 'io-github-elyngved-failmodes' -- npx -y failmodes-mcp
Using the Fail Modes taxonomy, list common AI failure modes for a customer support chatbot. Group them by input understanding, reasoning, output safety, and user experience, and explain the risk of each group.
A categorized list of failure modes with risk notes for team review.
Refer to the Fail Modes taxonomy and design 10 evaluation test cases for a text generation model, covering factual errors, prompt injection, overconfident answers, and context omission. Explain the goal of each test.
A set of test cases covering key failure modes, each with a clear evaluation goal.
Based on the Fail Modes taxonomy, identify relevant failure modes for hallucinated citations in a retrieval-augmented generation system, and propose detection methods, mitigation strategies, and a pre-launch checklist.
An analysis of relevant failure modes plus actionable detection, mitigation, and pre-launch checks.
Connect AI to a knowledge base for semantic retrieval and compliant content management.
Provides a live codebase architecture model for analysis and dependency tracing.
Let AI assistants search, run, and manage jobs across fal.ai models.
Discover and run fal models, check pricing, and process local media by chat.
Provide project knowledge search and failure analysis for Claude Code workflows.
Analyze and classify AI systems for EU AI Act compliance risks.