Review only changes since last commit using impact analysis. Token-efficient delta review with automatic blast-radius detection.
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See how to installReview the instructions the agent will receive before you install.
Perform a focused, token-efficient code review of only the changed code and its blast radius.
Token optimization: Before starting, call get_docs_section_tool(section_name="review-delta") for the optimized workflow. Use ONLY changed nodes + 2-hop neighbors in context.
Ensure the graph is current by calling build_or_update_graph_tool() (incremental update).
Get review context by calling get_review_context_tool(). This returns:
Analyze the blast radius by reviewing the impacted_nodes and impacted_files in the context. Focus on:
Perform the review using the context. For each changed file:
query_graph_tool(pattern="tests_for", target=<function_name>)Report findings in a structured format:
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Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
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Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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