Use when the user needs to run GitNexus CLI commands like analyze/index a repo, check status, clean the index, generate a wiki, or list indexed repos. Examples: "Index this repo", "Reanalyze the codebase", "Generate a wiki".
Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: "Why is X failing?", "Where does this error come from?", "Trace this bug".
Use when the user asks how code works, wants to understand architecture, trace execution flows, or explore unfamiliar parts of the codebase. Examples: "How does X work?", "What calls this function?", "Show me the auth flow".
Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?".
Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: "Is it safe to change X?", "What depends on this?", "What will break?".
Use when the user wants to rename, extract, split, move, or restructure code safely. Examples: "Rename this function", "Extract this into a module", "Refactor this class", "Move this to a separate file".
Triage and prioritize vulnerabilities using CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree framework to produce actionable remediation priorities.
Generate AI images with FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, Imagi...
Builds AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities.
Use agents.planners to define any number of planning agents, and optionally agents.judge to override the judge. If agents.judge is omitted, the first planner config is reused as the judge. If agents is omitted in the task spec, the CLI will use the user config file when present, otherwise it falls back to the default…
This guide provides opinionated, actionable best practices for building robust and maintainable LLM applications with langchain-js, emphasizing modularity, type safety, observability, and testing.
Definitive guidelines for writing maintainable, performant, and robust LangChain applications using modern best practices (LCEL, LangGraph, Pydantic, createagent).
This guide provides definitive, actionable best practices for developing with the OpenAI API, covering prompt engineering, robust client usage, agent design, and testing.
This guide defines the definitive best practices for writing TensorFlow code, focusing on tf.keras for models, tf.data for input pipelines, and @tf.function for performance, ensuring reproduc...